• A

  • Ad Blocking

    Prevents ads from showing up in brand unsafe environments where offensive content has been detected.

  • Ad Fraud

    Actions taken to siphon money from the digital advertising ecosystem without delivering valid audience engagement in return.

  • Ad Injection

    Placement fraud caused by a malicious publisher who owns a browser extension, uses it to inject ad impressions when a user visits certain premium sites, and enjoys premium CPMs for these hijacked impressions.

  • Ad network

    a company that connects publishers (niche website, bloggers) to advertisers (brands and merchants).

  • Addressable Media

    Addressable media refers to any media that can be tied to an individual user, either through a probabilistic or deterministic identifier. For instance, a display ad served in-app can be tied to the user’s device id, making it addressable. However, an ad broadcasted on standard, traditional TV does not pick up any identifier and therefore cannot be traced back to a specific user or household and is therefore not addressable.

    It’s easy to assume that all digital channels are addressable, but this is actually not accurate. Most marketers cannot retrieve specific identifiers from the Walled Gardens, leading to large sections of the digital marketing universe that remain non-addressable.

    Likewise, it’s easy to assume that all offline channels are non-addressable. But once more, this is actually not accurate. Direct mail is very addressable, and the cable companies have been rolling out addressable TV to better compete against IP-enabled digital TV (Connected TV and OTT)

  • Ads.cert

    An Interactive Advertising Bureau protocol augmenting ads.txt that uses cryptographically signed bid requests (a technology similar to blockchain) to authenticate inventory and record its path.

  • Ads.txt

    An Interactive Advertising Bureau text file that lists all approved traffic partners, intended to mitigate inventory sales by unauthorized traffic vendors.

  • Advanced Parameter Spoofing

    Distributed fraud technique combining device ID spoofing and bundle ID spoofing to make it look like many mobile devices are sending requests across many different publishers.

  • Advertiser

    a brand or a merchant who pays publishers to promote its products, services or brand as a whole.

  • Adware

    also referred to as “spyware”. Usually unwanted programs users download without knowing they are part of the deal. They track the user’s behavior and place unwanted ads in their workspace.

  • Affiliate Network

    a company that powers affiliate relationships, connecting advertisers and publishers. Typically, an affiliate network’s fee structure is based on a percentage of revenue generated (or of payouts to publishers), rather than a fixed cost.

  • Affiliate Program

    an arrangement through which the merchant pays a fee to the affiliate publisher for generating leads, clicks or sales from affiliate links. These programs can also be known as partner, associate, or referral programs

  • Alexa Rank

    a platform which ranks and estimates websites based on the user’s browsing habits. Its sample contains all internet users and websites.

  • Algorithmic Attribution

    Algorithmic attribution, also known as machine learning, is the process of assigning a portion of credit for a conversion to each touchpoint based on effectiveness. The key differentiator of algorithmic attribution is its use of advanced statistical modeling and inferences to determine an optimal, custom model that continually refines itself based on your data – put more simply, human assisted machine learning.

  • API

    Application Programming Interface that has a set of rules, routines and protocols that are used for building software with graphical user interface components. APIs allow businesses to access data in an automated fashion.

  • App Install

    Many marketers do have very targeted goals of driving installs of apps they may have recently released, These are often run through Cost-per-install (CPI) programs where the marketer is able to pay their media partners for driving new users to install the app.

    App install is often defined as the success metric for the CPI program, though many CPI programs wait until there is an actual post-app-install transaction before paying out. Because of their walled gardens, it’s actually quite difficult to measure whether the app install reported properly within certain advertisers. In cases where app installs need to be rewarded, the “install event” is often only recognized the first time the user starts up the app.

  • ATF / BTF

    Above The Fold, meaning the ad is viewable upon opening the browser without the user having to scroll. Ads placed lower that do require the user to scroll are Below The Fold.

  • Attributed Conversions

    Refers to the fractional conversions allocated by an attribution model to the channels, campaigns, keywords, placements or whatever attributable element. For instance, for a conversion path consisting of a paid search touchpoint followed by a display touchpoint leading to a single conversion, and assuming an even distribution of credit (i.e. a linear attribution model), the paid search channel gets an attributed conversion of 0.5 and the display channel gets an attributed conversion of 0.5

  • Attributed Revenue

    Refers to the fractional revenue allocated by an attribution model to the channels, campaigns, keywords, placements or whatever attributable element. For instance, for a conversion path consisting of a paid search touchpoint followed by a display touchpoint leading to a single conversion worth $50 in revenue, and assuming an even distribution of credit (i.e. a linear attribution model), the paid search channel gets an attributed revenue of $25 and the display channel gets an attributed conversion of $25.

    Note that advertisers can choose to provide pure revenue for their attribution analysis, but it’s usually better to use net revenue (which takes revenue and subtracts product costs) for your attribution calculation.

  • Attributed ROAS

    ROAS means Return on Ad Spend, and is a derived metric that captures how effective your media investment was in delivering positive value versus how much you spent on that media. Since Return on Ad Spend (ROAS) is a derived metric, attributed credit is not directly distributed to these metrics. Rather, Attributed ROAS is calculated using Attributed Revenue.

    The formula used is:
    Attributed ROAS = Attributed Revenue / Media Cost

  • Attributed ROI

    ROI stands for Return on Investment, and is a derived metric that captures how effective your media investment was.

    It looks at:

    (a) the positive value associated with the user performing the desired action (for instance, making a purchase, where the positive value is the money they spent)
    (b) the cost of the media
    (c) the cost of goods sold (the cost associated with the product.

    As you can tell, Return on Investment (ROI) is related to Return on Ad Spend (ROAS), but also adds the cost of the product in the calculation of the derived metric. Because Attributed ROI is a derived metric, attributed credit is not directly distributed to it. Rather, Attributed ROI is calculated using Attributed Revenue.

    The formula used is:
    Attributed ROI = Attributed Revenue / (Media Cost + Cost of Goods Sold)

  • Attribution

    The process of identifying a set of user actions (“events”) ​that contribute in some manner to a desired outcome, and then assigning a value to each of these events. Marketing attribution provides a level of understanding of what combination of events influence individuals to engage in a desired behavior, typically referred to as a conversion.

    In general, marketers and agencies will use attribution to determine how to distribute credit for a conversion event based on the kinds of exposures and engagement a specific user has gone through in their customer journey on the way to conversion

  • Attribution Fraud

    Occurs when a publisher games an advertiser’s attribution model (by way of click injection, cookie stuffing, etc.) to claim undue credit for driving a payable event.

  • Attribution Model

    An attribution model is a methodology that is applied to all of a campaign’s or advertisers conversion paths in order to determine how to distribute the credit for a conversion. If you are a retailer, for instance, and you find that $200,000 of your revenue in the past month were to users who were exposed to your paid media, attribution models help you figure out how to allocate the credit for the $200,000 across the elements of your paid media. Attribution models help you understand the value of channels, campaigns, placements, keywords, etc… based on the revenue they may have helped generate

    Various attribution models can be compared against each other to determine which is the best fit for your goals and gain a more holistic view of each media’s contribution. There is no one perfect model, an organization should continuously update their models and examine their ability to predict future performance.

  • Attribution, First Click

    first-click attribution is when an advertiser credits a conversion to the first click in a conversion path.

  • Attribution, Last Click

    last-click attribution is when an advertiser credits a conversion to the last click in a conversion path.

  • Attribution, Last-to-Cart

    last-to-cart attribution is when an advertiser credits a conversion to the last click in a conversion path before the consumer places an item in their shopping cart.

  • Attribution, Multi-Touch

    multi-touch attribution is when an advertiser attributes partial credit to each “touch” in a conversion path, rather than giving all the credit to the first, last, or last-to-cart click.

  • Auto-Download Offers

    When a site visitor clicks a banner, the content is downloaded automatically without the user’s consent.

  • Automated Traffic Detection

    Sophisticated algorithms that can accurately identify traffic from botnets, hijacked devices, malicious script injection and other automated means.

  • Data Mining, AI, and Machine Learning

    Data mining techniques can be used to surface anomalous patterns that are found in automated botnet traffic, device farms, emulators and other perfidious fraud tactics. Naturally, any machine learning algorithm works best when monitored, trained, calibrated, and supervised by data scientists with deep fraud expertise.

  • B

  • B2B

    Business-to-business exchange of products or services

  • B2C

    Business-to-consumer exchange of products or services

  • Banner Ad

    A static, animated, or rich media image that partners use to advertise a given product on their webpage.

  • Baseline Conversions

    Baseline conversions, in attribution, refers to the estimated number of conversions that would have happened even without any of the marketing activity being measured by the attribution model. For example, baseline conversions may have been caused by external factors such as hard-to-measure word-of-mouth marketing, or by offline advertising — which cannot be measured by attribution models.

    By establishing the baseline conversions before running attribution, the marketer is able to more precisely calculate the lift provided by their marketing initiatives, and only allocate the incremental conversions to the addressable initiatives being analyzed by the attribution system

  • Bathtub Model

    A bathtub model is a rules-based model that allocates a set amount on the first and last touchpoints of a conversion path, and taking the remainder and allocating an equal amount to the middle touchpoints. For instance, let’s say your conversion path consists of Email >> Video >> Display >> Paid Search >> Retargeting. If we configure the bathtub model to allocate 70% to the end points (meaning that Email gets 35% and Retargeting gets 35%) then the remainder gets distributed evenly to the intervening touchpoints (meaning that Video gets 10%, Display gets 10% and Paid Search gets 10%)

    Note that events may happen beyond a particular lookback window — and these will not receive any credit. For example, if the marketer has a 30-day lookback window in the above example, and a Paid Social event actually happened 31 days before the conversion event — then that Paid Social event does not receive any of the credit because it occurred before the 30-day lookback window.

  • Behavioral and Network Analysis

    Techniques that compare traffic characteristics like IP address and ISP info to a variety of fraud databases that are built off of historical fraud activity to detect invalid traffic through list-based filtration mechanisms.

  • Bias

    The models you use for attribution can introduce bias. For example, last click is biased in favor of channels that appear later in the buy cycle, such as coupon sites that often attract customers right before they buy, though they likely would have bought anyway.

  • Botnet

    A network of corrupted devices manipulated within a command and control architecture to execute malicious instructions and accelerate the velocity of fraudulent activity.

  • Brand Safety

    Verification that the content against which an ad is shown satisfies the advertiser’s threshold for brand integrity (no adults only content, violence, political extremism, etc.).

  • Brand Safety Categories

    There are a standard 12 categories that the advertising industry and marketers consider brand unsafe: obscenity, military conflict, illegal drugs, adult content, firearms, crime, piracy, death/violence, hate speech, terrorism, spam/harmful sites, tobacco.

  • Browser and Device Analysis

    Looks at the remnant clues such as attributes around the browser session for traces of malware, anomalous on-page behavior, faked domains and app ids, deceptive placement handling by malicious publishers and mobile botnets that convincingly, but imperfectly, mimic legitimate traffic.

  • Bundle ID

    A bundle ID is a mobile app’s identifier, much like a domain identifies a mobile website.

  • Bundle ID Spoofing

    Occurs when bad actors misrepresent their inventory’s bundle ID to buyers so that it appears to be associated with a premium app (and a higher CPM), when it’s coming from a dud, low quality traffic source instead.

  • Category-level Attribution

    Attribution is typically run across all conversions that occur within a time period. However, E-Commerce marketers have an opportunity to get more granular, and analyze a subset of their conversions specific to a particular category.

    They can run attribution at the category level in order to answer questions like:

    * Which channels are best at driving revenue for high-margin categories, like lady’s handbags and shoes?
    * Which ones are best at driving conversions for my top-selling men’s shoes category?
    and so forth.

  • Whitelist / Blacklist

    a whitelist defines the domain/apps on which ads exclusively may run. Conversely, a blacklist defines the domains/apps on which ads should not be placed.

  • C

  • Channel

    Attribution is about examining all the various channels that are part of the customer journey – both online and offline. Online channels include search, social, display, affiliate, email and so much more. Offline channels like print, television, radio and outdoor are equally as important in an omnichannel customer journey. The nuance here is that the offline channels must be addressable, i.e. they can be traced back to an online visitor in order for the offline channel to appear in the journey. At the aggregate level, both offline addressable and non-addressable explain overall customer response to marketing stimuli.

  • Channel Predictions

    Channel Predictions predict how a marketer’s KPIs are likely to trend over the next 30 days, allowing them to see how they are pacing to their goals based on a number of inputs.

    Using Channel Level Predictions or Forecasting, a marketers can know in advance when to sit back and relax (because pacing indicates they are likely to crush their goals) and focus on other areas of growth, or, if Forecasting extrapolate that they will miss their KPI goals, they get early-enough warning to go on overdrive and take additional actions to spur growth.

  • Chargeback

    A product that is returned or a sale that falls through. The commission made through sale is deducted from the partner’s payout.

  • Click

    Clicks refer to the action of engaging with the advertiser’s media. On a mobile device, it’s more appropriate to refer to clicks as taps.

    Clicks on many paid search or standard banner ads will typically take users to the advertiser’s website or app.
    However, this may not always be the case — clicks or taps on certain types of display ads may trigger a video or other interactive element that keeps the user on the same page.

  • Click Fraud

    Clicks feigned or spoofed to fool advertiser KPIs, defraud CPC campaigns, or steal attribution for a payable event.

  • Click Tracking

    Click tracking allow tracking solutions such as Impact to track when the user clicks on something. In truth, clicks can either be tracked directly on the website (the user ends up clicking through into a landing page anyway) or can be trafficked in the advertiser’s ad management system as a 3rd party click through callout. In a web environment, the click tracker is often an executable tag, though pixels are also viable. In-app requires a dedicated API for click tracking since Javascript tags cannot be used within an In-app environment. All necessary contextual information about the referrer (the original publisher or media partner source of the click) is passed along with the click tracker

  • Click-Through Rate

    The ratio of clicks to impressions, usually displayed as a percentage.

  • Closer

    A partner who “closes the sale”, causing a consumer to convert. Examples include coupon, deal, loyalty, toolbar, and cart abandonment partners. See also: “Introducer” and “Contributor”.

  • Commission

    Also known as a referral fee and the income the publisher receives for referring a lead to the advertiser’s website.

  • Consumer Journey

    A consumer journey refers to the set of the advertiser’s marketing touchpoints that a particular user is exposed to or engages with over a period of time. It’s easy to confuse the consumer journey with the conversion paths — but they are not the same because many consumer journeys don’t end up with conversions.

    Users who end up converting (i.e. in retail, a conversion is often a successful order. In auto, a conversion is often when a user chooses to ‘schedule a test drive’. Consumers who convert are typically exposed to a number of touchpoints beforehand. When customer journeys lead to a conversion, the customer journey is called a conversion path.

    Not all conversions are driven by advertising. Some people just go directly to the advertiser’s website and make a purchase – even without receiving any exposure to any paid media. Such a conversion would essentially be organic and have a zero-length conversion path

  • Content Farm

    A website that create huge amounts of low-value content to generate clicks and create ad revenue.

  • Content Marketing

    Content marketing refers to a marketing technique where the marketer publishes their own short or long-form content (in any format — written, audio, video) and pushes it out to their audiences in the hope that the intellectual property provides value for the reader. Content marketing can take on a variety of angles, such as beginner’s guides, educational pieces, infographics, thought leadership, research papers, buyer’s guides and more.

    Content marketing stands in contrast to advertising, which is mostly paid marketing used to build awareness or persuade viewers to take action — the concept of intellectual capital is less pronounced in the advertising world versus the advertising world. However — they are very complementary in nature, since advertising can be used to promote and increase awareness of new content marketing pieces provided by the marketer.

    Content marketing is distributed using a variety of methods:

    a) Published on-site. Content marketing is often posted on the marketer’s website, and the marketer uses a variety of technique (paid advertising, organic social posts, email, etc…) to reach audiences and make them aware of the new piece of content marketing, and drive them to the site.

    b) Published on 3rd party sites. Content syndication can happen in a variety of ways. A marketer may work with a trade association to publish their content marketing on their site (and other promotional channels, for example — content marketing may be disbursed to the 3rd party’s newsletters, etc…). A publisher may incorporate the piece of content marketing into their site as a “Sponsored Article” — which is a form of native advertising

  • Content Publisher

    A partner who promotes an advertiser’s goods and services through written content. This can range from an individual blogger to a traditional media company or magazine.

  • Contextual Classification

    Categorization of the page based on some standard (such as the IAB Tech Lab Content Taxonomy) or custom taxonomy.

  • Contributor

    A partner who pushes consumers toward conversion, driving value in the middle of the conversion path. Examples can include content blogs and comparison partners. See also: “Introducer” and “Closer”.

  • Conversion

    Conversions refer to success events — they represent actions that marketers want to their audiences to do. There are online conversions — success events that happen on the digital channel, and offline conversions — success events that happen in the physical world. When a user successfully checks out of the advertiser’s e-commerce site, then that’s an example of an online conversion. Another user may go to the advertiser’s brick & mortar location and buy something — an excellent example of offline conversion.

  • Conversion De-duplication

    A marketer will typically use multiple systems to manage different channels. For instance, they may use an SEM like Kenshoo or Marin to manage paid search, and they may use an Ad Server or DSP like Doubleclick, Sizmek or the Trade Desk to execute their display ads. Each may track conversions independently — and if channel managers are not coordinating, each channel manager is watching their own conversion tracking, and the total number of conversions end up far exceeding the true number of conversions because they are getting overcounted across systems.

    In our example above, if a marketer using different systems for SEM and Display noticed 50 conversions the past day, and noticed that all 50 involved both one Paid Search and one Display event each — then if no one does conversion de-duplication, then the marketer may wrongly conclude that they received 100 conversions over the past day — 50 from paid search and 50 from display.

    That’s why cross-channel leaders recognize the importance of conversion de-duplication. Conversion de-duplication consolidates and reconciles all conversion events, so that duplicated conversion events recognized by separate systems are unified. It is a necessary step for any reliable Customer Journey Analytics or Multi-touch Attribution analysis.

  • Conversion Fraud

    Fraud techniques engineered to exploit performance marketers’ CPA spend by faking or spoofing conversion events.

  • Conversion Path

    The list of “touch points” leading up to a conversion. This includes each time an advertiser “touches” the consumer through one of their own marketing channels (such as a display ad or an email) or through one of their partners.

  • Conversion Paths

    A conversion path refers to the specific subset of consumer journeys that end with a user converting

  • Conversion Rate

    A rate of the number of times a tracking link has lead to a sale vs. the number of times the link has been clicked on, shown in percentage. To calculate this rate, take the amount of sales a banner has generated and divide it by the number of clicks. Multiply by 100 and the answer you get is the conversion rate.

  • Conversion Tracking

    Conversion tracking allow tracking solutions such as Impact to track when the user converts on something. In a web environment, the conversion tracker is often an executable Javascript tag, though pixels are also possible. In-app requires a dedicated API for conversion tracking since Javascript tags do not run within the In-app environment.

  • Cookie

    Cookies are still the primary deterministic identifier in the desktop and mobile web world. Cookies can either be first-party cookies or third-party cookies.

    Apple Safari has been the most restrictive browser and does not allow setting of 3rd party cookies by default on iPhones (though users have the option to alter this behavior from their Browser Settings), and have dramatically limited the lifespan of even first-party cookies with its ITP updates.

    Cookie formats are typically non-standardized as most companies maintain their own cookie pools. They are also pseudonymous – that is, they can be tied to personally identifiable information (PII) but when viewed on their own, don’t tell the viewer anything beyond a string of letters and numbers.

  • Cookie (First Party)

    First party cookies are cookies that are issued by the domain that they are currently browsing on

  • Cookie (Third Party)

    Third party cookies are cookies issued by a domain that is different from the domain the user is currently browsing on

  • Cookie Stuffing

    A type of attribution fraud in which a site visitor receives a third-party cookie unbeknownst to him or her.

  • Cookies

    Information that your computer stores in your web browser when you visit a website or click on a link. It allows websites to keep track of your visits and activity, as well as attribute referrals to the relevant partners. Cookies are considered “first party” if the cookie’s domain matches the site the user is on, and “third party” if the domains do not match.

  • Cost Importers

    Cost importers are Impact’s tools for pulling in media cost data from 3rd party systems within the advertiser’s tech stack. Cost importers are generally IT-less (they do not require a technical resource to implement the integration) and can be fully configured by non-technical resources from the Impact platform directly.

  • Coupon Publisher

    A type of affiliate that generates sales for an advertiser by offering discount codes (also called voucher codes or coupon codes) to their users.

  • CPA

    CPA, or Cost per Acquisition or Cost per Action, is a metric that is tracked in many direct response and performance campaigns, particularly in verticals that are tracking user conversions — whether that conversion represents a sale or a form submission, depending on what the advertiser decides. This is why it’s also often referred to as Cost per Conversion.

    Some marketers will include “clicks” as a viable action — in those cases, the calculation is essentially equivalent to a CPC (Cost per Click).

    A related concept is eCPA, or Effective Cost per Acquisition. This is often calculated by advertisers who pay on another cost basis such as CPM or CPC, but wish to convert it to a Cost per Acquisition in order to optimize their media buying to some Cost per Acquisition target.

    It is calculated as follows:
    ( sum of the relevant media costs / total # of acquisitions )

    So, if a display campaign spent $1,000, and garnered 20 conversions, then the the eCPA = $1000 / 20 = $50

  • CPC

    CPC, or Cost per Click, is a metric that is tracked in many branding, direct response and performance campaigns across any vertical. A click often refers to clickthru on an ad that directs them to the advertiser’s website, though many rich media campaigns may count a click on the ad that triggers some engagement (for instance, the user clicks on the ad to start playing a video, or playing a mini-game on the ad unit); in the rich media situation, this can also be referred to as Cost per Engagement (CPE).

    A related concept is eCPC, or Effective Cost per Click. This is often calculated by advertisers who pay on another cost basis such as CPM, but wish to convert it to a Cost per Click in order to optimize their media buying to some Cost per Click target.

    It is calculated as follows:
    ( sum of the relevant media costs / total # of clicks )

    So, if a display campaign spent $5,000, and garnered 250 clicks, then the the eCPC = $5000 / 250 = $20

  • CPCV

    CPCV, or Cost per Completed View, is a metric that is tracked in many video-based campaign across any vertical. A completed view is often triggered once the viewer of the video reaches the end of the video, though due to the idiosyncracies of many video player platforms, it may be triggered when <100% of the video is viewed.

    A related concept is eCPCV, or Effective Cost per Completed View. This is often calculated by advertisers who pay on another cost basis such as CPM, but wish to convert it to a Cost per Completed View in order to optimize their media buying to some Cost per Completed View target.

    It is calculated as follows:
    ( sum of the relevant media costs / total # of completed views )

    So, if a display campaign spent $10,000, and garnered 200 completed views, then the the eCPC = $10000 / 200 = $50

  • CPI

    Cost per Install, or the price an advertiser pays for each install event in which a user downloads their app.

  • CPL

    CPL, or Cost per Lead, is essentially a subset of CPA, or Cost per Acquisition, specifically used by verticals that require the audience to complete a form with their contact info. For instance, in the insurance vertical, an interested user may have to enter their personal info in order to request an insurance quote or have a broker contact them.

  • CPM

    CPM, or Cost per Mille, or Cost per thousand impressions (mille is the latin word for thousand) is one of the most common ways to purchase advertising today. Though it is used across many branding and direct response campaigns, it is particularly suited for verticals and campaigns intended to raise awareness.

    For instance, if the CPM is priced at $2, and you wish to deliver 1,000,000 impressions, then the cost of the campaign is

    (Total # of impressions / 1000) * $2
    (1,000,000 impressions / 1000) * $2 = $2,000

    Many advertisers running direct response or performance campaigns who pay for media based on CPM will often calculate an eCPC or eCPA as a KPI in order to track their success and to optimize toward lowering that KPI.

  • CPS

    Cost per Sale, or the price an advertiser pays for each referral that ends in a sale. Essentially a subset of CPA, specifically used by verticals that require the audience to complete a sale.

  • CPV

    Cost per View, or the price an advertiser pays for every time their video ad is displayed.

  • CPvM

    CPvM, or Cost per Viewable Impression, is a metric that is tracked in many campaign across any vertical. A viewable impression is generally measured based on IAB standards — that is, for a display ad, 50% of the ad appears on the screen for at least 1 second, and for a video ad, 50% of the ad appears on the screen for at least 2 seconds.

    Since most display or video campaigns today are paid in CPM rather than CPvM, CPvM is usually calculated.

    It is calculated as follows:
    ( sum of the relevant media costs / total # of viewable impressions )

    So, if a display campaign spent $2,000, and garnered 200 viewable impressions, then the the CPvM = $2000 / 200 = $10″

  • Creative

    A promo tool advertisers create to get visitors to click through and take action. Examples include banners, pop-ups, email copy, text links, badges, etc.

  • Creative Fraud

    Creative fraud, or malvertising, is when bad actors inject malicious code in ads in order to cause some type of fraudulent activity, such as generating fake clicks or additional ad calls.

  • Cross-Device Journey

    Cross-device Journey depicts the customers journey regardless of which of their owned device a marketer’s touchpoint reaches them on. This is in contrast with a journey that does not factor in cross-device. A user who was exposed to the marketer’s media touchpoints across their mobile device, tablet and desktop will appear as three separate users with three distinct single-device customer journeys instead of one unified user spanning their many devices.

    This has always been important, but is growing more and more so. In the US, the average user owns over 3 devices — and that number continues to increase each year. In order for marketers to have any reliability in their Customer Journey Analytics or Multi-touch Attribution solution — it must understand the users’ cross-device journey

  • Custom Model

    Custom Models are rules-based attribution models that are completely defined by the marketer’s business rules. They can start with some base rules-based model (i.e. start off with a a linear attribution model) and can be customized to meet just about any business rule the marketer has. For instance, they can implement a Custom Rule that says “Allocate 30% of the credit to the first touchpoint unless the first touchpoint is a website visit. Allocate 20% to the final touchpoint and distribute the remaining credit to the rest of the central touchpoints.”

    Altitude (by Impact) attribution models are very malleable, and Altitude provides pretty flexible ways to shape and customize the attribution model to fit exactly whatever business rule customizations are needed

  • Customer Journey

    The value of attribution is to examine the journey that led to the desired action – this includes cross channel (online, offline) and cross device (desktop, mobile, tablet). 79% of users own three or more devices. Recent studies show that users switch between devices up to 27 times per hour.

  • Customer Journey Analytics

    Customer Journey Analytics refers to a category of marketing intelligence products that deal with analyzing metrics and structures associated with the customer journey.

    Marketers can, for instance, ask questions such as:

    * What is the average number of touchpoints along the customer journey for converting paths?
    The marketer may choose to anti-target a user who dramatically exceeds that average by a wide margin.

    * What is the most popular way that converting paths start?
    The marketer may choose to dial-up some of their investments on these first touch channels or campaigns

    * What is the average duration of a conversion path?
    The marketer may choose to anti-target users who far exceed the typical duration that most users take to convert

    Many of these Customer Journey Analyses can be performed directly from the available Impact reports, though a user who would really like to dig deep into them can analyze individual paths through PAQL, Impact’s proprietary querying language for customer journeys.

    In the future, we anticipate marketers to leverage Customer Journey Analytics to start activating marketing investments to guide users down higher-conversion rate paths.

  • D

  • Browser and Device Analysis

    Looks at the remnant clues such as attributes around the browser session for traces of malware, anomalous on-page behavior, faked domains and app ids, deceptive placement handling by malicious publishers and mobile botnets that convincingly, but imperfectly, mimic legitimate traffic.

  • Daily Budget

    The budget limit for your campaign on a daily basis.

  • Dashboard

    A dashboard is a set of visual widgets that are used by specific roles within a data-driven marketing department to run their business and make decisions. Visual widgets can include longitudinal charts, snapshots-in-time breakdown charts, tables, lists, trending or forecast graphs, real-time KPI scoreboards, goal meters and many other innovative mechanisms to visualize numerical data in order to simplify and bubble up insights.

    Generally, different members of the marketing organization will want to have organize, assemble and tailor their own dashboards to support their unique role, root-cause analysis methodologies and visual preferences. For instance, the CMO Dashboard will in general be far broader and shallower than the Paid Search Manager or Display Dashboards, which would be channel-specific and far more granular

    Dashboards visuals generally fall into a number of major purposes:

    * Monitor Performance – High-level mission control views to monitor on general performance on a regular basis to ensure that day-to-day performance is going according to expectation, and there are no major anomalies in the data (e.g. If one of your channel systems goes down, for instance, marketing leadership may immediately notice a drop in delivered impressions)

    * KPI and Goal Monitors – A data-driven organization always measures KPIs and tracks it to strategic marketing goals. It’s important that every member of the marketing team keeps close tabs of how they are tracking to their goals, and constantly making the required adjustments to make sure they hit them

    * Compare Longitudinally – Time is one of the most important dimensions in marketing analytics, and most growth organizations will want to ensure that certain important metrics (like Attributed Revenue or Return on Ad Spend) are growing month-over-month or year-over-year (particularly for seasonal businesses)

    * Root Cause Analysis – These are drill-down widgets that allow you to look at anomalies and dig deeper into what might be causing a particular trend. The ability to get granular is a crucial part in being able to answer “Why?” questions and derive smart insights that can be used to take action and optimize wisely

  • Data Center

    A large network of computer servers typically used by bad actors to remotely execute various ad fraud techniques.

  • Data Integration

    With so much data available these days, the challenge is to consolidate it all and extract clear, actionable insights. Finding a platform that can systematically integrate data from various sources will help to tame your big data madness.

  • Data Mining, AI, and Machine Learning

    Data mining techniques can be used to surface anomalous patterns that are found in automated botnet traffic, device farms, emulators and other perfidious fraud tactics. Naturally, any machine learning algorithm works best when monitored, trained, calibrated, and supervised by data scientists with deep fraud expertise.

  • Data Quality

    When it comes to data, many marketers intuitively believe in garbage in, garbage out. The data used in attribution modeling needs to be harmonized and cleaned to a common level of granularity so that it is useful. Utilizing data from various sources guarantees disparate data and finding a way to correlate it is critical.

  • Data Silos

    Data silos generally refer to a particularly insidious issue in marketing intelligence that has arisen from the precambrian explosion of channel-specific systems over the past 20 years. As the number of ways for a marketer to reach their audiences through digital media have grown (and continues to grow), point solution systems have emerged to supply planning, workflow and optimization tools for those channels. These tools have generated an ever-growing mass of data, and marketing organizations have typically kept these point solution data as separate siloes to keep their channel teams’ management and optimization processes streamlined.

    Unfortunately, data silos gave rise to a number of problems that have gotten in the way of providing reliable marketing intelligence (and many marketing intelligence systems have simply ignored many of these problems)

    * No Omni-channel View – When data remains fragmented in siloes, then marketing leaders are not able to truly understand, at a holistic level, everything that is going on across their media. Many marketing organizations have taken to exporting reports from different systems, and manually patching together reams of unreconciled Excel spreadsheets together, an error-prone and time consuming task that often arrives too late after campaigns are already over, all in order to simply understand what is happening at a high-level

    * Duplicated, Unreconciled Data – Most systems have mechanisms to optimize for their own channel. These often require firing a conversion tag when a user reaches a success event within the advertiser’s website or mobile app. Unfortunately, each channel system is firing and measuring its own conversion events in an unreconciled way, leading to each channel system claiming credit and resulting in the over-counting of conversions.

    * Potential Bias – Several channel systems have stepped forward to offer themselves as a solution for consolidated channel tracking, but many of these systems are owned by enormous media owners. If the systems that are evaluating performance are also owned by the media owners who are being evaluated, then the potential for introducing bias is great

  • Deep Linking

    A link that allows a website visitor to go to a product page directly. A basic tracking link simply goes to the advertiser’s homepage.

  • Deterministic Identifier

    A deterministic identifier is an identifier that can be definitively tied to a specific user’s device.

    The most common deterministic identifiers include:

    * Cookies — which, despite many actions taken by Safari and Chrome, remain an indispensible identifier in the desktop and mobile web world

    * IFAs — identifiers for advertisers, which are primarily used in the in-app world. Android and iOS platforms maintain their own proprietary scheme for device identification

    * PIIs — short for Personally Identifiable Information, this refers to data that can be tied to an individual, such as login info, email, phone numbers, names, social handles and others

  • Device Farms

    User fraud technique in which agencies and performance partners who are asked by advertisers to “drive performance” for their ad campaigns hire hundreds of low-cost workers in developing countries to browse fake or real websites and “click” on the advertiser’s ad or “install” and open the advertiser’s app.

  • Device Fingerprinting

    Device fingerprinting often leverage either proprietary or open-source methods for collecting data from digital transactions in order to uniquely identify a user.

    This can sometimes lead to a surprising level of accuracy, depending on the technique used. A common fingerprinting mechanism, for example, leverages the specific collection and order of fonts on a user’s device to uniquely identify them.

    Many companies may use some of these methods combined with their own. Because these are simply an approximation of the unique user versus s clear delineation of one, fingerprinting is a probabilistic method – and there is a chance that two users may collide and be confused for each other because they have the same fingerprint.

    Because each vendor has their own secret fingerprinting recipe, the lifespan and scope of a fingerprint varies from vendor to vendor.

  • Device Hijacking

    Occurs when a user downloads a malicious app on their smartphone or tablet, often from a trusted source like the App or Play Store. The app hijacks the device to inflate traffic numbers and steal ad dollars by rapidly loading hidden ads and emulating human behavior. This happens in the background, even when the app is minimized or the device is sleeping.

  • Device ID

    A device ID is the unique identifier for a particular mobile device.

  • Device ID Reset Marathons

    Device ID reset marathons are able to achieve exploitation on a mass scale when device farms execute events (like clicks or installs) and are then reset, each device obtaining a new device ID, and the process runs from the beginning again.

  • Device ID Spoofing

    Fraud operators have started manipulating device ID information (misreporting the device ID associated with their inventory) in order to simulate more normal-looking browsing patterns and fool increasingly sensitive detection methodologies.

  • Device Manipulation Recognition

    Detection methodology that looks for anomalies within traffic to identify instances of device manipulation, where a fraudulent user or bot uses operating system and browser manipulation to spoof their real identity and simulate traffic.

  • Digital Media

    Digital media often refers to all media techniques delivered over the internet or wireless environment, including email, SMS marketing, paid search, paid social, digital video, display, native, digital audio and more. This is in contrast to offline media, which refers to all media techniques related to traditional pre-internet channels

    It is often mistakenly referred to all digital media as addressable media which is erroneous because many digital marketing activities, such as advertising on YouTube or Twitter, actually non-addressable outside of the walled gardens’ tools.

  • Disclosure

    A notice on the partner’s website that notifies readers of the fact that the partner is getting paid for any purchases customers make through their links. It is important to have one to be compliant with FTC laws.

  • Display Advertising

    Commonly understood to mean “banner ad”, but formats have evolved to include rich media ads. Display ads can be static or animated and can remain within their placement on the publisher’s page or expand out of it. Typically tag based.

  • Domain Cloaking

    Occurs when a malicious publisher serves ads in a series of nested iFrames and attempts to cover their tracks by falsely representing one of the intermediate iFrames as originating from a premium publisher.

  • Domain Spoofing

    Occurs when bad actors build malicious sites and sell their inventory to legitimate resellers (networks and exchanges) at a premium by misrepresenting their actual domains and masquerading as premium publishers.

  • Double Opt-In

    A two-step subscription system, in which a website visitor voluntarily fills out a form to receive notifications, and then confirms his or her subscription via email.

  • E

  • Earned Media

    The term Earned Media is often used in conjunction with the other two types of media: Paid Media and Owned Media. Earned Media, as opposed to Paid Media or Owned Media, represents word-of-mouth marketing (content that is generally not paid for) that helps build awareness for the brand, or drives visitors into the advertiser’s owned media.

    Examples of earned media would include social mentions, likes, reviews, SEO, retweets, recommendations. Producing great content (eBooks, webinars, blog posts, etc…) is also an effective vehicle for driving earned media, because that content can be syndicated and generate inbound links, etc…

  • Engagement Metrics

    Measure a user’s engagement with an ad beyond the minimum viewable impression standards. These metrics may include custom viewability measurement (such as the duration a video ad was played) and interactivity measurement (such as direct mouse interactions with a rich media display ad).

  • EPC

    Earnings per click (EPC) is a measurement of how much commission partners tend to make on average for each click they generate for an advertiser’s program. This is a way for partners to estimate how much money they will make on a CPA basis, based on their expected click volume.

  • External Factors

    A strong attribution model will take into account non-marketing elements such as seasonality, major holiday events, macroeconomic factors and competitive activities which can also greatly influence sales.

  • F

  • First Touch Model

    A First Touch model is a rules-based model that allocates 100% of revenue to the very first touchpoint of a conversion path within a given lookback window.. For instance, let’s say your conversion path consists of Email >> Video >> Display >> Paid Search >> Retargeting. In a First Touch Model, 100% of the revenue is credited to the Email event since it is the first touchpoint in the conversion path.

    Note that events may happen beyond a particular lookback window — and these will not receive any credit. For example, if the marketer has a 30-day lookback window in the above example, and a Paid Social event actually happened 31 days before the conversion event — then that Paid Social event does not receive any of the credit because it occurred before the 30-day lookback window.

  • Forecast

    Attribution is no longer about just looking back to see what led to the desired action, it’s about being able to forecast how shifts in spending will ultimately affect your revenue. Forecasting, or marketing mix modeling, is a great tool to help marketers determine optimal media investments.

  • Fraud Intelligence Database

    A fraud intelligence database must be dynamic to capture momentarily current lists of fraudulent IPs and forensic reputation data. This catches the bad actors in digital advertising that tend to use the same tactics to commit fraudulent activity repetitively.

  • Full-Funnel Detection

    A fraud database that spans impression, click, install, and conversion events. Evaluating traffic for fraud across the entire funnel enables sharper detection at each point of the conversion path and allows us to offer unique capabilities- like install attribution fraud detection.

  • G

  • Gateway Tracking

    A legacy tracking method developed by early affiliate networks. In this tracking method, users who click on an affiliate link are routed invisibly through a “gateway” hosted by the affiliate network, then redirected to the advertiser’s content. As the user passes through the gateway, the network places a tracking cookie in their browser.

  • Geo Target

    Allows advertisers to target a specific country, state, province, city, zip code, postal code, area code, or DMA.

  • Geometric Analysis

    A method of data collection and analysis to produce viewability measurement. Commonly utilizes a JS API to measure the coordinates of the ad unit on the page respective to the browser viewport. If the coordinates are outside the browser viewport, the ad is not viewable. When ads are served within unfriendly iFrames, using only the geometrical approach can produce only a small share of measurable impressions, so supplementary viewability measurement methodologies may be used.

  • Ghost Site

    Sites designed to receive bot traffic, and not meant for humans.

  • GIVT

    General Invalid Traffic (GIVT) is traffic that can be easily identified as invalid through routine, list and parameter-based filtration techniques.

  • Goal Tracking

    Goal tracking refers to a practice used by data-driven marketing organizations to measure and keep track of the pacing of their Key Performance Indicators. Well-designed marketing goals and KPIs are designed such that they support even higher-level cross-departmental business goals and KPIs

  • Granular Data

    User-level customer journey data provides a level of granularity that isn’t part of marketing mix models (MMM). The ability to construct the exact sequence of touchpoints leading to a conversion provides a level of insight that can identify correlations between channels and make it possible to optimize your integrated marketing strategy.

  • Gross Rating Point

    GRP stands for Gross Ratings Points, and is used to measure a combination of reach and frequency of a particular ad campaign across the population corresponding to the marketer’s desired audience. It is often used as a measurement of legacy TV reach.

    GRP is calculated using the following formula:
    GRP = 100 * Reach (% of Target Audience) * Average Frequency

    For example, if a marketer wishes to reach females 18-30, and executes a TV campaign that airs on 5 TV episodes for a TV show that reaches 30% of the target audience of females 18-30, then the GRP is 150 (i.e. 100 * 30% * 5).

  • H

  • Hidden Ads

    Is placement fraud caused by a malicious publisher placing ads behind other elements on the page, stuffing ads into nonviewable 1×1 pixels, or loading ads off-screen.

  • Homogeneous Data

    Disparate data is the root of all evil when it comes to attribution. Mapping data from various sources into a single source of the truth is necessary to establish a homogeneous data set for modeling. Don’t start modeling until your data is homogeneous.

  • I

  • IAB

    The Interactive Advertising Bureau is a the standardizing body in the digital advertising ecosystem, developing industry guidelines, conducting research, and providing legal support.

  • Identifiers

    Identifiers are attributes or mechanisms that are primarily used to establish the identity of a user. They are an important building block in much of performance marketing because they help tie different marketing touchpoints (such as ad exposures and paid search clicks) to actual success events (conversion events).

    Identifiers come in two flavors: deterministic identifiers (which can be used to definitively identify a user or device) and probabilistic identifiers (which can be used to approximate the identity of a user or device). The most common types of identifiers are cookies, IFAs, PII and device fingerprints/snapshots

  • Identity Graph

    We’ll use the term identity graph and device graph interchangeably. A Device Graph (as per Digiday) is a map that links an individual to all the devices they use. This could include a person’s computer at work, laptop at home, tablet and smartphone. As the internet of things starts increasing the number of connected, digital, IP-enabled devices owned by a user, the identity graph will grow to also include their OTT/Connected TV, smart speaker, and other smart devices. Instead of counting each device as the behavior of a different person, a device graph counts them as one person, so there’s no duplication. Advertisers can then see things like what time of day a person was exposed to an ad and on which device, which helps show what role any particular ad had in a purchase.

    Identity graphs consist of identifiers matched up with data assets that help link together different identifiers into something that may represent an individual.

    A simple identity graph may consist two identifiers, like cookies, matched together by some shared unique data asset:

    a) A more common identity graph might consist of a set of identifiers that have been mapped to a user through an abstract concept such as a User Id. In this case, we’re not tying the identity of the user to some pseudonymized piece of PII information such as a hashed email, but to a unique user identifier:

    b) As you can see above, the identity graph attempts to “identify” a user by linking together a series of deterministic identifiers such as cookies, IFAs along with pseudonymized deterministic through hashed emails and cookie synching along with probabilistic links through device fingerprinting.

  • Identity Resolution Services

    Identity Resolution Services refer to solutions providers such as TapAd, Drawbridge, Screen6 and others, whose primary activity is building out, enriching and maintaining an identity/device graph of users. These solutions are often integrated with other advertising systems to offer perceivable customer value to the marketer, such as the ability to provide accurate reach metrics, maintain frequency caps, perform smarter targeting, offer more reliable metrics and more.

    Impact solutions such as Radius and Altitude leverage a combination of 3rd party Identity Resolution Services and its own proprietary identity graph, to recognize users across their devices to stitch together omni- channel customer journeys, provide deeper customer journey analytics and calculate more reliable attribution for smarter media optimization.

  • IFA

    IFA stands for Identifiers for Advertisers, and are particularly relevant for the in-app world. These identifiers are maintained by the platforms they are on (usually Apple iOS or Google Android) and are useful for identifying a unique device across all apps on that device. It is typically inaccessible on the mobile browser though.

    Like cookies, they are deterministic and consist of a string of 32 alphanumeric characters and are pseudonymous. Unlike cookies, they are controlled completely by the platforms they are on, and typically (with the exception of fraudulent device reset farms) have a long lifespan.

  • iFrame

    An HTML document embedded in a publisher’s site, used to enable third party ad exchanges and networks to insert ads without compromising that publisher’s security or quality.

  • Image Pixel

    Establishes a browser to server connection allowing IP, UA, and other data points to be passed in the HTTP header.

  • Impact Consortium

    The Impact Consortium is Impact’s own proprietary identity graph, used to power Impact’s expansive attribution capabilities.

    Advertisers who onboard into the Impact Platform have the option to join into the Impact Consortium. If the advertiser passes in customer identity data (say, their email address when the user logs into the secure area of the advertiser’s site) into our Universal Tracking Tag, Impact captures a deterministic identifier that ties a specific user to a device. When the user logs in across multiple devices, and when the advertiser fires the UTT tag across those devices, then the Impact platform is able to tie the user and their multiple devices.

    The Impact Consortium is fully compliant to privacy legislation such as GDPR.

  • Impression

    The number of times a banner ad is viewed by website visitors. One impression means that the ad is displayed only once.

  • Impression Fraud

    Fraud techniques engineered to exploit advertisers’ CPM spend by faking or spoofing impression events.

  • Impression Trackers

    Impression Trackers allow platforms like Impact, with its powerful tracking capabilities, to track when the user receives an impression — usually of a display or video ad.

    Impression trackers are often trafficked in the advertiser’s ad management system as a 3rd party impression callout. In a web environment, the impression tracker is often an executable Javascript tag, with an pixel trackers as backup for environments that do not allow Javascript to be executed.. In-app requires a dedicated API for Impression tracking since Javascript tags cannot be used within an In-app environment. All necessary contextual information about the publisher is passed along with the image tracker

  • In-House

    Advertisers who manage their affiliate program by themselves using an affiliate software or tracking system instead of an affiliate network.

  • In-Stream Video

    Video advertising that generally shows up before, in the middle of, or after other primary content video stream.

  • Inappropriate Domains

    Domains that are unbefitting for ads and would compromise brand image. Examples include pages that feature terrorist sentiments or pornographic elements.

  • Incentivized Affiliates

    Website traffic that is incentivized with actions that will ultimately result in the affiliate earning a commission. Incentives can be prizes, discounts, free subscriptions and others.

  • Incentivized Traffic

    Traffic from users that were offered incentives (like an in-app reward) for clicking through to another other sites. This constitutes user level fraud when supply side players misreport it as organic traffic.

  • Incrementality

    Incrementality refers to a measurement of advertising effectiveness that can be measured by attribution at multiple dimensions of granularity: channel, campaign, keyword, placement, etc… It indicates the amount of lift to a particular metric (i.e. incremental sales, incremental conversions, etc…) that is brought about by the marketing investment — comparing, for example those who were exposed to or clicked on a particular channel, campaign, keyword, placement, etc… versus one who had not had that touchpoint.

    Incrementality can often be measured effectively by more advanced attribution algorithms, such as ones that leverage advanced statistical or machine learning techniques that calculates the likelihood of an increase on the target metric based on the presence or absence of a particular touchpoint in both customer journeys that end in conversion and ones that do not.

  • Influencer

    A social media publisher with a large follower base who promotes brands through social media.

  • Influencer Fraud

    Occurs when a paid influencer uses an illegitimately inflated follower count to ask higher rates of an advertiser for engaging their audience with brand sponsored content.

  • Influencer, Celebrity

    Celebrities are often famous because of reasons outside of social media. They can be movie, tv, music or sports stars. Or they can be “cewebrities” – people who made their fame online, but now are recognized universally. (>1M followers).

  • Influencer, Macro

    These larger influencers have often become popular due to social media. Some may be local celebrities whose renown have been amplified by social tools. Some may be digitally-famous category experts. (10K – 1M followers)

  • Influencer, Micro

    These small influencers are numerous, and are often too fragmented to be managed in a high-touch way. Most of this segment is popular exclusively through social media. (<10K followers)

  • Influencer, Organic

    This is a social influencer of any size who says good things about your brand, despite not being paid for those mentions.

  • Install Attribution Fraud

    Certain partners cheat performance marketers’ CPI campaigns by faking or stealing credit for the actions that led to a user installation.

  • Install Fraud

    Fraud techniques engineered to exploit performance marketers’ CPI spend by faking or spoofing payable app install events.

  • Install Tracking

    Install Tracking is specific to the mobile/tablet world and allows an advertiser to track when their ad campaigns have resulted in a new install. Many marketers run their own Cost-per-install (CPI) programs to encourage users to download their app and use it.

    Since there’s really no way way for you to fire 3rd party tracking code directly in the app store, meaning that there is no way to detect the install event directly from the app store event, most advertisers usually end up firing the Install Tracking Event when it detects that the app has only been opened for the very first time by the new mobile owner.

  • Intersection Object

    A viewability measurement technique specific to Chrome; creates a shape containing only those areas where all components overlap (for example, an ad container). A point is part of an intersection if it is inside both objects (the ad and the ad container).

  • Intra-Device

    Intra-device is particularly applicable to the mobile world, and refers to the ability to recognize a user within the same device, but across mobile web and in-app. Recall that 3rd party cookies are often deactivated in many devices in the mobile web, and unless the user does not clickthru on an ad or affiliate link, there are few alternatives to recognizing the user outside of probabilistic identifiers. When the user goes to a mobile app, on the other hand, there is often a way to recognize the user through deterministic identifiers (IFAs).

    Identity Resolution Services that can bridge the gap and recognize users as they move from mobile web to in-app can map out and include the intra-device journey, which can be woven into an overall understanding of the user’s cross-device journey

  • Introducer

    A partner who “introduces” a product or service to consumers, driving value early in the conversion path. Examples can include social influencers, content partners, and traditional media publishers like news sites and magazines. See also: “Contributor” and “Closer”.

  • Invalid Traffic

    Traffic that does not legitimately fulfill the agreed upon user and placement specifications according to which the ad or audience engagement was purchased.

  • J

  • Javascript Tag

    Gathers information directly from the page, enabling both server-side and session-side analysis. A JS tag integration is necessary for viewability and other verification measurements.

  • Javascript Tracking

    Javascript Tracking is used to signal events to a Tracking Service in the web environments where Javascript is enabled (which will happen in most cases — most users browsing the web on desktop or mobile will usually have Javascript enabled). In web environments where Javascript is disabled, tracking can usually still be accomplished by image trackers. In the in-app world, tracking is usually achieved through API tracking integrations.

    Javascript tracking can be used to track any important web events: impression events (when ads are shown to a user), click events (when ads are clicked on, or when the user lands in one of the advertiser’s properties through an outbound link from an ad or a link from another site, a clickthru from an influencer mention or affiliate link, etc..) and conversion events (when the user makes a purchase, or completes a lead gen form, etc…). It can also measure other related metrics typically associated with web analytics, such as session-level duration, # of pageviews, etc…

  • K

  • Keyword List

    A list of words that a brand does not want adjacent to their ads.

  • KPI

    A KPI, or Key Performance Indicator, is a measurement that will directly affect your marketing objectives. They can be identified by examining your strategic business goals, and deciding how to measure your progress towards those goals. Every business has unique KPIs so be sure you are measuring the most meaningful metrics to make more educated marketing decisions.

    KPIs sometimes correspond to individual metrics, but more often, they are calculated from a series of metrics you are tracking. One common example of a KPI for advertising is ROAS (return on ad spend). ROAS is a measurement that evaluates gross revenue generated for every dollar spent. The math is simple if you have the tracking data you need. ROAS = revenue from ad campaign, minus the cost of the ad campaign, divided by the cost of the ad campaign.

  • L

  • Last Click Model

    Last Click attribution assigns 100% credit to the final touchpoint (i.e. clicks) that immediately precedes a sale or conversion. While last click is important in identifying the closer, marketers should be sure to also examine the introducer (first click) and influencers (middle touches) as well.

  • Legitimate Bots

    There’s a significant number of “good bots” that crawl the web and participate in healthy internet function.

  • Lifetime Value

    The Lifetime Value (or LTV for short) captures the total value generated by a particular customer for a given advertiser, usually because of repeat purchases or conversions made by a given customer. Consumers with high LTV are a brand’s most valuable consumers, and many marketers rightfully attempt to locate audiences that increase their average LTV.

  • Linear Model

    A linear model is a rules-based model and one of the simplest ones for those who are starting out when moving from single-touch attribution models to multi-touch attribution models. A linear model allocates an equal amount of credit to all involved touchpoints of a conversion path. For instance, let’s say your conversion path consists of Email >> Video >> Display >> Paid Search >> Retargeting. The linear model allocates an equal amount to each touchpoint, so Email gets 20%, Video gets 20%, Display gets 20%, Paid Search gets 20% and Retargeting gets 20%.

    Optimizing marketing channels based on an even model means that the advertiser is rewarding frequency alone but not any external factors such as seasonal or macro-economic factors. An issue with this model is that diminishing returns and relative channel effectiveness are not accounted for as all channels and path positions are credited equally so more spend leads to linearly more conversion.

    Note that events may happen beyond a particular lookback window — and these will not receive any credit. For example, if the marketer has a 30-day lookback window in the above example, and a Paid Social event actually happened 31 days before the conversion event — then that Paid Social event does not receive any of the credit because it occurred before the 30-day lookback window.

  • Location Spoofing

    User level fraud technique in which malicious apps report fake location data (latitude, longitude) to media buyers in order to collect high payouts based on a (falsified) premium location.

  • Lookback Window

    A lookback window represents the amount of time (usually specified as a number of days) prior to a conversion that a marketer decides would be a reasonable period of time for a marketing touchpoint to have credibly influenced a customer’s decision to convert. The lookback window is applicable for both single-touch and multi-touch models — both rules-based and machine-learning attribution models.

    If a marketing event took place prior to the lookback window, then it is not considered when the attribution model is applied. For example, if the marketer decides to use a 30-day lookback window (meaning, consider only marketing events 30 days prior to a conversion, but no more), then if a paid social event happened 31 days before a conversion, then it would receive no credit whatsoever for that conversion, regardless of attribution model.

    For most products, a 30-day lookback window is reasonable and standard. Certain types of products, such as autos and durable goods, may opt for a 90-day lookback window as more appropriate to reflect the longer purchase and decision-making cycle for those types of products

  • Loyalty Affiliates

    Similar to incentivized affiliates, in this case users make a longer term commitment to the advertiser and are required to purchase products and participating in activities. Many loyalty affiliates offer cashback to the user in exchange for purchasing from advertisers through their loyalty portal.

  • M

  • Data Mining, AI, and Machine Learning

    Data mining techniques can be used to surface anomalous patterns that are found in automated botnet traffic, device farms, emulators and other perfidious fraud tactics. Naturally, any machine learning algorithm works best when monitored, trained, calibrated, and supervised by data scientists with deep fraud expertise.

  • Machine Learning Attribution

    A machine learning algorithm leverages advanced statistical techniques such as linear and nonlinear regression, cooperative game theory and other data mining methods, to allocate credit in the fairest possible way possible, based on a touchpoint’s propensity to increase an audience’s likelihood to convert. It looks at all the touchpoints — both the presence and absence of touchpoints — and their role in driving incremental value — looking at both the baseline, converting paths and non-converting paths.

    It is often perceived to be the most bias-free of distributing credit, but receives pushback from marketing organizations due to the perceived black box nature of its algorithm, particularly for those unfamiliar with its specific methodology or data science techniques in general. Most attribution vendors will have their own proprietary implementations of data science methodologies and will mix in some of their “secret sauce” in order to provide what they believe, would yield the most optimal set of incrementality calculations for their customers.

  • Malicious App

    A bad behaving publisher that siphons money from the adtech ecosystem by perpetrating various fraudulent actions such as aggressively calling non-viewable ads and running ads in the background of device when it is not even in use.

  • Malicious Bot

    A bot designed to perpetrate ad fraud.

  • Malicious SDK

    A software development kit into which a malware author has written malicious code, which a developer then embeds into its app. Once embedded, the malicious SDK can commit various ad fraud techniques from within the app itself.

  • Malware

    Software that is intended to corrupt devices and device systems. Malware can be used to perpetrate ad fraud by hijacking devices, creatives, browsers, apps, and SDKs.

  • Marketing Event

    A marketing event represents a trackable event such as an exposure to a display ad, watching a video ad, clicking on a paid search or paid social ad, tapping on an affiliate or influencer link, clicking through from an email or newsletter into the website, etc… These marketing events or touchpoints become the basic building blocks of a customer journey, and can be stitched together to illustrate all of the ways the brand has engaged with their audiences in hopefully persuading them to eventually convert.

  • Marketing Intelligence

    Marketing intelligence refers to the systems, skills and processes that allow marketing organizations to make smart, data-informed decisions, usually through well-designed reports, KPIs, dashboards. For our purpose, we hone in on a particularly important marketing question: how to allocate their marketing spend most effectively based on the ROI and incremental value provided by their different marketing investments.

    In order to make informed, holistic decisions specifically around allocating spend, marketers need to look at all aspects of the marketing problem. Marketers thus have to capture information across multiple marketing domains, including customers (which includes current customers and prospective customers), channels, media, customer behavior, sales and more. Marketing intelligence consolidates all this information into a centralized location so that the marketer has an overarching view that they can use to make smart and informed decisions regarding their marketing initiatives and spend.

    Note: The use of the term “Marketing intelligence” can be confusing because it is used quite broadly. For instance, you can read various trade journals and magazines to receive “marketing intelligence” around the latest developments in the industry. This is not what we mean by “Marketing Intelligence” though.

    Salesforce.com, a salesforce automation tool, may provide some marketing intelligence around the prospect funnel. Marketo, a marketing automation tool, may provide some marketing intelligence around customer engagement on the marketer’s email or landing pages. Many of these martech tools might even have sophisticated KPI trackers, visualization or querying platforms to provide intelligence to specific questions in marketing.

    But for our purposes, these are not true “Marketing Intelligence” systems because they focus on very specific problem siloes rather than providing systems that allow marketers to receive marketing intelligence across the larger marketing universe – across channels, campaigns, devices, audience types and vendors – as a whole – which is necessary for answering the larger marketing question focused on smarter allocation of media spend.

  • Marketing System of Record

    A marketing system of record or marketing source of truth (we use the two terms interchangeably) allows users to consolidate all their data into a single platform, and leverage it for to achieve marketing intelligence by applying various data applications such as KPI/goal tracking, scorecarding, dashboarding, reporting and attribution on top of the consolidated data.

    Why do marketing organizations need a system of record?

    Because marketing organizations are experiencing an explosion of marketing technologies that have come about in the past few years to deal with the growing complexity and proliferation of channels they have had to oversee. With over 5,000 marketing technologies available in the market, marketing organizations have a harder and harder time gaining visibility into their investments, what media efforts are truly making an impact on their customers, and which marketing initiatives are delivering positive net value.

    A Marketing System of Record, does the following:

    Collect. Automates the ingestion and consolidation of the marketing campaign data from different systems and different sources stretched out across different channels Reconcile/Normalize. Data consolidated into a single system need to be cleaned up, unified and normalized. Customers who may be recognized by an email address in one system, a cookie in another, and a device id in a third system needed to be reconciled into a single identity Apply. Knowledge-based applications could then be built over this robust source-of-truth for marketing data. This runs a gamut, from analytical applications such as reports, KPI measurement and visualization tools to advanced data applications such as customer journey pathing and attribution analysis

  • Measurability rate

    The rate at which impressions can be measured for viewability. Measurability rates vary by viewability measurement techniques, technologies, and vendors.

  • Measurable impressions

    Indicates the number of impressions for which viewability measurement was possible. Factors that impede viewability measurement include unfriendly iFrames, which prevent viewability measurement vendors from accessing information about the iFrame’s parent site.

  • Media Mix Modeling

    A media mix model is an econometric top-down model that bridges the online world with the offline one. Media Mix Models are great for assessing whether non-addressable media like TV, radio, print, out-of-home and others are pulled into the media mix model, along with external factors such as macroeconomics, weather and seasonality – all these elements can also be factored into the Media Mix Modeling’s longitudinal statistical analytics.

    Media Mix Models, marketers receive guidelines, informed by advanced econometric data, that tell them which factors are most impactful in driving a lift in revenues or conversions, thus giving marketers directional recommendations on how to allocate their media budgets across offline AND online advertising to maximize impact.

  • Mobile Advertising

    In the mobile space, ads can appear on either mobile web or in-app. Mobile is often used to refer to both smartphone and tablet experiences.

  • Model Overfitting

    Overfitting is a modeling error which occurs when a function is too closely fit to a set of data points, which is a no-no in data science and limits the practical usability of a model. One can, in theory, create a model that explains all the data points of a particular test data set extremely well to the point that too many parameters are used to explain away most residual variation (i.e. all the noise). The consequences of using an overfitted model is that the overfitted model becomes ill- suited to explain the behavior of another data set representing the general population, because it has been over tailored to the test data set.

  • Model Validation

    The statistical model used to generate attribution findings should be validated with in-sample as well as holdout sample, or “control” (a sample of data not used in fitting a model) – the holdout sample is used to assess the performance of the models.

  • MRAID

    Mobile Rich Media Ad Interface Definitions is the IAB’s standardization of one common API for in-app rich media ads, supported by multiple SDKs. MRAID is essentially the translator that reconciles the app’s and the ad’s languages. It has been commonly used beyond its intended purpose to measure in-app ad viewability.

  • MRC Accreditation

    The Media Ratings Council standardizes excellent media measurement across vendors and performs annual external audits of rating service operations to determine whether a rating service meets their rigorous standards.

  • Multi-funnel Conversion

    Most conversion funnels are simple – eCommerce funnels often involve only one: Land on the site > shop for a product > add it to cart > checkout > order confirmed!

    However, some businesses rely on far more complicated conversion paths, and may leverage multiple conversion funnels, thus we use the term Multi-funnel Conversions to describe this. Conversion funnels often lead to intermediate “success events”, and it’s not uncommon for marketers to optimize towards these immediate “success events” – especially when the conversion process is complex, lengthy and true value only gets realized after the user makes their way through subsequent conversion funnels. For example, marketers may optimize towards driving users to subscribe to a service/create an account, but not necessarily use the service or perform some revenue-generating task. This is when it’s important for platforms to support the concept of “multi-step conversion funnels”

    Analyzing the behavior across multi-funnel conversions allow marketers to define multiple “success events” and effectively stitch together conversion funnels. By doing so, marketers maintain a view of their short-term conversion performance (which media is driving the most account signups) but are also able to determine which media investments introduce customers who provide true value in the final conversion of a multi-step conversion funnel process (which media is driving the account signups that eventually perform some revenue generating activity later on).

  • Multi-touch Attribution Models

    Multi-Touch Attribution Models (or MTAs for short) are more complicated than Single-touch Attribution Models. MTAs seeks to distribute credit across more than one touchpoint in a conversion path. One of the biggest deficiencies of single-touch attribution models is that it does not recognize a fundamental fact around marketing and advertising: that is, that that marketing and advertising is usually a “team sport” and that multiple touchpoints cooperate together to convince a prospect to eventually convert.

    It’s usually not a one-person effort. Certain type of video advertising may be good in building out awareness. Rich media advertising or email campaigns may be good at building out interest and purchase intent. Paid search may be the final step after the user decides that they already want to make a purchase. All these channels come together to successfully drive a conversion.

  • Multivariate Testing

    A method for optimizing content in which multiple factors are modified, in an attempt to find the optimal combination. See also: “Split Testing”.

  • N

  • Behavioral and Network Analysis

    Techniques that compare traffic characteristics like IP address and ISP info to a variety of fraud databases that are built off of historical fraud activity to detect invalid traffic through list-based filtration mechanisms.

  • Native Advertising

    Has a wide definition, but includes ads that seamlessly blend into the look-and-feel, styling parameters, and editorial content of a publisher site in order to minimize obtrusiveness.

  • NHT

    Non-human traffic is automated invalid traffic. NHT compromises any campaign optimized on human engagement and distorts performance metrics.

  • Niche Marketing

    Targeting advertisements to a specific market segment.

  • Non-Addressable Media

    Non-addressable media refers to any media that cannot be tied to a unique user because no unique identifier can be extracted when the ad is delivered. For instance, when an ad is delivered through traditional TV, Radio, or when an ad is printed on a newspaper or on a billboard, that ad is generally classified as non-addressable. This is in contrast to addressable media, which CAN be tied to an individual user, either through a probabilistic or deterministic identifier. For instance, a display ad served in-app can be tied to the user’s device id, making it addressable.

    It’s easy to assume that all offline channels are non-addressable. But once more, this is actually not accurate. Direct mail is very addressable, and the cable companies have been rolling out addressable TV to better compete against IP-enabled digital TV (Connected TV and OTT)

    Likewise, It’s easy to assume that all digital channels are addressable, but this is actually not accurate. Most marketers cannot retrieve specific identifiers from the Walled Gardens, leading to large sections of the digital marketing universe that remain non-addressable.

  • Non-Converting Paths

    Non-converting paths represent customer journeys that do not resolve into a conversion. This may be because the user has not converted yet, or may never actually convert at all. It is important for marketing intelligence solutions to understand both converting paths and non- converting paths in order to truly understand, from an attribution perspective, how influential different touch points are in truly driving lift and increasing users’ propensity to convert.

  • Normalized Data

    Normalizing data for the purposes of marketing intelligence is the process of organizing data from disparate data sources — often representing different channels and data models — into a centralized repository with data structures that can support all the necessary data regardless of source. Normalization also makes the assumption that the data is de-duplicated and redundancy is reduced, and all important dependencies between the data set are captured in the most efficient way possible

  • O

  • Offer

    Any type of content that’s created by advertisers (merchants) and promoted by partners, which are found in affiliate networks.

  • Offline Conversion

    Offline conversions refer to success events that happen outside of addressable digital channels, such as sales in brick & mortar locations, or closing a sales through the advertiser’s call center, or closing a lead through a third party agent or franchisee. There is usually enough PII information collected from the offline conversion (information such as names, credit card numbers, etc…) that allow marketers to identify the individual performing the offline conversion.

    Through integrations with marketers CRM systems, it should be possible to tie a user’s digital activities (including their marketing journey and online conversions) with offline conversion events.

    Why would a marketer want to do that?

    Because conversions, whether offline or online, do not happen in silos — and being exposed to marketing messages online has been shown to drive sales in the brick & mortar world. Because of the online/offline divide, too many marketers have taken the easier route of associating offline conversions with offline marketing, and online conversions with online marketing — but customers don’t think and behave in such a simplistic manner. By looking at customer journeys that drive both online and offline conversions, marketers are able to obtain a far more accurate picture about the incremental effects of their digital marketing on ALL types of conversion events

  • Offline Media

    Offline media is often used to refer to legacy media techniques that predated the rise of the internet, such as TV, Radio, Print, Direct Mail, Call Centers, Cinema Advertising, Billboards and more. This is in contrast to digital media, which refers to all media techniques related to the internet

    It is often mistakenly referred to as non-addressable media which is erroneous (many direct mail and call center techniques are highly addressable marketing activities).

  • OMID

    The Open Measurement Interface Definition API allows third-party verification vendors to collect viewability measurement signals specific to the in-app environment, supplanting the need for apps to implement each third party vendor’s SDK.

  • Omni-channel

    Omnichannel is defined as a multi-channel sales approach that focuses on an integrated shopping experience across all channels. Customers may encounter many touchpoints and move between online and offline channels, such as ordering online for in-store pickup. Each channel’s role is considered in relation to others and the customer experience is designed to be seamless and consistent.

  • OPM

    Outsourced Program Management (OPM) is a type of agency that will manage an advertiser’s partner program on their behalf.

  • OTS

    Opportunity To Be Seen benchmarks whether an ad was served under conditions that meant it had the potential to be seen by a user, agnostic to whether the user actually viewed it.

  • Out-Stream Video

    Video advertising that acts as a fusion of rich media and in-stream formats, served against non-video content.

  • Outbound Link

    A link to a website other than your own.

  • Owned Media

    The term Owned Media is often used in conjunction with the other two types of media: Paid Media and Earned Media.

    Owned Media refers to all media efforts that are in full control of the advertiser, and generally does not incur any variable payout to an external publisher (i.e. An ad creative may be fully designed and built by the advertiser, but in order to disseminate it, you need to pay publishers to place it on their site). Examples of Owned Media include the advertiser’s website, any media properties or microsites they may own, any mobile apps they build, any blogs they maintain, posts and tweets they may do on any social channels they maintain, customer base email marketing they may do, etc… Furthermore, when marketers invest in enriching one’s owned media, it also pays dividends on the Earned Media front (and, to an extent, on the Paid Media front — for example — better quality landing pages on the advertiser’s site can help improve quality scores on their Paid Search efforts).

  • P

  • Packet Sniffing

    In-app fraud detection technique that includes listening to ad requests from an app, loading any ads returned, and recording on and off-screen activity to compare what is showing on screen to the actual ads loaded by the app. The sniffer does not use a proxy so the app will not know that its network activity is being monitored.

  • Paid Marketing

    Paid Marketing refers to all initiatives undertaken by a marketing organization that requires some form of payment for delivery of exposure, engagement or conversion from the advertiser’s prospective audience. Paid Media, which is often used to describe advertising-like activities, is a subset of Paid Marketing. Apart from advertising, other initiatives that go under paid marketing could include affiliates, influencers, business-to-business strategic partnerships, local and client brand ambassadors and many more.

  • Paid Media

    The term Paid Media is often used in conjunction with the other two types of media: Owned Media and Earned Media.

    Paid Media is often referred to as advertising, and often refers to media exposure that is paid for at either a CPM or fixed-fee typed basis (though much advertising DOES get paid for through alternative payments models like Cost per Click (CPC), Cost per Lead (CPL), Cost per Install (CPI) or Cost per Acquisition (CPA).

    Paid Media typically consist of these formats/channels: Standard Banners, Rich Media, In-Stream Video, Digital Audio, Native, Paid Search, Paid Social, Digital Out of Home, and of course, traditional offline formats/channels such as TV, Radio, Print (Magazines or Newspapers), Outdoor, Cinema, etc…

  • Paid Search

    An advertising model used on many search engines and content sites. In this model, advertisers bid on keywords and phrases that may be relevant to their target, then pay whenever a user clicks on their ad.

  • Partner

    Any individual or business that works with another business for the purposes of promoting that other business’s products or services.

  • Partnership Development

    The practice of discovering and recruiting individuals or businesses who indirectly sell to your target consumer; it also involves marketing to partners in order to incentivize them to take actions that bring in new customers, increase the frequency of repeat customers, and effectively grow your revenue stream outside of traditional sales and marketing channels.

  • Partnership Lifecycle Management

    The complete set of activities used to forge, deepen and optimize an enterprise’s relationship with their partners. The purpose of Partnership Relationship Management is to manage the Partnership Lifecycle.

    The five main stages of Partnerships are:

    1) Identifying and discovering new partners
    2) Engaging and recruiting them,
    3) Onboarding them,
    4) Activating them to start driving revenue and
    5) Growing and cultivating partner relationships – thereby optimizing your partnership program.

  • Partnership Management

    An approach in which a single business unit or department manages all of a businesses partnerships (such as affiliate, social influencer, and strategic partnerships) on a single platform.

  • Pathing

    Pathing refers to the process of stitching together customer journeys and analyzing their structure, metrics and characteristics for additional insight. Stitching customer journeys together can often be a tedious, difficult and error-prone process, and one that cannot be done manually without technological solutions to support it.

    Here are a sampling of difficulties that come from doing this:

    1) Collection and Assembly of Touchpoints. Most marketers on average leverage 12+ different systems to manage and launch their campaigns. Cost and transactional data need to be either ingested into a central system, or the data can be captured through Javascript, Image or API Trackers deployed on every system that needs it.

    2) Reconciliation of Touchpoints across Devices. Most audiences today own 3-4 internet-enabled devices, and that number continues to do up. Stitching together customer journeys require a deep understanding of assembling a cohesive multi-device identity graph to ensure you have a reconciled customer path across all their devices.

  • Pathing and Attribution Querying Language (PAQL)

    The Pathing and Attribution Query Language, or PAQL for short, is a proprietary patent-pending language for marketers to collect customer journeys, across multiple devices and multiple channels, in order to generate custom pathing and attribution marketing insights.

    PAQL can also be used to tailor the behavior of rules-based attribution models in order to fulfill just about any custom business rules required by an organization. PAQL is a highly flexible way of creating bespoke attribution models necessary to meet the unique attribution modeling needs of any marketing organization.

  • Pay-per-post

    A payment model often seen among social influencers, in which the advertiser pays the influencer a flat rate for each post or mention, regardless of performance.

  • Payment Threshold

    The amount of commissions partners are required to earn before being able to withdraw them to their bank account.

  • Payout

    Revenue per one sale or conversion.

  • People-based View

    People-based view refers to looking at marketing data, not as a series of unrelated marketing touchpoints and events, but as a stream of inter-related events tied to a particular person. This means, the marketing intelligence solution needs to normalize and stitch all marketing events and related data points into a unified customer journey, rather than just flat and unreconciled exposure, engagement and financial data. It needs to be able to recognize that disparate events that appear to be happening in different devices owned by the same user (on the user’s desktop, tablet and mobile), even events that appear to be happening in different parts of the same device (mobile web versus in-app) and recognize that these are all the same person.

    When marketing intelligence solutions provide a people-based view, it represents a far more accurate picture about how their marketing initiatives are truly driving prospects into customers, and leads to better optimization decisions versus non people-based views.

    People-based views require that the customer journey:

    1) Represents de-duplicated events. Without a people-based view, different channel systems may lay claim to their own conversion events, leading to significantly over-estimating how many conversions your marketing is actually doing

    2) Represents a cross-device view. Media has long worked in conjunction with each other across a users’ different screens. An old adage says that users don’t think in screens or devices, but marketers, due to the difficulty of managing the proprietary complexities of each device, sometimes have to look at their data device-by-device, instead of recognizing the user behind multiple devices.

    3) Represents an intra-device view. Just because it’s not easy to stitch together the probabilistic world of cookies for mobile web with the deterministic world of IFAs in mobile app, doesn’t mean it shouldn’t be done. Though mobile web only represents 15% of the mobile minute, it is still a significant presence in the mobile channel, the fastest growing channel. Being able to recognize the same user across mobile web and in-app within the same device is paramount for a people- based view

  • Performance Marketing

    Marketing programs in which the advertiser pays their media partners directly for some desired action like a sale, lead or click.

  • Performance Reporting

    Visual and numerical reporting that shows how an advertiser’s partner program or ad campaigns are performing over time — such as how many sales each partner generated over a selected time period.

  • PII

    PII is short for Personally Identifiable Information and generally refers to data that contains personally identifiable information, such as login info, emails, phone numbers, names, social handles, etc… They can be used to link together other identifiers and are a highly reliable, deterministic identifier.

    Because it is information that has been entered by the user, it is often very reliable. It can also be used to bridge the online/offline identification challenge. PII need to conform to the growing demands of privacy legislation such as GDPR.

  • Pixel Tracking

    Pixel Tracking is used to signal events to a Tracking Service in the web environments where Javascript is disabled. Fortunately, in most web environments, Javascript IS enabled, so the preferred methodology is to use Javascript Trackers instead of Pixel Trackers. In the in-app world, tracking is usually achieved through API tracking integrations.

    Pixel tracking can be used to track any important web events: impression events (when ads are shown to a user), click events (when ads are clicked on, or when the user lands in one of the advertiser’s properties through an outbound link from an ad or a link from another site, a clickthru from an influencer mention or affiliate link, etc..) and conversion events (when the user makes a purchase, or completes a lead gen form, etc…)”

  • Placement Level Fraud

    Ad fraud technique in which the user is real, but the ad placement is fake or manipulated.

  • Placement Verification

    Uncovers domain/app masking and spoofing by analyzing discrepancies between referring sources passed through headers, exposing the top level environment in which the user is actually receiving the ad.

  • Post-bid Fraud Detection

    Analyzes the user and placement of an impression after the ad impression is delivered. It can be applied to both premium buys (when advertisers/agencies deliver ads directly to publishers) and programmatic buys (when advertisers/agencies deliver ads via a DSP). Post-bid verification can also measure the viewability of an ad.

  • Post-click Conversion Rate

    Post-click conversion rates represent a measure of users who have both clicked on an ad AND converted.

    The formula is:
    ( # of converting users who have clicked on an ad / # of impressions )

  • Post-impression Conversion Rate

    Post-impression conversion rates represent a measure of users who have both clicked on an ad AND converted.

    The formula is:
    ( # of converting users who have been exposed to an ad / # of impressions )

  • PPC

    Pay per click model, in which an advertiser pays when their ad is clicked on.

  • PPL

    Pay per lead model, in which an advertiser pays when their site visitor provides their contact information to the advertiser.

  • PPS

    Pay per sale model, in which an advertiser pays the affiliate only when a sale happens.

  • Pre-bid Filtering

    Evaluates a placement for brand safety, contextual appropriateness, and ad fraud before a bid is placed. A bid is only placed if verification conditions determined by the advertiser are met.

  • Pre-bid Fraud Detection

    Is a solution to use under a variety of contexts before the bid request to make a media buying or monetization decision based on that risk assessment.

  • Probabilistic Identifier

    Probabilistic identifiers do not rely on deterministic identifiers that uniquely identify an individual. Rather, probabilistic identifiers are simply an approximation of a unique user versus a clear delineation of one. Meaning, there is a chance that two probabilistically identified users may collide and be confused for each other because their probabilistic identifier mistakenly conflates them as the same user. Naturally, the chance for collision is highly dependent on the strength of the probabilistic identification mechanism.

  • Product Attribution

    Product Attribution allows users to run their attribution models at the product-level versus the order or conversion-level. Generally, most attribution companies treat conversions as indivisible units when drawing their path-to-conversion. But, in truth, a conversion could actually represent an order that contains multiple products purchased.

    Product Attribution allows the marketer to recalculate pathing and crediting at the more granular product-level instead of simply limiting pathing and attribution at the conversion level. This allows the marketer to see the attributed quantity and revenue for any given product, and is tremendously useful in helping advertisers drive product-specific marketing and media strategies

  • Product Feed

    Also called a product catalog, this is the file that contains a list of all products sold by a given advertiser. Usually includes names, descriptions and prices of the products.

  • Proxy Piercing

    In cases where a user is is browsing via a proxy (like a sophisticated botnet tunneling traffic through multiple devices), proxy piercing techniques can analyze the ad request IP and the end user IP to tease out unacceptable mismatches, in part by recognizing correlations between IP mismatches and other types of fraud.

  • Publisher

    Also known as an partner. Owner of a website which hosts tracking links and promotes brands.

  • Q

  • Query

    Most people think of search when it comes to a query – the search query is the word or the string of words entered in the search box of a search engine to access some information on the web. The study of search query trends is key to search engine marketing (SEM) optimization.

  • R

  • Raw Clicks

    Total number of clicks that occur on the same affiliate link.

  • Reason Code

    Reason codes provide event-level classification of the traffic characteristics that tripped fraud risk thresholds.

  • Redirection

    Forwarding a URL to another URL.

  • Referring Domain

    The domain from which a user came when they landed on a new domain.

  • Retargeting

    Retargeting is a lower-funnel technique to target users who have visited the advertiser’s website. In the E-Commerce world, retargeting may get to the granularity of knowing when visitors visited one or more of their product pages, added items to their cart and/or started but did not finish their checkout. Understanding user behavior at this granular level allows retargeters to employ a series of optimization techniques, such as valuing and bidding more for users who are especially deep in the advertiser’s web conversion funnel, or personalizing the ad through dynamic creative.

  • Retargeting Fraud

    Bots acquire retargeting cookies and mimic human browsing behavior in order to collect on the premium CPMs typically associated with retargeting campaigns. Advertisers suffer for investing in audiences that provide no engagement value and relying on distorted campaign performance metrics.

  • Risk Scores and Ranges

    A 0-100 scale provides a simple fraud risk metric – the higher the score, the higher the likelihood of that traffic having fraudulent characteristics.

    This scale is broken down into risk ranges:

    < 3% (Premium): high quality traffic. Invalid traffic activity may be due to false positives.
    3-6% (Low): invalid traffic is not likely. Some invalid traffic may occur at the event level.
    6-10% (Moderate): some invalid traffic is likely, concentrated at the event level. Traffic mixing between valid and invalid sources is likely.
    10-20% (Elevated): invalid traffic is likely, some concentrated at the event level. Traffic mixing between valid and invalid traffic sources is highly likely.
    20-30% (High): Invalid traffic activity is likely to affect the entire source. Traffic mixing between valid and invalid traffic sources is highly likely.
    30-100% (Critical): It is not recommended to buy from sources with invalid traffic levels within this threshold.

  • ROI/ROAS

    Return on Investment (ROI) or Return on Ad Spend (ROAS) are often used interchangeably in the media and paid marketing world to represent the value generated by specific marketing initiatives. It can be analyzed at a channel or campaign perspective, although channel managers who are managing a specific channel can use ROI/ROAS to optimize at a more granular level for their channel, such as ad groups and keywords for Paid Search managers, or placements and ads for Display and Video managers.

  • Rules-based Model

    There are various rules-based attribution models such as last touch, first touch, first and last, position-based, time decay and linear. The difference between rules-based and algorithmic models is that rules-based applies the same rules to each and every conversion while algorithmic learns from your data to continually refine a custom data-driven model. Algorithmic takes into account correlations between your media and even external factors like economic conditions and seasonality.

  • S

  • SDK

    A Software Development Kit is a grouping of software that’s used to develop applications respective to a particular device or operating system.

  • Search Engine Marketing (SEM)

    Promoting of websites by increasing their visibility in search engine results.

  • Search Engine Optimization (SEO)

    Maximizing the visitor volume to a website by optimizing the site to appear high in the list of search results.

  • Single Opt-In

    The simplest conversion flow, where the site visitor only enters his or her information in the form without confirming it via email.

  • Single-touch Attribution Models

    Single Touch Attribution Models are the simplest kind of attribution model, because they allocate 100% of the credit for a particular conversion to a single touchpoint. The most common type of single-touch attribution model is called the Last Click model, which awards 100% of the credit for a conversion to the touchpoint that generated the last click before conversion happened (assuming that the click happened within a particular lookback window).

  • SIVT

    Sophisticated Invalid Traffic (SIVT) is inclusive of complex, advanced fraud types and cannot be easily identified through list or parameter-based filtration. Instead, it takes advanced analytics, multipoint corroboration, and human intervention to uncover and suppress.

  • Social Advertising

    Social ads often appear in walled gardens such as Facebook, Twitter, Instagram, Snap, YouTube and more. Most of these ecosystems don’t utilize the standard IAB-defined mechanisms that are common in display, video and mobile.

  • Sourced Traffic

    Traffic acquired from third parties to augment a publisher’s audience.

  • Split Testing

    Also called “A/B testing”. The practice of testing two different versions of content, copy and/or ads to understand which one works best for the target audience. See also ”Multivariate Testing”.

  • Stacked Ads

    Is placement fraud caused by a malicious publisher stacking multiple ads in nested iframes and monetizing the entire stack on a CPM basis, when only the top ad was viewable.

  • Statistical Significance

    In the simplest of terms, when a statistic is significant, it simply means that you are very sure that the statistic is reliable.There is a lot of math behind this calculation but what you need to understand is the “p-value” which represents the probability that random chance could explain the result. In general, a 5% or lower p-value is considered to be statistically significant.

  • Strategic Partnership

    Also called a brand-to-brand partnership, B2B partnership, or Business Development/Biz Dev partnership, this is an arrangement in which one advertiser or brand promotes the goods or services of another advertiser or brand.

  • Subway Graph

    A subway graph visually shows the marketing touch points along a conversion path according to the “days before conversion” that the marketing touchpoint occurred.

  • Success Event

    A success event is an event within a website or an app which an advertiser decides they want their website/app visitors to do. These can be revenue or lead-generating events such as successful checkouts, or completion of a lead-gen event, or noteworthy intermediary events, such as the creation of a new account, adding items to the shopping cart, or first starting with a lead gen form.

  • Super Affiliates

    Group of select affiliates who generate most of the affiliate programs’ profits.

  • T

  • TAG Accreditation

    The Trustworthy Accountability Group awards seals such as “Certified Against Piracy” and “Certified Against Fraud” to buyers, sellers, and intermediaries in the digital supply chain who meet rigorous traffic verification requirements.

  • Targeted Marketing

    Distinguishing between different market segments in a marketing campaign. Groups can be distinguished by location, age, interests, etc.

  • Time Decay Model

    Time decay models reward the media touchpoint closest to conversion most and the others receive less credit the earlier they are in the path. Time decay models reward path position regardless of the relative effectiveness of each of the channels in the customer journey. Just like most rules-based models, they ignore external factors.

    Note that events may happen beyond a particular lookback window — and these will not receive any credit. For example, if the marketer has a 30-day lookback window in the above example, and a Paid Social event actually happened 31 days before the conversion event — then that Paid Social event does not receive any of the credit because it occurred before the 30-day lookback window.

  • Tracking Link

    A unique linking code that tracks activity of a publisher and publisher’s visitors for a brand. This code is embedded into a text or picture link and helps attribute visitors to the partners who sent them to the advertiser.

  • Tracking Software

    Platforms like MediaRails that track and analyze partner marketing activity in a reliable way.

  • Traffic

    All users that visit a website.

  • Trafficking

    Trafficking refers to the operational process used to set up and launch an ad campaign. Trafficking processes exist on both the demand-side and the supply-side. On the demand-side, it usually involves ad operations personnel on the media agency side, executing campaign workflows on their 3rd party ad server or demand side platforms.

    On the supply-side, it usually involves ad operations personnel on the publisher side, executing complementary campaign workflows on their publisher-side ad server or supply-side platforms. Because so much of attribution relies on firing impression, click and conversion trackers through Javascript or Pixel trackers — these are usually set up and implemented as part of the trafficking process by ad operations people on the demand-side.

  • Tunneling

    Some of the most pernicious fraud techniques include tunneling through VPNs, such as botnets operating through proxies. A lot of “mobile web” fraud is really desktop GIVT coming from server farms tunneling through proxies to infected devices.

  • TV Attribution

    TV Attribution Models allow marketers to understand the impact of various dimensions of their TV advertising, such as the TV Ad Network (ABC, Fox, CBS, NBC, …), TV Program and TV Ad Airing Spot, on their website traffic, online sales and other digital activities. It has long been accepted by marketers that airing commercials on legacy TV can often lead to conversions online — but due to the non-addressable nature of TV Advertising, the impact is hard to accurately quantify.

    With TV Attribution Models, marketers can collect TV data in aggregate (GRP), and analyze their incremental impact on driving conversions in the online world.

  • Two-Tier

    An affiliate program that allows affiliates to earn commissions from their own sales and from the second-tier affiliates they recruited to participate in the program.

  • U

  • Unfriendly iFrame

    Does not allow third party participants like ad exchanges or verification vendors to access information about the publisher site in which the iFrame is embedded. This poses a significant challenge to viewability measurement.

  • Unique Clicks

    A type of reporting that allows you to see how many unique people click on your link or ad. This is different from Raw clicks as it doesn’t include duplicate visitors or clicks.

  • Unique Contribution/Revenue

    When assembling a path-to-conversion, it is quite possible to find a number of paths that consist of one marketing touchpoint followed by a conversion. It is easy to conclude that, if that marketing event had NOT happened, then the conversion event may not have happened at all. We therefore measure unique contribution or unique revenue based on the amount of conversions or revenue delivered by a particular touchpoint where it is present in a single-touchpoint conversion path.

    Unique contribution represents the number of conversions driven by a channel or media investment that you would not have received if it was not for that media investment’s sole contribution.

    Unique revenue represents sales revenue driven by a channel or media investment that you would not have received if it was not for that media investment’s sole contribution.

    With the complex channel overlap of today’s marketing environment, you want to measure each media’s unique contribution and unique revenue so you know where you’re getting the most bang for your buck.

    For example, if a marketer, by analyzing their conversion paths, find that 50 conversion paths looked like this: Paid Search Click –> Conversion, delivering about $1,000 in revenue. Then the Unique Contribution of Paid Search would be those 50 conversions, and the Unique Revenue would be $1,000.

  • User Level Fraud

    Ad fraud technique in which the user is fake, and the ad placement could be real or fake/manipulated.

  • V

  • vCPM

    Viewable Cost per Mille, or the cost per 1,000 delivered viewable ad impressions. Calculated only after the impressions have been verified as viewable.

  • Verification

    In the ad tech ecosystem, verification has come to include fraud detection, viewability measurement, brand safety assurance, and contextual categorization.

  • Video Advertising

    Refers to ads that leverage sight, sound, and motion to communicate the advertiser’s message. Includes “in-stream video” and “out-stream video”.

  • View-through Conversion

    View-through conversions represents instances where an audience was exposed to a particular ad (in whatever format — display, video or other), but did not click on the unit to go to the advertiser’s website. However, the user may have registered the exposure to the advertiser’s message in their head. They may go to the advertiser’s site at some point in the near future and take the desired conversion action. When the exposure event occurs within the lookback window duration of the conversion event, then we say that the user has had a “view-through conversion”.

  • Viewability

    Analyzes whether a delivered ad has truly been seen by the user. The IAB dictates that an ad is viewable if 50% of its pixels are visible on the user’s screen for at least 1 second if display and at least 2 seconds if video.

  • Viewability Fraud

    Bad actors can artificially inflate their viewable ad count by using techniques like placing ads in 1×1 containers and loading ads on top of each other.

  • Viewable Area

    Is the portion of an ad that could be seen by a human user, expressed as a percentage.

  • Viewport

    The area of a website that the user sees immediately upon opening a page, without scrolling up or down.

  • Viewtime

    The duration of time an ad meets viewable area criteria.

  • VPAID

    Video Player Ad-Serving Interface Definition is a script first introduced by the IAB to enable interactive elements in video ads. It’s important for its video viewability measurement benefits.

  • W

  • Walled Gardens

    Walled gardens represent areas in the digital media space where paid media can be purchased, but limited or no tracking data can be extracted at the event level. Most walled gardens will certainly ingest advertiser data in order to optimize campaign performance within the walls of their walled garden, but often do not provide granular (or any) data back to advertiser to allow them to optimize throughout their initiative (across both walled garden and other publishers). The social channels are probably the most famous of the Walled Gardens, including Google YouTube, Facebook, Instagram, Twitter and others.

    Walled gardens present a particularly large and existential challenge for marketers and other players within the digital media space since most media dollars are actually captured by the walled gardens

  • Whitelist / Blacklist

    a whitelist defines the domain/apps on which ads exclusively may run. Conversely, a blacklist defines the domains/apps on which ads should not be placed.

  • Y

  • Yield

    It’s all about the results. It can take a lot of time and effort to build a statistically-significant, accurate attribution model but don’t lose sight of the ROI. Keep your investment balanced with the potential savings or increase in revenue. You wouldn’t spend $100,000 to save $10,000 now would you? But if you have a large revenue stream, a 1% improvement in close rate can easily pay for your investment in attribution.

A

Ad Blocking

Prevents ads from showing up in brand unsafe environments where offensive content has been detected.

Ad Fraud

Actions taken to siphon money from the digital advertising ecosystem without delivering valid audience engagement in return.

Ad Injection

Placement fraud caused by a malicious publisher who owns a browser extension, uses it to inject ad impressions when a user visits certain premium sites, and enjoys premium CPMs for these hijacked impressions.

Ad network

a company that connects publishers (niche website, bloggers) to advertisers (brands and merchants).

Addressable Media

Addressable media refers to any media that can be tied to an individual user, either through a probabilistic or deterministic identifier. For instance, a display ad served in-app can be tied to the user’s device id, making it addressable. However, an ad broadcasted on standard, traditional TV does not pick up any identifier and therefore cannot be traced back to a specific user or household and is therefore not addressable.

It’s easy to assume that all digital channels are addressable, but this is actually not accurate. Most marketers cannot retrieve specific identifiers from the Walled Gardens, leading to large sections of the digital marketing universe that remain non-addressable.

Likewise, it’s easy to assume that all offline channels are non-addressable. But once more, this is actually not accurate. Direct mail is very addressable, and the cable companies have been rolling out addressable TV to better compete against IP-enabled digital TV (Connected TV and OTT)

Ads.cert

An Interactive Advertising Bureau protocol augmenting ads.txt that uses cryptographically signed bid requests (a technology similar to blockchain) to authenticate inventory and record its path.

Ads.txt

An Interactive Advertising Bureau text file that lists all approved traffic partners, intended to mitigate inventory sales by unauthorized traffic vendors.

Advanced Parameter Spoofing

Distributed fraud technique combining device ID spoofing and bundle ID spoofing to make it look like many mobile devices are sending requests across many different publishers.

Advertiser

a brand or a merchant who pays publishers to promote its products, services or brand as a whole.

Adware

also referred to as “spyware”. Usually unwanted programs users download without knowing they are part of the deal. They track the user’s behavior and place unwanted ads in their workspace.

Affiliate Network

a company that powers affiliate relationships, connecting advertisers and publishers. Typically, an affiliate network’s fee structure is based on a percentage of revenue generated (or of payouts to publishers), rather than a fixed cost.

Affiliate Program

an arrangement through which the merchant pays a fee to the affiliate publisher for generating leads, clicks or sales from affiliate links. These programs can also be known as partner, associate, or referral programs

Alexa Rank

a platform which ranks and estimates websites based on the user’s browsing habits. Its sample contains all internet users and websites.

Algorithmic Attribution

Algorithmic attribution, also known as machine learning, is the process of assigning a portion of credit for a conversion to each touchpoint based on effectiveness. The key differentiator of algorithmic attribution is its use of advanced statistical modeling and inferences to determine an optimal, custom model that continually refines itself based on your data – put more simply, human assisted machine learning.

API

Application Programming Interface that has a set of rules, routines and protocols that are used for building software with graphical user interface components. APIs allow businesses to access data in an automated fashion.

App Install

Many marketers do have very targeted goals of driving installs of apps they may have recently released, These are often run through Cost-per-install (CPI) programs where the marketer is able to pay their media partners for driving new users to install the app.

App install is often defined as the success metric for the CPI program, though many CPI programs wait until there is an actual post-app-install transaction before paying out. Because of their walled gardens, it’s actually quite difficult to measure whether the app install reported properly within certain advertisers. In cases where app installs need to be rewarded, the “install event” is often only recognized the first time the user starts up the app.

ATF / BTF

Above The Fold, meaning the ad is viewable upon opening the browser without the user having to scroll. Ads placed lower that do require the user to scroll are Below The Fold.

Attributed Conversions

Refers to the fractional conversions allocated by an attribution model to the channels, campaigns, keywords, placements or whatever attributable element. For instance, for a conversion path consisting of a paid search touchpoint followed by a display touchpoint leading to a single conversion, and assuming an even distribution of credit (i.e. a linear attribution model), the paid search channel gets an attributed conversion of 0.5 and the display channel gets an attributed conversion of 0.5

Attributed Revenue

Refers to the fractional revenue allocated by an attribution model to the channels, campaigns, keywords, placements or whatever attributable element. For instance, for a conversion path consisting of a paid search touchpoint followed by a display touchpoint leading to a single conversion worth $50 in revenue, and assuming an even distribution of credit (i.e. a linear attribution model), the paid search channel gets an attributed revenue of $25 and the display channel gets an attributed conversion of $25.

Note that advertisers can choose to provide pure revenue for their attribution analysis, but it’s usually better to use net revenue (which takes revenue and subtracts product costs) for your attribution calculation.

Attributed ROAS

ROAS means Return on Ad Spend, and is a derived metric that captures how effective your media investment was in delivering positive value versus how much you spent on that media. Since Return on Ad Spend (ROAS) is a derived metric, attributed credit is not directly distributed to these metrics. Rather, Attributed ROAS is calculated using Attributed Revenue.

The formula used is:
Attributed ROAS = Attributed Revenue / Media Cost

Attributed ROI

ROI stands for Return on Investment, and is a derived metric that captures how effective your media investment was.

It looks at:

(a) the positive value associated with the user performing the desired action (for instance, making a purchase, where the positive value is the money they spent)
(b) the cost of the media
(c) the cost of goods sold (the cost associated with the product.

As you can tell, Return on Investment (ROI) is related to Return on Ad Spend (ROAS), but also adds the cost of the product in the calculation of the derived metric. Because Attributed ROI is a derived metric, attributed credit is not directly distributed to it. Rather, Attributed ROI is calculated using Attributed Revenue.

The formula used is:
Attributed ROI = Attributed Revenue / (Media Cost + Cost of Goods Sold)

Attribution

The process of identifying a set of user actions (“events”) ​that contribute in some manner to a desired outcome, and then assigning a value to each of these events. Marketing attribution provides a level of understanding of what combination of events influence individuals to engage in a desired behavior, typically referred to as a conversion.

In general, marketers and agencies will use attribution to determine how to distribute credit for a conversion event based on the kinds of exposures and engagement a specific user has gone through in their customer journey on the way to conversion

Attribution Fraud

Occurs when a publisher games an advertiser’s attribution model (by way of click injection, cookie stuffing, etc.) to claim undue credit for driving a payable event.

Attribution Model

An attribution model is a methodology that is applied to all of a campaign’s or advertisers conversion paths in order to determine how to distribute the credit for a conversion. If you are a retailer, for instance, and you find that $200,000 of your revenue in the past month were to users who were exposed to your paid media, attribution models help you figure out how to allocate the credit for the $200,000 across the elements of your paid media. Attribution models help you understand the value of channels, campaigns, placements, keywords, etc… based on the revenue they may have helped generate

Various attribution models can be compared against each other to determine which is the best fit for your goals and gain a more holistic view of each media’s contribution. There is no one perfect model, an organization should continuously update their models and examine their ability to predict future performance.

Attribution, First Click

first-click attribution is when an advertiser credits a conversion to the first click in a conversion path.

Attribution, Last Click

last-click attribution is when an advertiser credits a conversion to the last click in a conversion path.

Attribution, Last-to-Cart

last-to-cart attribution is when an advertiser credits a conversion to the last click in a conversion path before the consumer places an item in their shopping cart.

Attribution, Multi-Touch

multi-touch attribution is when an advertiser attributes partial credit to each “touch” in a conversion path, rather than giving all the credit to the first, last, or last-to-cart click.

Auto-Download Offers

When a site visitor clicks a banner, the content is downloaded automatically without the user’s consent.

Automated Traffic Detection

Sophisticated algorithms that can accurately identify traffic from botnets, hijacked devices, malicious script injection and other automated means.

Data Mining, AI, and Machine Learning

Data mining techniques can be used to surface anomalous patterns that are found in automated botnet traffic, device farms, emulators and other perfidious fraud tactics. Naturally, any machine learning algorithm works best when monitored, trained, calibrated, and supervised by data scientists with deep fraud expertise.

B

B2B

Business-to-business exchange of products or services

B2C

Business-to-consumer exchange of products or services

Banner Ad

A static, animated, or rich media image that partners use to advertise a given product on their webpage.

Baseline Conversions

Baseline conversions, in attribution, refers to the estimated number of conversions that would have happened even without any of the marketing activity being measured by the attribution model. For example, baseline conversions may have been caused by external factors such as hard-to-measure word-of-mouth marketing, or by offline advertising — which cannot be measured by attribution models.

By establishing the baseline conversions before running attribution, the marketer is able to more precisely calculate the lift provided by their marketing initiatives, and only allocate the incremental conversions to the addressable initiatives being analyzed by the attribution system

Bathtub Model

A bathtub model is a rules-based model that allocates a set amount on the first and last touchpoints of a conversion path, and taking the remainder and allocating an equal amount to the middle touchpoints. For instance, let’s say your conversion path consists of Email >> Video >> Display >> Paid Search >> Retargeting. If we configure the bathtub model to allocate 70% to the end points (meaning that Email gets 35% and Retargeting gets 35%) then the remainder gets distributed evenly to the intervening touchpoints (meaning that Video gets 10%, Display gets 10% and Paid Search gets 10%)

Note that events may happen beyond a particular lookback window — and these will not receive any credit. For example, if the marketer has a 30-day lookback window in the above example, and a Paid Social event actually happened 31 days before the conversion event — then that Paid Social event does not receive any of the credit because it occurred before the 30-day lookback window.

Behavioral and Network Analysis

Techniques that compare traffic characteristics like IP address and ISP info to a variety of fraud databases that are built off of historical fraud activity to detect invalid traffic through list-based filtration mechanisms.

Bias

The models you use for attribution can introduce bias. For example, last click is biased in favor of channels that appear later in the buy cycle, such as coupon sites that often attract customers right before they buy, though they likely would have bought anyway.

Botnet

A network of corrupted devices manipulated within a command and control architecture to execute malicious instructions and accelerate the velocity of fraudulent activity.

Brand Safety

Verification that the content against which an ad is shown satisfies the advertiser’s threshold for brand integrity (no adults only content, violence, political extremism, etc.).

Brand Safety Categories

There are a standard 12 categories that the advertising industry and marketers consider brand unsafe: obscenity, military conflict, illegal drugs, adult content, firearms, crime, piracy, death/violence, hate speech, terrorism, spam/harmful sites, tobacco.

Browser and Device Analysis

Looks at the remnant clues such as attributes around the browser session for traces of malware, anomalous on-page behavior, faked domains and app ids, deceptive placement handling by malicious publishers and mobile botnets that convincingly, but imperfectly, mimic legitimate traffic.

Bundle ID

A bundle ID is a mobile app’s identifier, much like a domain identifies a mobile website.

Bundle ID Spoofing

Occurs when bad actors misrepresent their inventory’s bundle ID to buyers so that it appears to be associated with a premium app (and a higher CPM), when it’s coming from a dud, low quality traffic source instead.

Category-level Attribution

Attribution is typically run across all conversions that occur within a time period. However, E-Commerce marketers have an opportunity to get more granular, and analyze a subset of their conversions specific to a particular category.

They can run attribution at the category level in order to answer questions like:

* Which channels are best at driving revenue for high-margin categories, like lady’s handbags and shoes?
* Which ones are best at driving conversions for my top-selling men’s shoes category?
and so forth.

Whitelist / Blacklist

a whitelist defines the domain/apps on which ads exclusively may run. Conversely, a blacklist defines the domains/apps on which ads should not be placed.

C

Channel

Attribution is about examining all the various channels that are part of the customer journey – both online and offline. Online channels include search, social, display, affiliate, email and so much more. Offline channels like print, television, radio and outdoor are equally as important in an omnichannel customer journey. The nuance here is that the offline channels must be addressable, i.e. they can be traced back to an online visitor in order for the offline channel to appear in the journey. At the aggregate level, both offline addressable and non-addressable explain overall customer response to marketing stimuli.

Channel Predictions

Channel Predictions predict how a marketer’s KPIs are likely to trend over the next 30 days, allowing them to see how they are pacing to their goals based on a number of inputs.

Using Channel Level Predictions or Forecasting, a marketers can know in advance when to sit back and relax (because pacing indicates they are likely to crush their goals) and focus on other areas of growth, or, if Forecasting extrapolate that they will miss their KPI goals, they get early-enough warning to go on overdrive and take additional actions to spur growth.

Chargeback

A product that is returned or a sale that falls through. The commission made through sale is deducted from the partner’s payout.

Click

Clicks refer to the action of engaging with the advertiser’s media. On a mobile device, it’s more appropriate to refer to clicks as taps.

Clicks on many paid search or standard banner ads will typically take users to the advertiser’s website or app.
However, this may not always be the case — clicks or taps on certain types of display ads may trigger a video or other interactive element that keeps the user on the same page.

Click Fraud

Clicks feigned or spoofed to fool advertiser KPIs, defraud CPC campaigns, or steal attribution for a payable event.

Click Tracking

Click tracking allow tracking solutions such as Impact to track when the user clicks on something. In truth, clicks can either be tracked directly on the website (the user ends up clicking through into a landing page anyway) or can be trafficked in the advertiser’s ad management system as a 3rd party click through callout. In a web environment, the click tracker is often an executable tag, though pixels are also viable. In-app requires a dedicated API for click tracking since Javascript tags cannot be used within an In-app environment. All necessary contextual information about the referrer (the original publisher or media partner source of the click) is passed along with the click tracker

Click-Through Rate

The ratio of clicks to impressions, usually displayed as a percentage.

Closer

A partner who “closes the sale”, causing a consumer to convert. Examples include coupon, deal, loyalty, toolbar, and cart abandonment partners. See also: “Introducer” and “Contributor”.

Commission

Also known as a referral fee and the income the publisher receives for referring a lead to the advertiser’s website.

Consumer Journey

A consumer journey refers to the set of the advertiser’s marketing touchpoints that a particular user is exposed to or engages with over a period of time. It’s easy to confuse the consumer journey with the conversion paths — but they are not the same because many consumer journeys don’t end up with conversions.

Users who end up converting (i.e. in retail, a conversion is often a successful order. In auto, a conversion is often when a user chooses to ‘schedule a test drive’. Consumers who convert are typically exposed to a number of touchpoints beforehand. When customer journeys lead to a conversion, the customer journey is called a conversion path.

Not all conversions are driven by advertising. Some people just go directly to the advertiser’s website and make a purchase – even without receiving any exposure to any paid media. Such a conversion would essentially be organic and have a zero-length conversion path

Content Farm

A website that create huge amounts of low-value content to generate clicks and create ad revenue.

Content Marketing

Content marketing refers to a marketing technique where the marketer publishes their own short or long-form content (in any format — written, audio, video) and pushes it out to their audiences in the hope that the intellectual property provides value for the reader. Content marketing can take on a variety of angles, such as beginner’s guides, educational pieces, infographics, thought leadership, research papers, buyer’s guides and more.

Content marketing stands in contrast to advertising, which is mostly paid marketing used to build awareness or persuade viewers to take action — the concept of intellectual capital is less pronounced in the advertising world versus the advertising world. However — they are very complementary in nature, since advertising can be used to promote and increase awareness of new content marketing pieces provided by the marketer.

Content marketing is distributed using a variety of methods:

a) Published on-site. Content marketing is often posted on the marketer’s website, and the marketer uses a variety of technique (paid advertising, organic social posts, email, etc…) to reach audiences and make them aware of the new piece of content marketing, and drive them to the site.

b) Published on 3rd party sites. Content syndication can happen in a variety of ways. A marketer may work with a trade association to publish their content marketing on their site (and other promotional channels, for example — content marketing may be disbursed to the 3rd party’s newsletters, etc…). A publisher may incorporate the piece of content marketing into their site as a “Sponsored Article” — which is a form of native advertising

Content Publisher

A partner who promotes an advertiser’s goods and services through written content. This can range from an individual blogger to a traditional media company or magazine.

Contextual Classification

Categorization of the page based on some standard (such as the IAB Tech Lab Content Taxonomy) or custom taxonomy.

Contributor

A partner who pushes consumers toward conversion, driving value in the middle of the conversion path. Examples can include content blogs and comparison partners. See also: “Introducer” and “Closer”.

Conversion

Conversions refer to success events — they represent actions that marketers want to their audiences to do. There are online conversions — success events that happen on the digital channel, and offline conversions — success events that happen in the physical world. When a user successfully checks out of the advertiser’s e-commerce site, then that’s an example of an online conversion. Another user may go to the advertiser’s brick & mortar location and buy something — an excellent example of offline conversion.

Conversion De-duplication

A marketer will typically use multiple systems to manage different channels. For instance, they may use an SEM like Kenshoo or Marin to manage paid search, and they may use an Ad Server or DSP like Doubleclick, Sizmek or the Trade Desk to execute their display ads. Each may track conversions independently — and if channel managers are not coordinating, each channel manager is watching their own conversion tracking, and the total number of conversions end up far exceeding the true number of conversions because they are getting overcounted across systems.

In our example above, if a marketer using different systems for SEM and Display noticed 50 conversions the past day, and noticed that all 50 involved both one Paid Search and one Display event each — then if no one does conversion de-duplication, then the marketer may wrongly conclude that they received 100 conversions over the past day — 50 from paid search and 50 from display.

That’s why cross-channel leaders recognize the importance of conversion de-duplication. Conversion de-duplication consolidates and reconciles all conversion events, so that duplicated conversion events recognized by separate systems are unified. It is a necessary step for any reliable Customer Journey Analytics or Multi-touch Attribution analysis.

Conversion Fraud

Fraud techniques engineered to exploit performance marketers’ CPA spend by faking or spoofing conversion events.

Conversion Path

The list of “touch points” leading up to a conversion. This includes each time an advertiser “touches” the consumer through one of their own marketing channels (such as a display ad or an email) or through one of their partners.

Conversion Paths

A conversion path refers to the specific subset of consumer journeys that end with a user converting

Conversion Rate

A rate of the number of times a tracking link has lead to a sale vs. the number of times the link has been clicked on, shown in percentage. To calculate this rate, take the amount of sales a banner has generated and divide it by the number of clicks. Multiply by 100 and the answer you get is the conversion rate.

Conversion Tracking

Conversion tracking allow tracking solutions such as Impact to track when the user converts on something. In a web environment, the conversion tracker is often an executable Javascript tag, though pixels are also possible. In-app requires a dedicated API for conversion tracking since Javascript tags do not run within the In-app environment.

Cookie

Cookies are still the primary deterministic identifier in the desktop and mobile web world. Cookies can either be first-party cookies or third-party cookies.

Apple Safari has been the most restrictive browser and does not allow setting of 3rd party cookies by default on iPhones (though users have the option to alter this behavior from their Browser Settings), and have dramatically limited the lifespan of even first-party cookies with its ITP updates.

Cookie formats are typically non-standardized as most companies maintain their own cookie pools. They are also pseudonymous – that is, they can be tied to personally identifiable information (PII) but when viewed on their own, don’t tell the viewer anything beyond a string of letters and numbers.

Cookie (First Party)

First party cookies are cookies that are issued by the domain that they are currently browsing on

Cookie (Third Party)

Third party cookies are cookies issued by a domain that is different from the domain the user is currently browsing on

Cookie Stuffing

A type of attribution fraud in which a site visitor receives a third-party cookie unbeknownst to him or her.

Cookies

Information that your computer stores in your web browser when you visit a website or click on a link. It allows websites to keep track of your visits and activity, as well as attribute referrals to the relevant partners. Cookies are considered “first party” if the cookie’s domain matches the site the user is on, and “third party” if the domains do not match.

Cost Importers

Cost importers are Impact’s tools for pulling in media cost data from 3rd party systems within the advertiser’s tech stack. Cost importers are generally IT-less (they do not require a technical resource to implement the integration) and can be fully configured by non-technical resources from the Impact platform directly.

Coupon Publisher

A type of affiliate that generates sales for an advertiser by offering discount codes (also called voucher codes or coupon codes) to their users.

CPA

CPA, or Cost per Acquisition or Cost per Action, is a metric that is tracked in many direct response and performance campaigns, particularly in verticals that are tracking user conversions — whether that conversion represents a sale or a form submission, depending on what the advertiser decides. This is why it’s also often referred to as Cost per Conversion.

Some marketers will include “clicks” as a viable action — in those cases, the calculation is essentially equivalent to a CPC (Cost per Click).

A related concept is eCPA, or Effective Cost per Acquisition. This is often calculated by advertisers who pay on another cost basis such as CPM or CPC, but wish to convert it to a Cost per Acquisition in order to optimize their media buying to some Cost per Acquisition target.

It is calculated as follows:
( sum of the relevant media costs / total # of acquisitions )

So, if a display campaign spent $1,000, and garnered 20 conversions, then the the eCPA = $1000 / 20 = $50

CPC

CPC, or Cost per Click, is a metric that is tracked in many branding, direct response and performance campaigns across any vertical. A click often refers to clickthru on an ad that directs them to the advertiser’s website, though many rich media campaigns may count a click on the ad that triggers some engagement (for instance, the user clicks on the ad to start playing a video, or playing a mini-game on the ad unit); in the rich media situation, this can also be referred to as Cost per Engagement (CPE).

A related concept is eCPC, or Effective Cost per Click. This is often calculated by advertisers who pay on another cost basis such as CPM, but wish to convert it to a Cost per Click in order to optimize their media buying to some Cost per Click target.

It is calculated as follows:
( sum of the relevant media costs / total # of clicks )

So, if a display campaign spent $5,000, and garnered 250 clicks, then the the eCPC = $5000 / 250 = $20

CPCV

CPCV, or Cost per Completed View, is a metric that is tracked in many video-based campaign across any vertical. A completed view is often triggered once the viewer of the video reaches the end of the video, though due to the idiosyncracies of many video player platforms, it may be triggered when <100% of the video is viewed.

A related concept is eCPCV, or Effective Cost per Completed View. This is often calculated by advertisers who pay on another cost basis such as CPM, but wish to convert it to a Cost per Completed View in order to optimize their media buying to some Cost per Completed View target.

It is calculated as follows:
( sum of the relevant media costs / total # of completed views )

So, if a display campaign spent $10,000, and garnered 200 completed views, then the the eCPC = $10000 / 200 = $50

CPI

Cost per Install, or the price an advertiser pays for each install event in which a user downloads their app.

CPL

CPL, or Cost per Lead, is essentially a subset of CPA, or Cost per Acquisition, specifically used by verticals that require the audience to complete a form with their contact info. For instance, in the insurance vertical, an interested user may have to enter their personal info in order to request an insurance quote or have a broker contact them.

CPM

CPM, or Cost per Mille, or Cost per thousand impressions (mille is the latin word for thousand) is one of the most common ways to purchase advertising today. Though it is used across many branding and direct response campaigns, it is particularly suited for verticals and campaigns intended to raise awareness.

For instance, if the CPM is priced at $2, and you wish to deliver 1,000,000 impressions, then the cost of the campaign is

(Total # of impressions / 1000) * $2
(1,000,000 impressions / 1000) * $2 = $2,000

Many advertisers running direct response or performance campaigns who pay for media based on CPM will often calculate an eCPC or eCPA as a KPI in order to track their success and to optimize toward lowering that KPI.

CPS

Cost per Sale, or the price an advertiser pays for each referral that ends in a sale. Essentially a subset of CPA, specifically used by verticals that require the audience to complete a sale.

CPV

Cost per View, or the price an advertiser pays for every time their video ad is displayed.

CPvM

CPvM, or Cost per Viewable Impression, is a metric that is tracked in many campaign across any vertical. A viewable impression is generally measured based on IAB standards — that is, for a display ad, 50% of the ad appears on the screen for at least 1 second, and for a video ad, 50% of the ad appears on the screen for at least 2 seconds.

Since most display or video campaigns today are paid in CPM rather than CPvM, CPvM is usually calculated.

It is calculated as follows:
( sum of the relevant media costs / total # of viewable impressions )

So, if a display campaign spent $2,000, and garnered 200 viewable impressions, then the the CPvM = $2000 / 200 = $10″

Creative

A promo tool advertisers create to get visitors to click through and take action. Examples include banners, pop-ups, email copy, text links, badges, etc.

Creative Fraud

Creative fraud, or malvertising, is when bad actors inject malicious code in ads in order to cause some type of fraudulent activity, such as generating fake clicks or additional ad calls.

Cross-Device Journey

Cross-device Journey depicts the customers journey regardless of which of their owned device a marketer’s touchpoint reaches them on. This is in contrast with a journey that does not factor in cross-device. A user who was exposed to the marketer’s media touchpoints across their mobile device, tablet and desktop will appear as three separate users with three distinct single-device customer journeys instead of one unified user spanning their many devices.

This has always been important, but is growing more and more so. In the US, the average user owns over 3 devices — and that number continues to increase each year. In order for marketers to have any reliability in their Customer Journey Analytics or Multi-touch Attribution solution — it must understand the users’ cross-device journey

Custom Model

Custom Models are rules-based attribution models that are completely defined by the marketer’s business rules. They can start with some base rules-based model (i.e. start off with a a linear attribution model) and can be customized to meet just about any business rule the marketer has. For instance, they can implement a Custom Rule that says “Allocate 30% of the credit to the first touchpoint unless the first touchpoint is a website visit. Allocate 20% to the final touchpoint and distribute the remaining credit to the rest of the central touchpoints.”

Altitude (by Impact) attribution models are very malleable, and Altitude provides pretty flexible ways to shape and customize the attribution model to fit exactly whatever business rule customizations are needed

Customer Journey

The value of attribution is to examine the journey that led to the desired action – this includes cross channel (online, offline) and cross device (desktop, mobile, tablet). 79% of users own three or more devices. Recent studies show that users switch between devices up to 27 times per hour.

Customer Journey Analytics

Customer Journey Analytics refers to a category of marketing intelligence products that deal with analyzing metrics and structures associated with the customer journey.

Marketers can, for instance, ask questions such as:

* What is the average number of touchpoints along the customer journey for converting paths?
The marketer may choose to anti-target a user who dramatically exceeds that average by a wide margin.

* What is the most popular way that converting paths start?
The marketer may choose to dial-up some of their investments on these first touch channels or campaigns

* What is the average duration of a conversion path?
The marketer may choose to anti-target users who far exceed the typical duration that most users take to convert

Many of these Customer Journey Analyses can be performed directly from the available Impact reports, though a user who would really like to dig deep into them can analyze individual paths through PAQL, Impact’s proprietary querying language for customer journeys.

In the future, we anticipate marketers to leverage Customer Journey Analytics to start activating marketing investments to guide users down higher-conversion rate paths.

D

Browser and Device Analysis

Looks at the remnant clues such as attributes around the browser session for traces of malware, anomalous on-page behavior, faked domains and app ids, deceptive placement handling by malicious publishers and mobile botnets that convincingly, but imperfectly, mimic legitimate traffic.

Daily Budget

The budget limit for your campaign on a daily basis.

Dashboard

A dashboard is a set of visual widgets that are used by specific roles within a data-driven marketing department to run their business and make decisions. Visual widgets can include longitudinal charts, snapshots-in-time breakdown charts, tables, lists, trending or forecast graphs, real-time KPI scoreboards, goal meters and many other innovative mechanisms to visualize numerical data in order to simplify and bubble up insights.

Generally, different members of the marketing organization will want to have organize, assemble and tailor their own dashboards to support their unique role, root-cause analysis methodologies and visual preferences. For instance, the CMO Dashboard will in general be far broader and shallower than the Paid Search Manager or Display Dashboards, which would be channel-specific and far more granular

Dashboards visuals generally fall into a number of major purposes:

* Monitor Performance – High-level mission control views to monitor on general performance on a regular basis to ensure that day-to-day performance is going according to expectation, and there are no major anomalies in the data (e.g. If one of your channel systems goes down, for instance, marketing leadership may immediately notice a drop in delivered impressions)

* KPI and Goal Monitors – A data-driven organization always measures KPIs and tracks it to strategic marketing goals. It’s important that every member of the marketing team keeps close tabs of how they are tracking to their goals, and constantly making the required adjustments to make sure they hit them

* Compare Longitudinally – Time is one of the most important dimensions in marketing analytics, and most growth organizations will want to ensure that certain important metrics (like Attributed Revenue or Return on Ad Spend) are growing month-over-month or year-over-year (particularly for seasonal businesses)

* Root Cause Analysis – These are drill-down widgets that allow you to look at anomalies and dig deeper into what might be causing a particular trend. The ability to get granular is a crucial part in being able to answer “Why?” questions and derive smart insights that can be used to take action and optimize wisely

Data Center

A large network of computer servers typically used by bad actors to remotely execute various ad fraud techniques.

Data Integration

With so much data available these days, the challenge is to consolidate it all and extract clear, actionable insights. Finding a platform that can systematically integrate data from various sources will help to tame your big data madness.

Data Mining, AI, and Machine Learning

Data mining techniques can be used to surface anomalous patterns that are found in automated botnet traffic, device farms, emulators and other perfidious fraud tactics. Naturally, any machine learning algorithm works best when monitored, trained, calibrated, and supervised by data scientists with deep fraud expertise.

Data Quality

When it comes to data, many marketers intuitively believe in garbage in, garbage out. The data used in attribution modeling needs to be harmonized and cleaned to a common level of granularity so that it is useful. Utilizing data from various sources guarantees disparate data and finding a way to correlate it is critical.

Data Silos

Data silos generally refer to a particularly insidious issue in marketing intelligence that has arisen from the precambrian explosion of channel-specific systems over the past 20 years. As the number of ways for a marketer to reach their audiences through digital media have grown (and continues to grow), point solution systems have emerged to supply planning, workflow and optimization tools for those channels. These tools have generated an ever-growing mass of data, and marketing organizations have typically kept these point solution data as separate siloes to keep their channel teams’ management and optimization processes streamlined.

Unfortunately, data silos gave rise to a number of problems that have gotten in the way of providing reliable marketing intelligence (and many marketing intelligence systems have simply ignored many of these problems)

* No Omni-channel View – When data remains fragmented in siloes, then marketing leaders are not able to truly understand, at a holistic level, everything that is going on across their media. Many marketing organizations have taken to exporting reports from different systems, and manually patching together reams of unreconciled Excel spreadsheets together, an error-prone and time consuming task that often arrives too late after campaigns are already over, all in order to simply understand what is happening at a high-level

* Duplicated, Unreconciled Data – Most systems have mechanisms to optimize for their own channel. These often require firing a conversion tag when a user reaches a success event within the advertiser’s website or mobile app. Unfortunately, each channel system is firing and measuring its own conversion events in an unreconciled way, leading to each channel system claiming credit and resulting in the over-counting of conversions.

* Potential Bias – Several channel systems have stepped forward to offer themselves as a solution for consolidated channel tracking, but many of these systems are owned by enormous media owners. If the systems that are evaluating performance are also owned by the media owners who are being evaluated, then the potential for introducing bias is great

Deep Linking

A link that allows a website visitor to go to a product page directly. A basic tracking link simply goes to the advertiser’s homepage.

Deterministic Identifier

A deterministic identifier is an identifier that can be definitively tied to a specific user’s device.

The most common deterministic identifiers include:

* Cookies — which, despite many actions taken by Safari and Chrome, remain an indispensible identifier in the desktop and mobile web world

* IFAs — identifiers for advertisers, which are primarily used in the in-app world. Android and iOS platforms maintain their own proprietary scheme for device identification

* PIIs — short for Personally Identifiable Information, this refers to data that can be tied to an individual, such as login info, email, phone numbers, names, social handles and others

Device Farms

User fraud technique in which agencies and performance partners who are asked by advertisers to “drive performance” for their ad campaigns hire hundreds of low-cost workers in developing countries to browse fake or real websites and “click” on the advertiser’s ad or “install” and open the advertiser’s app.

Device Fingerprinting

Device fingerprinting often leverage either proprietary or open-source methods for collecting data from digital transactions in order to uniquely identify a user.

This can sometimes lead to a surprising level of accuracy, depending on the technique used. A common fingerprinting mechanism, for example, leverages the specific collection and order of fonts on a user’s device to uniquely identify them.

Many companies may use some of these methods combined with their own. Because these are simply an approximation of the unique user versus s clear delineation of one, fingerprinting is a probabilistic method – and there is a chance that two users may collide and be confused for each other because they have the same fingerprint.

Because each vendor has their own secret fingerprinting recipe, the lifespan and scope of a fingerprint varies from vendor to vendor.

Device Hijacking

Occurs when a user downloads a malicious app on their smartphone or tablet, often from a trusted source like the App or Play Store. The app hijacks the device to inflate traffic numbers and steal ad dollars by rapidly loading hidden ads and emulating human behavior. This happens in the background, even when the app is minimized or the device is sleeping.

Device ID

A device ID is the unique identifier for a particular mobile device.

Device ID Reset Marathons

Device ID reset marathons are able to achieve exploitation on a mass scale when device farms execute events (like clicks or installs) and are then reset, each device obtaining a new device ID, and the process runs from the beginning again.

Device ID Spoofing

Fraud operators have started manipulating device ID information (misreporting the device ID associated with their inventory) in order to simulate more normal-looking browsing patterns and fool increasingly sensitive detection methodologies.

Device Manipulation Recognition

Detection methodology that looks for anomalies within traffic to identify instances of device manipulation, where a fraudulent user or bot uses operating system and browser manipulation to spoof their real identity and simulate traffic.

Digital Media

Digital media often refers to all media techniques delivered over the internet or wireless environment, including email, SMS marketing, paid search, paid social, digital video, display, native, digital audio and more. This is in contrast to offline media, which refers to all media techniques related to traditional pre-internet channels

It is often mistakenly referred to all digital media as addressable media which is erroneous because many digital marketing activities, such as advertising on YouTube or Twitter, actually non-addressable outside of the walled gardens’ tools.

Disclosure

A notice on the partner’s website that notifies readers of the fact that the partner is getting paid for any purchases customers make through their links. It is important to have one to be compliant with FTC laws.

Display Advertising

Commonly understood to mean “banner ad”, but formats have evolved to include rich media ads. Display ads can be static or animated and can remain within their placement on the publisher’s page or expand out of it. Typically tag based.

Domain Cloaking

Occurs when a malicious publisher serves ads in a series of nested iFrames and attempts to cover their tracks by falsely representing one of the intermediate iFrames as originating from a premium publisher.

Domain Spoofing

Occurs when bad actors build malicious sites and sell their inventory to legitimate resellers (networks and exchanges) at a premium by misrepresenting their actual domains and masquerading as premium publishers.

Double Opt-In

A two-step subscription system, in which a website visitor voluntarily fills out a form to receive notifications, and then confirms his or her subscription via email.

E

Earned Media

The term Earned Media is often used in conjunction with the other two types of media: Paid Media and Owned Media. Earned Media, as opposed to Paid Media or Owned Media, represents word-of-mouth marketing (content that is generally not paid for) that helps build awareness for the brand, or drives visitors into the advertiser’s owned media.

Examples of earned media would include social mentions, likes, reviews, SEO, retweets, recommendations. Producing great content (eBooks, webinars, blog posts, etc…) is also an effective vehicle for driving earned media, because that content can be syndicated and generate inbound links, etc…

Engagement Metrics

Measure a user’s engagement with an ad beyond the minimum viewable impression standards. These metrics may include custom viewability measurement (such as the duration a video ad was played) and interactivity measurement (such as direct mouse interactions with a rich media display ad).

EPC

Earnings per click (EPC) is a measurement of how much commission partners tend to make on average for each click they generate for an advertiser’s program. This is a way for partners to estimate how much money they will make on a CPA basis, based on their expected click volume.

External Factors

A strong attribution model will take into account non-marketing elements such as seasonality, major holiday events, macroeconomic factors and competitive activities which can also greatly influence sales.

F

First Touch Model

A First Touch model is a rules-based model that allocates 100% of revenue to the very first touchpoint of a conversion path within a given lookback window.. For instance, let’s say your conversion path consists of Email >> Video >> Display >> Paid Search >> Retargeting. In a First Touch Model, 100% of the revenue is credited to the Email event since it is the first touchpoint in the conversion path.

Note that events may happen beyond a particular lookback window — and these will not receive any credit. For example, if the marketer has a 30-day lookback window in the above example, and a Paid Social event actually happened 31 days before the conversion event — then that Paid Social event does not receive any of the credit because it occurred before the 30-day lookback window.

Forecast

Attribution is no longer about just looking back to see what led to the desired action, it’s about being able to forecast how shifts in spending will ultimately affect your revenue. Forecasting, or marketing mix modeling, is a great tool to help marketers determine optimal media investments.

Fraud Intelligence Database

A fraud intelligence database must be dynamic to capture momentarily current lists of fraudulent IPs and forensic reputation data. This catches the bad actors in digital advertising that tend to use the same tactics to commit fraudulent activity repetitively.

Full-Funnel Detection

A fraud database that spans impression, click, install, and conversion events. Evaluating traffic for fraud across the entire funnel enables sharper detection at each point of the conversion path and allows us to offer unique capabilities- like install attribution fraud detection.

G

Gateway Tracking

A legacy tracking method developed by early affiliate networks. In this tracking method, users who click on an affiliate link are routed invisibly through a “gateway” hosted by the affiliate network, then redirected to the advertiser’s content. As the user passes through the gateway, the network places a tracking cookie in their browser.

Geo Target

Allows advertisers to target a specific country, state, province, city, zip code, postal code, area code, or DMA.

Geometric Analysis

A method of data collection and analysis to produce viewability measurement. Commonly utilizes a JS API to measure the coordinates of the ad unit on the page respective to the browser viewport. If the coordinates are outside the browser viewport, the ad is not viewable. When ads are served within unfriendly iFrames, using only the geometrical approach can produce only a small share of measurable impressions, so supplementary viewability measurement methodologies may be used.

Ghost Site

Sites designed to receive bot traffic, and not meant for humans.

GIVT

General Invalid Traffic (GIVT) is traffic that can be easily identified as invalid through routine, list and parameter-based filtration techniques.

Goal Tracking

Goal tracking refers to a practice used by data-driven marketing organizations to measure and keep track of the pacing of their Key Performance Indicators. Well-designed marketing goals and KPIs are designed such that they support even higher-level cross-departmental business goals and KPIs

Granular Data

User-level customer journey data provides a level of granularity that isn’t part of marketing mix models (MMM). The ability to construct the exact sequence of touchpoints leading to a conversion provides a level of insight that can identify correlations between channels and make it possible to optimize your integrated marketing strategy.

Gross Rating Point

GRP stands for Gross Ratings Points, and is used to measure a combination of reach and frequency of a particular ad campaign across the population corresponding to the marketer’s desired audience. It is often used as a measurement of legacy TV reach.

GRP is calculated using the following formula:
GRP = 100 * Reach (% of Target Audience) * Average Frequency

For example, if a marketer wishes to reach females 18-30, and executes a TV campaign that airs on 5 TV episodes for a TV show that reaches 30% of the target audience of females 18-30, then the GRP is 150 (i.e. 100 * 30% * 5).

H

Hidden Ads

Is placement fraud caused by a malicious publisher placing ads behind other elements on the page, stuffing ads into nonviewable 1×1 pixels, or loading ads off-screen.

Homogeneous Data

Disparate data is the root of all evil when it comes to attribution. Mapping data from various sources into a single source of the truth is necessary to establish a homogeneous data set for modeling. Don’t start modeling until your data is homogeneous.

I

IAB

The Interactive Advertising Bureau is a the standardizing body in the digital advertising ecosystem, developing industry guidelines, conducting research, and providing legal support.

Identifiers

Identifiers are attributes or mechanisms that are primarily used to establish the identity of a user. They are an important building block in much of performance marketing because they help tie different marketing touchpoints (such as ad exposures and paid search clicks) to actual success events (conversion events).

Identifiers come in two flavors: deterministic identifiers (which can be used to definitively identify a user or device) and probabilistic identifiers (which can be used to approximate the identity of a user or device). The most common types of identifiers are cookies, IFAs, PII and device fingerprints/snapshots

Identity Graph

We’ll use the term identity graph and device graph interchangeably. A Device Graph (as per Digiday) is a map that links an individual to all the devices they use. This could include a person’s computer at work, laptop at home, tablet and smartphone. As the internet of things starts increasing the number of connected, digital, IP-enabled devices owned by a user, the identity graph will grow to also include their OTT/Connected TV, smart speaker, and other smart devices. Instead of counting each device as the behavior of a different person, a device graph counts them as one person, so there’s no duplication. Advertisers can then see things like what time of day a person was exposed to an ad and on which device, which helps show what role any particular ad had in a purchase.

Identity graphs consist of identifiers matched up with data assets that help link together different identifiers into something that may represent an individual.

A simple identity graph may consist two identifiers, like cookies, matched together by some shared unique data asset:

a) A more common identity graph might consist of a set of identifiers that have been mapped to a user through an abstract concept such as a User Id. In this case, we’re not tying the identity of the user to some pseudonymized piece of PII information such as a hashed email, but to a unique user identifier:

b) As you can see above, the identity graph attempts to “identify” a user by linking together a series of deterministic identifiers such as cookies, IFAs along with pseudonymized deterministic through hashed emails and cookie synching along with probabilistic links through device fingerprinting.

Identity Resolution Services

Identity Resolution Services refer to solutions providers such as TapAd, Drawbridge, Screen6 and others, whose primary activity is building out, enriching and maintaining an identity/device graph of users. These solutions are often integrated with other advertising systems to offer perceivable customer value to the marketer, such as the ability to provide accurate reach metrics, maintain frequency caps, perform smarter targeting, offer more reliable metrics and more.

Impact solutions such as Radius and Altitude leverage a combination of 3rd party Identity Resolution Services and its own proprietary identity graph, to recognize users across their devices to stitch together omni- channel customer journeys, provide deeper customer journey analytics and calculate more reliable attribution for smarter media optimization.

IFA

IFA stands for Identifiers for Advertisers, and are particularly relevant for the in-app world. These identifiers are maintained by the platforms they are on (usually Apple iOS or Google Android) and are useful for identifying a unique device across all apps on that device. It is typically inaccessible on the mobile browser though.

Like cookies, they are deterministic and consist of a string of 32 alphanumeric characters and are pseudonymous. Unlike cookies, they are controlled completely by the platforms they are on, and typically (with the exception of fraudulent device reset farms) have a long lifespan.

iFrame

An HTML document embedded in a publisher’s site, used to enable third party ad exchanges and networks to insert ads without compromising that publisher’s security or quality.

Image Pixel

Establishes a browser to server connection allowing IP, UA, and other data points to be passed in the HTTP header.

Impact Consortium

The Impact Consortium is Impact’s own proprietary identity graph, used to power Impact’s expansive attribution capabilities.

Advertisers who onboard into the Impact Platform have the option to join into the Impact Consortium. If the advertiser passes in customer identity data (say, their email address when the user logs into the secure area of the advertiser’s site) into our Universal Tracking Tag, Impact captures a deterministic identifier that ties a specific user to a device. When the user logs in across multiple devices, and when the advertiser fires the UTT tag across those devices, then the Impact platform is able to tie the user and their multiple devices.

The Impact Consortium is fully compliant to privacy legislation such as GDPR.

Impression

The number of times a banner ad is viewed by website visitors. One impression means that the ad is displayed only once.

Impression Fraud

Fraud techniques engineered to exploit advertisers’ CPM spend by faking or spoofing impression events.

Impression Trackers

Impression Trackers allow platforms like Impact, with its powerful tracking capabilities, to track when the user receives an impression — usually of a display or video ad.

Impression trackers are often trafficked in the advertiser’s ad management system as a 3rd party impression callout. In a web environment, the impression tracker is often an executable Javascript tag, with an pixel trackers as backup for environments that do not allow Javascript to be executed.. In-app requires a dedicated API for Impression tracking since Javascript tags cannot be used within an In-app environment. All necessary contextual information about the publisher is passed along with the image tracker

In-House

Advertisers who manage their affiliate program by themselves using an affiliate software or tracking system instead of an affiliate network.

In-Stream Video

Video advertising that generally shows up before, in the middle of, or after other primary content video stream.

Inappropriate Domains

Domains that are unbefitting for ads and would compromise brand image. Examples include pages that feature terrorist sentiments or pornographic elements.

Incentivized Affiliates

Website traffic that is incentivized with actions that will ultimately result in the affiliate earning a commission. Incentives can be prizes, discounts, free subscriptions and others.

Incentivized Traffic

Traffic from users that were offered incentives (like an in-app reward) for clicking through to another other sites. This constitutes user level fraud when supply side players misreport it as organic traffic.

Incrementality

Incrementality refers to a measurement of advertising effectiveness that can be measured by attribution at multiple dimensions of granularity: channel, campaign, keyword, placement, etc… It indicates the amount of lift to a particular metric (i.e. incremental sales, incremental conversions, etc…) that is brought about by the marketing investment — comparing, for example those who were exposed to or clicked on a particular channel, campaign, keyword, placement, etc… versus one who had not had that touchpoint.

Incrementality can often be measured effectively by more advanced attribution algorithms, such as ones that leverage advanced statistical or machine learning techniques that calculates the likelihood of an increase on the target metric based on the presence or absence of a particular touchpoint in both customer journeys that end in conversion and ones that do not.

Influencer

A social media publisher with a large follower base who promotes brands through social media.

Influencer Fraud

Occurs when a paid influencer uses an illegitimately inflated follower count to ask higher rates of an advertiser for engaging their audience with brand sponsored content.

Influencer, Celebrity

Celebrities are often famous because of reasons outside of social media. They can be movie, tv, music or sports stars. Or they can be “cewebrities” – people who made their fame online, but now are recognized universally. (>1M followers).

Influencer, Macro

These larger influencers have often become popular due to social media. Some may be local celebrities whose renown have been amplified by social tools. Some may be digitally-famous category experts. (10K – 1M followers)

Influencer, Micro

These small influencers are numerous, and are often too fragmented to be managed in a high-touch way. Most of this segment is popular exclusively through social media. (<10K followers)

Influencer, Organic

This is a social influencer of any size who says good things about your brand, despite not being paid for those mentions.

Install Attribution Fraud

Certain partners cheat performance marketers’ CPI campaigns by faking or stealing credit for the actions that led to a user installation.

Install Fraud

Fraud techniques engineered to exploit performance marketers’ CPI spend by faking or spoofing payable app install events.

Install Tracking

Install Tracking is specific to the mobile/tablet world and allows an advertiser to track when their ad campaigns have resulted in a new install. Many marketers run their own Cost-per-install (CPI) programs to encourage users to download their app and use it.

Since there’s really no way way for you to fire 3rd party tracking code directly in the app store, meaning that there is no way to detect the install event directly from the app store event, most advertisers usually end up firing the Install Tracking Event when it detects that the app has only been opened for the very first time by the new mobile owner.

Intersection Object

A viewability measurement technique specific to Chrome; creates a shape containing only those areas where all components overlap (for example, an ad container). A point is part of an intersection if it is inside both objects (the ad and the ad container).

Intra-Device

Intra-device is particularly applicable to the mobile world, and refers to the ability to recognize a user within the same device, but across mobile web and in-app. Recall that 3rd party cookies are often deactivated in many devices in the mobile web, and unless the user does not clickthru on an ad or affiliate link, there are few alternatives to recognizing the user outside of probabilistic identifiers. When the user goes to a mobile app, on the other hand, there is often a way to recognize the user through deterministic identifiers (IFAs).

Identity Resolution Services that can bridge the gap and recognize users as they move from mobile web to in-app can map out and include the intra-device journey, which can be woven into an overall understanding of the user’s cross-device journey

Introducer

A partner who “introduces” a product or service to consumers, driving value early in the conversion path. Examples can include social influencers, content partners, and traditional media publishers like news sites and magazines. See also: “Contributor” and “Closer”.

Invalid Traffic

Traffic that does not legitimately fulfill the agreed upon user and placement specifications according to which the ad or audience engagement was purchased.

J

Javascript Tag

Gathers information directly from the page, enabling both server-side and session-side analysis. A JS tag integration is necessary for viewability and other verification measurements.

Javascript Tracking

Javascript Tracking is used to signal events to a Tracking Service in the web environments where Javascript is enabled (which will happen in most cases — most users browsing the web on desktop or mobile will usually have Javascript enabled). In web environments where Javascript is disabled, tracking can usually still be accomplished by image trackers. In the in-app world, tracking is usually achieved through API tracking integrations.

Javascript tracking can be used to track any important web events: impression events (when ads are shown to a user), click events (when ads are clicked on, or when the user lands in one of the advertiser’s properties through an outbound link from an ad or a link from another site, a clickthru from an influencer mention or affiliate link, etc..) and conversion events (when the user makes a purchase, or completes a lead gen form, etc…). It can also measure other related metrics typically associated with web analytics, such as session-level duration, # of pageviews, etc…

K

Keyword List

A list of words that a brand does not want adjacent to their ads.

KPI

A KPI, or Key Performance Indicator, is a measurement that will directly affect your marketing objectives. They can be identified by examining your strategic business goals, and deciding how to measure your progress towards those goals. Every business has unique KPIs so be sure you are measuring the most meaningful metrics to make more educated marketing decisions.

KPIs sometimes correspond to individual metrics, but more often, they are calculated from a series of metrics you are tracking. One common example of a KPI for advertising is ROAS (return on ad spend). ROAS is a measurement that evaluates gross revenue generated for every dollar spent. The math is simple if you have the tracking data you need. ROAS = revenue from ad campaign, minus the cost of the ad campaign, divided by the cost of the ad campaign.

L

Last Click Model

Last Click attribution assigns 100% credit to the final touchpoint (i.e. clicks) that immediately precedes a sale or conversion. While last click is important in identifying the closer, marketers should be sure to also examine the introducer (first click) and influencers (middle touches) as well.

Legitimate Bots

There’s a significant number of “good bots” that crawl the web and participate in healthy internet function.

Lifetime Value

The Lifetime Value (or LTV for short) captures the total value generated by a particular customer for a given advertiser, usually because of repeat purchases or conversions made by a given customer. Consumers with high LTV are a brand’s most valuable consumers, and many marketers rightfully attempt to locate audiences that increase their average LTV.

Linear Model

A linear model is a rules-based model and one of the simplest ones for those who are starting out when moving from single-touch attribution models to multi-touch attribution models. A linear model allocates an equal amount of credit to all involved touchpoints of a conversion path. For instance, let’s say your conversion path consists of Email >> Video >> Display >> Paid Search >> Retargeting. The linear model allocates an equal amount to each touchpoint, so Email gets 20%, Video gets 20%, Display gets 20%, Paid Search gets 20% and Retargeting gets 20%.

Optimizing marketing channels based on an even model means that the advertiser is rewarding frequency alone but not any external factors such as seasonal or macro-economic factors. An issue with this model is that diminishing returns and relative channel effectiveness are not accounted for as all channels and path positions are credited equally so more spend leads to linearly more conversion.

Note that events may happen beyond a particular lookback window — and these will not receive any credit. For example, if the marketer has a 30-day lookback window in the above example, and a Paid Social event actually happened 31 days before the conversion event — then that Paid Social event does not receive any of the credit because it occurred before the 30-day lookback window.

Location Spoofing

User level fraud technique in which malicious apps report fake location data (latitude, longitude) to media buyers in order to collect high payouts based on a (falsified) premium location.

Lookback Window

A lookback window represents the amount of time (usually specified as a number of days) prior to a conversion that a marketer decides would be a reasonable period of time for a marketing touchpoint to have credibly influenced a customer’s decision to convert. The lookback window is applicable for both single-touch and multi-touch models — both rules-based and machine-learning attribution models.

If a marketing event took place prior to the lookback window, then it is not considered when the attribution model is applied. For example, if the marketer decides to use a 30-day lookback window (meaning, consider only marketing events 30 days prior to a conversion, but no more), then if a paid social event happened 31 days before a conversion, then it would receive no credit whatsoever for that conversion, regardless of attribution model.

For most products, a 30-day lookback window is reasonable and standard. Certain types of products, such as autos and durable goods, may opt for a 90-day lookback window as more appropriate to reflect the longer purchase and decision-making cycle for those types of products

Loyalty Affiliates

Similar to incentivized affiliates, in this case users make a longer term commitment to the advertiser and are required to purchase products and participating in activities. Many loyalty affiliates offer cashback to the user in exchange for purchasing from advertisers through their loyalty portal.

M

Data Mining, AI, and Machine Learning

Data mining techniques can be used to surface anomalous patterns that are found in automated botnet traffic, device farms, emulators and other perfidious fraud tactics. Naturally, any machine learning algorithm works best when monitored, trained, calibrated, and supervised by data scientists with deep fraud expertise.

Machine Learning Attribution

A machine learning algorithm leverages advanced statistical techniques such as linear and nonlinear regression, cooperative game theory and other data mining methods, to allocate credit in the fairest possible way possible, based on a touchpoint’s propensity to increase an audience’s likelihood to convert. It looks at all the touchpoints — both the presence and absence of touchpoints — and their role in driving incremental value — looking at both the baseline, converting paths and non-converting paths.

It is often perceived to be the most bias-free of distributing credit, but receives pushback from marketing organizations due to the perceived black box nature of its algorithm, particularly for those unfamiliar with its specific methodology or data science techniques in general. Most attribution vendors will have their own proprietary implementations of data science methodologies and will mix in some of their “secret sauce” in order to provide what they believe, would yield the most optimal set of incrementality calculations for their customers.

Malicious App

A bad behaving publisher that siphons money from the adtech ecosystem by perpetrating various fraudulent actions such as aggressively calling non-viewable ads and running ads in the background of device when it is not even in use.

Malicious Bot

A bot designed to perpetrate ad fraud.

Malicious SDK

A software development kit into which a malware author has written malicious code, which a developer then embeds into its app. Once embedded, the malicious SDK can commit various ad fraud techniques from within the app itself.

Malware

Software that is intended to corrupt devices and device systems. Malware can be used to perpetrate ad fraud by hijacking devices, creatives, browsers, apps, and SDKs.

Marketing Event

A marketing event represents a trackable event such as an exposure to a display ad, watching a video ad, clicking on a paid search or paid social ad, tapping on an affiliate or influencer link, clicking through from an email or newsletter into the website, etc… These marketing events or touchpoints become the basic building blocks of a customer journey, and can be stitched together to illustrate all of the ways the brand has engaged with their audiences in hopefully persuading them to eventually convert.

Marketing Intelligence

Marketing intelligence refers to the systems, skills and processes that allow marketing organizations to make smart, data-informed decisions, usually through well-designed reports, KPIs, dashboards. For our purpose, we hone in on a particularly important marketing question: how to allocate their marketing spend most effectively based on the ROI and incremental value provided by their different marketing investments.

In order to make informed, holistic decisions specifically around allocating spend, marketers need to look at all aspects of the marketing problem. Marketers thus have to capture information across multiple marketing domains, including customers (which includes current customers and prospective customers), channels, media, customer behavior, sales and more. Marketing intelligence consolidates all this information into a centralized location so that the marketer has an overarching view that they can use to make smart and informed decisions regarding their marketing initiatives and spend.

Note: The use of the term “Marketing intelligence” can be confusing because it is used quite broadly. For instance, you can read various trade journals and magazines to receive “marketing intelligence” around the latest developments in the industry. This is not what we mean by “Marketing Intelligence” though.

Salesforce.com, a salesforce automation tool, may provide some marketing intelligence around the prospect funnel. Marketo, a marketing automation tool, may provide some marketing intelligence around customer engagement on the marketer’s email or landing pages. Many of these martech tools might even have sophisticated KPI trackers, visualization or querying platforms to provide intelligence to specific questions in marketing.

But for our purposes, these are not true “Marketing Intelligence” systems because they focus on very specific problem siloes rather than providing systems that allow marketers to receive marketing intelligence across the larger marketing universe – across channels, campaigns, devices, audience types and vendors – as a whole – which is necessary for answering the larger marketing question focused on smarter allocation of media spend.

Marketing System of Record

A marketing system of record or marketing source of truth (we use the two terms interchangeably) allows users to consolidate all their data into a single platform, and leverage it for to achieve marketing intelligence by applying various data applications such as KPI/goal tracking, scorecarding, dashboarding, reporting and attribution on top of the consolidated data.

Why do marketing organizations need a system of record?

Because marketing organizations are experiencing an explosion of marketing technologies that have come about in the past few years to deal with the growing complexity and proliferation of channels they have had to oversee. With over 5,000 marketing technologies available in the market, marketing organizations have a harder and harder time gaining visibility into their investments, what media efforts are truly making an impact on their customers, and which marketing initiatives are delivering positive net value.

A Marketing System of Record, does the following:

Collect. Automates the ingestion and consolidation of the marketing campaign data from different systems and different sources stretched out across different channels Reconcile/Normalize. Data consolidated into a single system need to be cleaned up, unified and normalized. Customers who may be recognized by an email address in one system, a cookie in another, and a device id in a third system needed to be reconciled into a single identity Apply. Knowledge-based applications could then be built over this robust source-of-truth for marketing data. This runs a gamut, from analytical applications such as reports, KPI measurement and visualization tools to advanced data applications such as customer journey pathing and attribution analysis

Measurability rate

The rate at which impressions can be measured for viewability. Measurability rates vary by viewability measurement techniques, technologies, and vendors.

Measurable impressions

Indicates the number of impressions for which viewability measurement was possible. Factors that impede viewability measurement include unfriendly iFrames, which prevent viewability measurement vendors from accessing information about the iFrame’s parent site.

Media Mix Modeling

A media mix model is an econometric top-down model that bridges the online world with the offline one. Media Mix Models are great for assessing whether non-addressable media like TV, radio, print, out-of-home and others are pulled into the media mix model, along with external factors such as macroeconomics, weather and seasonality – all these elements can also be factored into the Media Mix Modeling’s longitudinal statistical analytics.

Media Mix Models, marketers receive guidelines, informed by advanced econometric data, that tell them which factors are most impactful in driving a lift in revenues or conversions, thus giving marketers directional recommendations on how to allocate their media budgets across offline AND online advertising to maximize impact.

Mobile Advertising

In the mobile space, ads can appear on either mobile web or in-app. Mobile is often used to refer to both smartphone and tablet experiences.

Model Overfitting

Overfitting is a modeling error which occurs when a function is too closely fit to a set of data points, which is a no-no in data science and limits the practical usability of a model. One can, in theory, create a model that explains all the data points of a particular test data set extremely well to the point that too many parameters are used to explain away most residual variation (i.e. all the noise). The consequences of using an overfitted model is that the overfitted model becomes ill- suited to explain the behavior of another data set representing the general population, because it has been over tailored to the test data set.

Model Validation

The statistical model used to generate attribution findings should be validated with in-sample as well as holdout sample, or “control” (a sample of data not used in fitting a model) – the holdout sample is used to assess the performance of the models.

MRAID

Mobile Rich Media Ad Interface Definitions is the IAB’s standardization of one common API for in-app rich media ads, supported by multiple SDKs. MRAID is essentially the translator that reconciles the app’s and the ad’s languages. It has been commonly used beyond its intended purpose to measure in-app ad viewability.

MRC Accreditation

The Media Ratings Council standardizes excellent media measurement across vendors and performs annual external audits of rating service operations to determine whether a rating service meets their rigorous standards.

Multi-funnel Conversion

Most conversion funnels are simple – eCommerce funnels often involve only one: Land on the site > shop for a product > add it to cart > checkout > order confirmed!

However, some businesses rely on far more complicated conversion paths, and may leverage multiple conversion funnels, thus we use the term Multi-funnel Conversions to describe this. Conversion funnels often lead to intermediate “success events”, and it’s not uncommon for marketers to optimize towards these immediate “success events” – especially when the conversion process is complex, lengthy and true value only gets realized after the user makes their way through subsequent conversion funnels. For example, marketers may optimize towards driving users to subscribe to a service/create an account, but not necessarily use the service or perform some revenue-generating task. This is when it’s important for platforms to support the concept of “multi-step conversion funnels”

Analyzing the behavior across multi-funnel conversions allow marketers to define multiple “success events” and effectively stitch together conversion funnels. By doing so, marketers maintain a view of their short-term conversion performance (which media is driving the most account signups) but are also able to determine which media investments introduce customers who provide true value in the final conversion of a multi-step conversion funnel process (which media is driving the account signups that eventually perform some revenue generating activity later on).

Multi-touch Attribution Models

Multi-Touch Attribution Models (or MTAs for short) are more complicated than Single-touch Attribution Models. MTAs seeks to distribute credit across more than one touchpoint in a conversion path. One of the biggest deficiencies of single-touch attribution models is that it does not recognize a fundamental fact around marketing and advertising: that is, that that marketing and advertising is usually a “team sport” and that multiple touchpoints cooperate together to convince a prospect to eventually convert.

It’s usually not a one-person effort. Certain type of video advertising may be good in building out awareness. Rich media advertising or email campaigns may be good at building out interest and purchase intent. Paid search may be the final step after the user decides that they already want to make a purchase. All these channels come together to successfully drive a conversion.

Multivariate Testing

A method for optimizing content in which multiple factors are modified, in an attempt to find the optimal combination. See also: “Split Testing”.

N

Behavioral and Network Analysis

Techniques that compare traffic characteristics like IP address and ISP info to a variety of fraud databases that are built off of historical fraud activity to detect invalid traffic through list-based filtration mechanisms.

Native Advertising

Has a wide definition, but includes ads that seamlessly blend into the look-and-feel, styling parameters, and editorial content of a publisher site in order to minimize obtrusiveness.

NHT

Non-human traffic is automated invalid traffic. NHT compromises any campaign optimized on human engagement and distorts performance metrics.

Niche Marketing

Targeting advertisements to a specific market segment.

Non-Addressable Media

Non-addressable media refers to any media that cannot be tied to a unique user because no unique identifier can be extracted when the ad is delivered. For instance, when an ad is delivered through traditional TV, Radio, or when an ad is printed on a newspaper or on a billboard, that ad is generally classified as non-addressable. This is in contrast to addressable media, which CAN be tied to an individual user, either through a probabilistic or deterministic identifier. For instance, a display ad served in-app can be tied to the user’s device id, making it addressable.

It’s easy to assume that all offline channels are non-addressable. But once more, this is actually not accurate. Direct mail is very addressable, and the cable companies have been rolling out addressable TV to better compete against IP-enabled digital TV (Connected TV and OTT)

Likewise, It’s easy to assume that all digital channels are addressable, but this is actually not accurate. Most marketers cannot retrieve specific identifiers from the Walled Gardens, leading to large sections of the digital marketing universe that remain non-addressable.

Non-Converting Paths

Non-converting paths represent customer journeys that do not resolve into a conversion. This may be because the user has not converted yet, or may never actually convert at all. It is important for marketing intelligence solutions to understand both converting paths and non- converting paths in order to truly understand, from an attribution perspective, how influential different touch points are in truly driving lift and increasing users’ propensity to convert.

Normalized Data

Normalizing data for the purposes of marketing intelligence is the process of organizing data from disparate data sources — often representing different channels and data models — into a centralized repository with data structures that can support all the necessary data regardless of source. Normalization also makes the assumption that the data is de-duplicated and redundancy is reduced, and all important dependencies between the data set are captured in the most efficient way possible

O

Offer

Any type of content that’s created by advertisers (merchants) and promoted by partners, which are found in affiliate networks.

Offline Conversion

Offline conversions refer to success events that happen outside of addressable digital channels, such as sales in brick & mortar locations, or closing a sales through the advertiser’s call center, or closing a lead through a third party agent or franchisee. There is usually enough PII information collected from the offline conversion (information such as names, credit card numbers, etc…) that allow marketers to identify the individual performing the offline conversion.

Through integrations with marketers CRM systems, it should be possible to tie a user’s digital activities (including their marketing journey and online conversions) with offline conversion events.

Why would a marketer want to do that?

Because conversions, whether offline or online, do not happen in silos — and being exposed to marketing messages online has been shown to drive sales in the brick & mortar world. Because of the online/offline divide, too many marketers have taken the easier route of associating offline conversions with offline marketing, and online conversions with online marketing — but customers don’t think and behave in such a simplistic manner. By looking at customer journeys that drive both online and offline conversions, marketers are able to obtain a far more accurate picture about the incremental effects of their digital marketing on ALL types of conversion events

Offline Media

Offline media is often used to refer to legacy media techniques that predated the rise of the internet, such as TV, Radio, Print, Direct Mail, Call Centers, Cinema Advertising, Billboards and more. This is in contrast to digital media, which refers to all media techniques related to the internet

It is often mistakenly referred to as non-addressable media which is erroneous (many direct mail and call center techniques are highly addressable marketing activities).

OMID

The Open Measurement Interface Definition API allows third-party verification vendors to collect viewability measurement signals specific to the in-app environment, supplanting the need for apps to implement each third party vendor’s SDK.

Omni-channel

Omnichannel is defined as a multi-channel sales approach that focuses on an integrated shopping experience across all channels. Customers may encounter many touchpoints and move between online and offline channels, such as ordering online for in-store pickup. Each channel’s role is considered in relation to others and the customer experience is designed to be seamless and consistent.

OPM

Outsourced Program Management (OPM) is a type of agency that will manage an advertiser’s partner program on their behalf.

OTS

Opportunity To Be Seen benchmarks whether an ad was served under conditions that meant it had the potential to be seen by a user, agnostic to whether the user actually viewed it.

Out-Stream Video

Video advertising that acts as a fusion of rich media and in-stream formats, served against non-video content.

Outbound Link

A link to a website other than your own.

Owned Media

The term Owned Media is often used in conjunction with the other two types of media: Paid Media and Earned Media.

Owned Media refers to all media efforts that are in full control of the advertiser, and generally does not incur any variable payout to an external publisher (i.e. An ad creative may be fully designed and built by the advertiser, but in order to disseminate it, you need to pay publishers to place it on their site). Examples of Owned Media include the advertiser’s website, any media properties or microsites they may own, any mobile apps they build, any blogs they maintain, posts and tweets they may do on any social channels they maintain, customer base email marketing they may do, etc… Furthermore, when marketers invest in enriching one’s owned media, it also pays dividends on the Earned Media front (and, to an extent, on the Paid Media front — for example — better quality landing pages on the advertiser’s site can help improve quality scores on their Paid Search efforts).

P

Packet Sniffing

In-app fraud detection technique that includes listening to ad requests from an app, loading any ads returned, and recording on and off-screen activity to compare what is showing on screen to the actual ads loaded by the app. The sniffer does not use a proxy so the app will not know that its network activity is being monitored.

Paid Marketing

Paid Marketing refers to all initiatives undertaken by a marketing organization that requires some form of payment for delivery of exposure, engagement or conversion from the advertiser’s prospective audience. Paid Media, which is often used to describe advertising-like activities, is a subset of Paid Marketing. Apart from advertising, other initiatives that go under paid marketing could include affiliates, influencers, business-to-business strategic partnerships, local and client brand ambassadors and many more.

Paid Media

The term Paid Media is often used in conjunction with the other two types of media: Owned Media and Earned Media.

Paid Media is often referred to as advertising, and often refers to media exposure that is paid for at either a CPM or fixed-fee typed basis (though much advertising DOES get paid for through alternative payments models like Cost per Click (CPC), Cost per Lead (CPL), Cost per Install (CPI) or Cost per Acquisition (CPA).

Paid Media typically consist of these formats/channels: Standard Banners, Rich Media, In-Stream Video, Digital Audio, Native, Paid Search, Paid Social, Digital Out of Home, and of course, traditional offline formats/channels such as TV, Radio, Print (Magazines or Newspapers), Outdoor, Cinema, etc…

Paid Search

An advertising model used on many search engines and content sites. In this model, advertisers bid on keywords and phrases that may be relevant to their target, then pay whenever a user clicks on their ad.

Partner

Any individual or business that works with another business for the purposes of promoting that other business’s products or services.

Partnership Development

The practice of discovering and recruiting individuals or businesses who indirectly sell to your target consumer; it also involves marketing to partners in order to incentivize them to take actions that bring in new customers, increase the frequency of repeat customers, and effectively grow your revenue stream outside of traditional sales and marketing channels.

Partnership Lifecycle Management

The complete set of activities used to forge, deepen and optimize an enterprise’s relationship with their partners. The purpose of Partnership Relationship Management is to manage the Partnership Lifecycle.

The five main stages of Partnerships are:

1) Identifying and discovering new partners
2) Engaging and recruiting them,
3) Onboarding them,
4) Activating them to start driving revenue and
5) Growing and cultivating partner relationships – thereby optimizing your partnership program.

Partnership Management

An approach in which a single business unit or department manages all of a businesses partnerships (such as affiliate, social influencer, and strategic partnerships) on a single platform.

Pathing

Pathing refers to the process of stitching together customer journeys and analyzing their structure, metrics and characteristics for additional insight. Stitching customer journeys together can often be a tedious, difficult and error-prone process, and one that cannot be done manually without technological solutions to support it.

Here are a sampling of difficulties that come from doing this:

1) Collection and Assembly of Touchpoints. Most marketers on average leverage 12+ different systems to manage and launch their campaigns. Cost and transactional data need to be either ingested into a central system, or the data can be captured through Javascript, Image or API Trackers deployed on every system that needs it.

2) Reconciliation of Touchpoints across Devices. Most audiences today own 3-4 internet-enabled devices, and that number continues to do up. Stitching together customer journeys require a deep understanding of assembling a cohesive multi-device identity graph to ensure you have a reconciled customer path across all their devices.

Pathing and Attribution Querying Language (PAQL)

The Pathing and Attribution Query Language, or PAQL for short, is a proprietary patent-pending language for marketers to collect customer journeys, across multiple devices and multiple channels, in order to generate custom pathing and attribution marketing insights.

PAQL can also be used to tailor the behavior of rules-based attribution models in order to fulfill just about any custom business rules required by an organization. PAQL is a highly flexible way of creating bespoke attribution models necessary to meet the unique attribution modeling needs of any marketing organization.

Pay-per-post

A payment model often seen among social influencers, in which the advertiser pays the influencer a flat rate for each post or mention, regardless of performance.

Payment Threshold

The amount of commissions partners are required to earn before being able to withdraw them to their bank account.

Payout

Revenue per one sale or conversion.

People-based View

People-based view refers to looking at marketing data, not as a series of unrelated marketing touchpoints and events, but as a stream of inter-related events tied to a particular person. This means, the marketing intelligence solution needs to normalize and stitch all marketing events and related data points into a unified customer journey, rather than just flat and unreconciled exposure, engagement and financial data. It needs to be able to recognize that disparate events that appear to be happening in different devices owned by the same user (on the user’s desktop, tablet and mobile), even events that appear to be happening in different parts of the same device (mobile web versus in-app) and recognize that these are all the same person.

When marketing intelligence solutions provide a people-based view, it represents a far more accurate picture about how their marketing initiatives are truly driving prospects into customers, and leads to better optimization decisions versus non people-based views.

People-based views require that the customer journey:

1) Represents de-duplicated events. Without a people-based view, different channel systems may lay claim to their own conversion events, leading to significantly over-estimating how many conversions your marketing is actually doing

2) Represents a cross-device view. Media has long worked in conjunction with each other across a users’ different screens. An old adage says that users don’t think in screens or devices, but marketers, due to the difficulty of managing the proprietary complexities of each device, sometimes have to look at their data device-by-device, instead of recognizing the user behind multiple devices.

3) Represents an intra-device view. Just because it’s not easy to stitch together the probabilistic world of cookies for mobile web with the deterministic world of IFAs in mobile app, doesn’t mean it shouldn’t be done. Though mobile web only represents 15% of the mobile minute, it is still a significant presence in the mobile channel, the fastest growing channel. Being able to recognize the same user across mobile web and in-app within the same device is paramount for a people- based view

Performance Marketing

Marketing programs in which the advertiser pays their media partners directly for some desired action like a sale, lead or click.

Performance Reporting

Visual and numerical reporting that shows how an advertiser’s partner program or ad campaigns are performing over time — such as how many sales each partner generated over a selected time period.

PII

PII is short for Personally Identifiable Information and generally refers to data that contains personally identifiable information, such as login info, emails, phone numbers, names, social handles, etc… They can be used to link together other identifiers and are a highly reliable, deterministic identifier.

Because it is information that has been entered by the user, it is often very reliable. It can also be used to bridge the online/offline identification challenge. PII need to conform to the growing demands of privacy legislation such as GDPR.

Pixel Tracking

Pixel Tracking is used to signal events to a Tracking Service in the web environments where Javascript is disabled. Fortunately, in most web environments, Javascript IS enabled, so the preferred methodology is to use Javascript Trackers instead of Pixel Trackers. In the in-app world, tracking is usually achieved through API tracking integrations.

Pixel tracking can be used to track any important web events: impression events (when ads are shown to a user), click events (when ads are clicked on, or when the user lands in one of the advertiser’s properties through an outbound link from an ad or a link from another site, a clickthru from an influencer mention or affiliate link, etc..) and conversion events (when the user makes a purchase, or completes a lead gen form, etc…)”

Placement Level Fraud

Ad fraud technique in which the user is real, but the ad placement is fake or manipulated.

Placement Verification

Uncovers domain/app masking and spoofing by analyzing discrepancies between referring sources passed through headers, exposing the top level environment in which the user is actually receiving the ad.

Post-bid Fraud Detection

Analyzes the user and placement of an impression after the ad impression is delivered. It can be applied to both premium buys (when advertisers/agencies deliver ads directly to publishers) and programmatic buys (when advertisers/agencies deliver ads via a DSP). Post-bid verification can also measure the viewability of an ad.

Post-click Conversion Rate

Post-click conversion rates represent a measure of users who have both clicked on an ad AND converted.

The formula is:
( # of converting users who have clicked on an ad / # of impressions )

Post-impression Conversion Rate

Post-impression conversion rates represent a measure of users who have both clicked on an ad AND converted.

The formula is:
( # of converting users who have been exposed to an ad / # of impressions )

PPC

Pay per click model, in which an advertiser pays when their ad is clicked on.

PPL

Pay per lead model, in which an advertiser pays when their site visitor provides their contact information to the advertiser.

PPS

Pay per sale model, in which an advertiser pays the affiliate only when a sale happens.

Pre-bid Filtering

Evaluates a placement for brand safety, contextual appropriateness, and ad fraud before a bid is placed. A bid is only placed if verification conditions determined by the advertiser are met.

Pre-bid Fraud Detection

Is a solution to use under a variety of contexts before the bid request to make a media buying or monetization decision based on that risk assessment.

Probabilistic Identifier

Probabilistic identifiers do not rely on deterministic identifiers that uniquely identify an individual. Rather, probabilistic identifiers are simply an approximation of a unique user versus a clear delineation of one. Meaning, there is a chance that two probabilistically identified users may collide and be confused for each other because their probabilistic identifier mistakenly conflates them as the same user. Naturally, the chance for collision is highly dependent on the strength of the probabilistic identification mechanism.

Product Attribution

Product Attribution allows users to run their attribution models at the product-level versus the order or conversion-level. Generally, most attribution companies treat conversions as indivisible units when drawing their path-to-conversion. But, in truth, a conversion could actually represent an order that contains multiple products purchased.

Product Attribution allows the marketer to recalculate pathing and crediting at the more granular product-level instead of simply limiting pathing and attribution at the conversion level. This allows the marketer to see the attributed quantity and revenue for any given product, and is tremendously useful in helping advertisers drive product-specific marketing and media strategies

Product Feed

Also called a product catalog, this is the file that contains a list of all products sold by a given advertiser. Usually includes names, descriptions and prices of the products.

Proxy Piercing

In cases where a user is is browsing via a proxy (like a sophisticated botnet tunneling traffic through multiple devices), proxy piercing techniques can analyze the ad request IP and the end user IP to tease out unacceptable mismatches, in part by recognizing correlations between IP mismatches and other types of fraud.

Publisher

Also known as an partner. Owner of a website which hosts tracking links and promotes brands.

Q

Query

Most people think of search when it comes to a query – the search query is the word or the string of words entered in the search box of a search engine to access some information on the web. The study of search query trends is key to search engine marketing (SEM) optimization.

R

Raw Clicks

Total number of clicks that occur on the same affiliate link.

Reason Code

Reason codes provide event-level classification of the traffic characteristics that tripped fraud risk thresholds.

Redirection

Forwarding a URL to another URL.

Referring Domain

The domain from which a user came when they landed on a new domain.

Retargeting

Retargeting is a lower-funnel technique to target users who have visited the advertiser’s website. In the E-Commerce world, retargeting may get to the granularity of knowing when visitors visited one or more of their product pages, added items to their cart and/or started but did not finish their checkout. Understanding user behavior at this granular level allows retargeters to employ a series of optimization techniques, such as valuing and bidding more for users who are especially deep in the advertiser’s web conversion funnel, or personalizing the ad through dynamic creative.

Retargeting Fraud

Bots acquire retargeting cookies and mimic human browsing behavior in order to collect on the premium CPMs typically associated with retargeting campaigns. Advertisers suffer for investing in audiences that provide no engagement value and relying on distorted campaign performance metrics.

Risk Scores and Ranges

A 0-100 scale provides a simple fraud risk metric – the higher the score, the higher the likelihood of that traffic having fraudulent characteristics.

This scale is broken down into risk ranges:

< 3% (Premium): high quality traffic. Invalid traffic activity may be due to false positives.
3-6% (Low): invalid traffic is not likely. Some invalid traffic may occur at the event level.
6-10% (Moderate): some invalid traffic is likely, concentrated at the event level. Traffic mixing between valid and invalid sources is likely.
10-20% (Elevated): invalid traffic is likely, some concentrated at the event level. Traffic mixing between valid and invalid traffic sources is highly likely.
20-30% (High): Invalid traffic activity is likely to affect the entire source. Traffic mixing between valid and invalid traffic sources is highly likely.
30-100% (Critical): It is not recommended to buy from sources with invalid traffic levels within this threshold.

ROI/ROAS

Return on Investment (ROI) or Return on Ad Spend (ROAS) are often used interchangeably in the media and paid marketing world to represent the value generated by specific marketing initiatives. It can be analyzed at a channel or campaign perspective, although channel managers who are managing a specific channel can use ROI/ROAS to optimize at a more granular level for their channel, such as ad groups and keywords for Paid Search managers, or placements and ads for Display and Video managers.

Rules-based Model

There are various rules-based attribution models such as last touch, first touch, first and last, position-based, time decay and linear. The difference between rules-based and algorithmic models is that rules-based applies the same rules to each and every conversion while algorithmic learns from your data to continually refine a custom data-driven model. Algorithmic takes into account correlations between your media and even external factors like economic conditions and seasonality.

S

SDK

A Software Development Kit is a grouping of software that’s used to develop applications respective to a particular device or operating system.

Search Engine Marketing (SEM)

Promoting of websites by increasing their visibility in search engine results.

Search Engine Optimization (SEO)

Maximizing the visitor volume to a website by optimizing the site to appear high in the list of search results.

Single Opt-In

The simplest conversion flow, where the site visitor only enters his or her information in the form without confirming it via email.

Single-touch Attribution Models

Single Touch Attribution Models are the simplest kind of attribution model, because they allocate 100% of the credit for a particular conversion to a single touchpoint. The most common type of single-touch attribution model is called the Last Click model, which awards 100% of the credit for a conversion to the touchpoint that generated the last click before conversion happened (assuming that the click happened within a particular lookback window).

SIVT

Sophisticated Invalid Traffic (SIVT) is inclusive of complex, advanced fraud types and cannot be easily identified through list or parameter-based filtration. Instead, it takes advanced analytics, multipoint corroboration, and human intervention to uncover and suppress.

Social Advertising

Social ads often appear in walled gardens such as Facebook, Twitter, Instagram, Snap, YouTube and more. Most of these ecosystems don’t utilize the standard IAB-defined mechanisms that are common in display, video and mobile.

Sourced Traffic

Traffic acquired from third parties to augment a publisher’s audience.

Split Testing

Also called “A/B testing”. The practice of testing two different versions of content, copy and/or ads to understand which one works best for the target audience. See also ”Multivariate Testing”.

Stacked Ads

Is placement fraud caused by a malicious publisher stacking multiple ads in nested iframes and monetizing the entire stack on a CPM basis, when only the top ad was viewable.

Statistical Significance

In the simplest of terms, when a statistic is significant, it simply means that you are very sure that the statistic is reliable.There is a lot of math behind this calculation but what you need to understand is the “p-value” which represents the probability that random chance could explain the result. In general, a 5% or lower p-value is considered to be statistically significant.

Strategic Partnership

Also called a brand-to-brand partnership, B2B partnership, or Business Development/Biz Dev partnership, this is an arrangement in which one advertiser or brand promotes the goods or services of another advertiser or brand.

Subway Graph

A subway graph visually shows the marketing touch points along a conversion path according to the “days before conversion” that the marketing touchpoint occurred.

Success Event

A success event is an event within a website or an app which an advertiser decides they want their website/app visitors to do. These can be revenue or lead-generating events such as successful checkouts, or completion of a lead-gen event, or noteworthy intermediary events, such as the creation of a new account, adding items to the shopping cart, or first starting with a lead gen form.

Super Affiliates

Group of select affiliates who generate most of the affiliate programs’ profits.

T

TAG Accreditation

The Trustworthy Accountability Group awards seals such as “Certified Against Piracy” and “Certified Against Fraud” to buyers, sellers, and intermediaries in the digital supply chain who meet rigorous traffic verification requirements.

Targeted Marketing

Distinguishing between different market segments in a marketing campaign. Groups can be distinguished by location, age, interests, etc.

Time Decay Model

Time decay models reward the media touchpoint closest to conversion most and the others receive less credit the earlier they are in the path. Time decay models reward path position regardless of the relative effectiveness of each of the channels in the customer journey. Just like most rules-based models, they ignore external factors.

Note that events may happen beyond a particular lookback window — and these will not receive any credit. For example, if the marketer has a 30-day lookback window in the above example, and a Paid Social event actually happened 31 days before the conversion event — then that Paid Social event does not receive any of the credit because it occurred before the 30-day lookback window.

Tracking Link

A unique linking code that tracks activity of a publisher and publisher’s visitors for a brand. This code is embedded into a text or picture link and helps attribute visitors to the partners who sent them to the advertiser.

Tracking Software

Platforms like MediaRails that track and analyze partner marketing activity in a reliable way.

Traffic

All users that visit a website.

Trafficking

Trafficking refers to the operational process used to set up and launch an ad campaign. Trafficking processes exist on both the demand-side and the supply-side. On the demand-side, it usually involves ad operations personnel on the media agency side, executing campaign workflows on their 3rd party ad server or demand side platforms.

On the supply-side, it usually involves ad operations personnel on the publisher side, executing complementary campaign workflows on their publisher-side ad server or supply-side platforms. Because so much of attribution relies on firing impression, click and conversion trackers through Javascript or Pixel trackers — these are usually set up and implemented as part of the trafficking process by ad operations people on the demand-side.

Tunneling

Some of the most pernicious fraud techniques include tunneling through VPNs, such as botnets operating through proxies. A lot of “mobile web” fraud is really desktop GIVT coming from server farms tunneling through proxies to infected devices.

TV Attribution

TV Attribution Models allow marketers to understand the impact of various dimensions of their TV advertising, such as the TV Ad Network (ABC, Fox, CBS, NBC, …), TV Program and TV Ad Airing Spot, on their website traffic, online sales and other digital activities. It has long been accepted by marketers that airing commercials on legacy TV can often lead to conversions online — but due to the non-addressable nature of TV Advertising, the impact is hard to accurately quantify.

With TV Attribution Models, marketers can collect TV data in aggregate (GRP), and analyze their incremental impact on driving conversions in the online world.

Two-Tier

An affiliate program that allows affiliates to earn commissions from their own sales and from the second-tier affiliates they recruited to participate in the program.

U

Unfriendly iFrame

Does not allow third party participants like ad exchanges or verification vendors to access information about the publisher site in which the iFrame is embedded. This poses a significant challenge to viewability measurement.

Unique Clicks

A type of reporting that allows you to see how many unique people click on your link or ad. This is different from Raw clicks as it doesn’t include duplicate visitors or clicks.

Unique Contribution/Revenue

When assembling a path-to-conversion, it is quite possible to find a number of paths that consist of one marketing touchpoint followed by a conversion. It is easy to conclude that, if that marketing event had NOT happened, then the conversion event may not have happened at all. We therefore measure unique contribution or unique revenue based on the amount of conversions or revenue delivered by a particular touchpoint where it is present in a single-touchpoint conversion path.

Unique contribution represents the number of conversions driven by a channel or media investment that you would not have received if it was not for that media investment’s sole contribution.

Unique revenue represents sales revenue driven by a channel or media investment that you would not have received if it was not for that media investment’s sole contribution.

With the complex channel overlap of today’s marketing environment, you want to measure each media’s unique contribution and unique revenue so you know where you’re getting the most bang for your buck.

For example, if a marketer, by analyzing their conversion paths, find that 50 conversion paths looked like this: Paid Search Click –> Conversion, delivering about $1,000 in revenue. Then the Unique Contribution of Paid Search would be those 50 conversions, and the Unique Revenue would be $1,000.

User Level Fraud

Ad fraud technique in which the user is fake, and the ad placement could be real or fake/manipulated.

V

vCPM

Viewable Cost per Mille, or the cost per 1,000 delivered viewable ad impressions. Calculated only after the impressions have been verified as viewable.

Verification

In the ad tech ecosystem, verification has come to include fraud detection, viewability measurement, brand safety assurance, and contextual categorization.

Video Advertising

Refers to ads that leverage sight, sound, and motion to communicate the advertiser’s message. Includes “in-stream video” and “out-stream video”.

View-through Conversion

View-through conversions represents instances where an audience was exposed to a particular ad (in whatever format — display, video or other), but did not click on the unit to go to the advertiser’s website. However, the user may have registered the exposure to the advertiser’s message in their head. They may go to the advertiser’s site at some point in the near future and take the desired conversion action. When the exposure event occurs within the lookback window duration of the conversion event, then we say that the user has had a “view-through conversion”.

Viewability

Analyzes whether a delivered ad has truly been seen by the user. The IAB dictates that an ad is viewable if 50% of its pixels are visible on the user’s screen for at least 1 second if display and at least 2 seconds if video.

Viewability Fraud

Bad actors can artificially inflate their viewable ad count by using techniques like placing ads in 1×1 containers and loading ads on top of each other.

Viewable Area

Is the portion of an ad that could be seen by a human user, expressed as a percentage.

Viewport

The area of a website that the user sees immediately upon opening a page, without scrolling up or down.

Viewtime

The duration of time an ad meets viewable area criteria.

VPAID

Video Player Ad-Serving Interface Definition is a script first introduced by the IAB to enable interactive elements in video ads. It’s important for its video viewability measurement benefits.

W

Walled Gardens

Walled gardens represent areas in the digital media space where paid media can be purchased, but limited or no tracking data can be extracted at the event level. Most walled gardens will certainly ingest advertiser data in order to optimize campaign performance within the walls of their walled garden, but often do not provide granular (or any) data back to advertiser to allow them to optimize throughout their initiative (across both walled garden and other publishers). The social channels are probably the most famous of the Walled Gardens, including Google YouTube, Facebook, Instagram, Twitter and others.

Walled gardens present a particularly large and existential challenge for marketers and other players within the digital media space since most media dollars are actually captured by the walled gardens

Whitelist / Blacklist

a whitelist defines the domain/apps on which ads exclusively may run. Conversely, a blacklist defines the domains/apps on which ads should not be placed.

Y

Yield

It’s all about the results. It can take a lot of time and effort to build a statistically-significant, accurate attribution model but don’t lose sight of the ROI. Keep your investment balanced with the potential savings or increase in revenue. You wouldn’t spend $100,000 to save $10,000 now would you? But if you have a large revenue stream, a 1% improvement in close rate can easily pay for your investment in attribution.

Partnerships

Ad network

a company that connects publishers (niche website, bloggers) to advertisers (brands and merchants).

Advertiser

a brand or a merchant who pays publishers to promote its products, services or brand as a whole.

Adware

also referred to as “spyware”. Usually unwanted programs users download without knowing they are part of the deal. They track the user’s behavior and place unwanted ads in their workspace.

Affiliate Network

a company that powers affiliate relationships, connecting advertisers and publishers. Typically, an affiliate network’s fee structure is based on a percentage of revenue generated (or of payouts to publishers), rather than a fixed cost.

Affiliate Program

an arrangement through which the merchant pays a fee to the affiliate publisher for generating leads, clicks or sales from affiliate links. These programs can also be known as partner, associate, or referral programs

Alexa Rank

a platform which ranks and estimates websites based on the user’s browsing habits. Its sample contains all internet users and websites.

API

Application Programming Interface that has a set of rules, routines and protocols that are used for building software with graphical user interface components. APIs allow businesses to access data in an automated fashion.

Attribution

The process of identifying a set of user actions (“events”) ​that contribute in some manner to a desired outcome, and then assigning a value to each of these events. Marketing attribution provides a level of understanding of what combination of events influence individuals to engage in a desired behavior, typically referred to as a conversion.

In general, marketers and agencies will use attribution to determine how to distribute credit for a conversion event based on the kinds of exposures and engagement a specific user has gone through in their customer journey on the way to conversion

Attribution, First Click

first-click attribution is when an advertiser credits a conversion to the first click in a conversion path.

Attribution, Last Click

last-click attribution is when an advertiser credits a conversion to the last click in a conversion path.

Attribution, Last-to-Cart

last-to-cart attribution is when an advertiser credits a conversion to the last click in a conversion path before the consumer places an item in their shopping cart.

Attribution, Multi-Touch

multi-touch attribution is when an advertiser attributes partial credit to each “touch” in a conversion path, rather than giving all the credit to the first, last, or last-to-cart click.

Auto-Download Offers

When a site visitor clicks a banner, the content is downloaded automatically without the user’s consent.

B2B

Business-to-business exchange of products or services

B2C

Business-to-consumer exchange of products or services

Banner Ad

A static, animated, or rich media image that partners use to advertise a given product on their webpage.

Chargeback

A product that is returned or a sale that falls through. The commission made through sale is deducted from the partner’s payout.

Click Fraud

Clicks feigned or spoofed to fool advertiser KPIs, defraud CPC campaigns, or steal attribution for a payable event.

Click-Through Rate

The ratio of clicks to impressions, usually displayed as a percentage.

Closer

A partner who “closes the sale”, causing a consumer to convert. Examples include coupon, deal, loyalty, toolbar, and cart abandonment partners. See also: “Introducer” and “Contributor”.

Commission

Also known as a referral fee and the income the publisher receives for referring a lead to the advertiser’s website.

Content Farm

A website that create huge amounts of low-value content to generate clicks and create ad revenue.

Content Publisher

A partner who promotes an advertiser’s goods and services through written content. This can range from an individual blogger to a traditional media company or magazine.

Contributor

A partner who pushes consumers toward conversion, driving value in the middle of the conversion path. Examples can include content blogs and comparison partners. See also: “Introducer” and “Closer”.

Conversion

Conversions refer to success events — they represent actions that marketers want to their audiences to do. There are online conversions — success events that happen on the digital channel, and offline conversions — success events that happen in the physical world. When a user successfully checks out of the advertiser’s e-commerce site, then that’s an example of an online conversion. Another user may go to the advertiser’s brick & mortar location and buy something — an excellent example of offline conversion.

Conversion Path

The list of “touch points” leading up to a conversion. This includes each time an advertiser “touches” the consumer through one of their own marketing channels (such as a display ad or an email) or through one of their partners.

Conversion Rate

A rate of the number of times a tracking link has lead to a sale vs. the number of times the link has been clicked on, shown in percentage. To calculate this rate, take the amount of sales a banner has generated and divide it by the number of clicks. Multiply by 100 and the answer you get is the conversion rate.

Cookie Stuffing

A type of attribution fraud in which a site visitor receives a third-party cookie unbeknownst to him or her.

Cookies

Information that your computer stores in your web browser when you visit a website or click on a link. It allows websites to keep track of your visits and activity, as well as attribute referrals to the relevant partners. Cookies are considered “first party” if the cookie’s domain matches the site the user is on, and “third party” if the domains do not match.

Coupon Publisher

A type of affiliate that generates sales for an advertiser by offering discount codes (also called voucher codes or coupon codes) to their users.

CPA

CPA, or Cost per Acquisition or Cost per Action, is a metric that is tracked in many direct response and performance campaigns, particularly in verticals that are tracking user conversions — whether that conversion represents a sale or a form submission, depending on what the advertiser decides. This is why it’s also often referred to as Cost per Conversion.

Some marketers will include “clicks” as a viable action — in those cases, the calculation is essentially equivalent to a CPC (Cost per Click).

A related concept is eCPA, or Effective Cost per Acquisition. This is often calculated by advertisers who pay on another cost basis such as CPM or CPC, but wish to convert it to a Cost per Acquisition in order to optimize their media buying to some Cost per Acquisition target.

It is calculated as follows:
( sum of the relevant media costs / total # of acquisitions )

So, if a display campaign spent $1,000, and garnered 20 conversions, then the the eCPA = $1000 / 20 = $50

CPC

CPC, or Cost per Click, is a metric that is tracked in many branding, direct response and performance campaigns across any vertical. A click often refers to clickthru on an ad that directs them to the advertiser’s website, though many rich media campaigns may count a click on the ad that triggers some engagement (for instance, the user clicks on the ad to start playing a video, or playing a mini-game on the ad unit); in the rich media situation, this can also be referred to as Cost per Engagement (CPE).

A related concept is eCPC, or Effective Cost per Click. This is often calculated by advertisers who pay on another cost basis such as CPM, but wish to convert it to a Cost per Click in order to optimize their media buying to some Cost per Click target.

It is calculated as follows:
( sum of the relevant media costs / total # of clicks )

So, if a display campaign spent $5,000, and garnered 250 clicks, then the the eCPC = $5000 / 250 = $20

CPL

CPL, or Cost per Lead, is essentially a subset of CPA, or Cost per Acquisition, specifically used by verticals that require the audience to complete a form with their contact info. For instance, in the insurance vertical, an interested user may have to enter their personal info in order to request an insurance quote or have a broker contact them.

CPM

CPM, or Cost per Mille, or Cost per thousand impressions (mille is the latin word for thousand) is one of the most common ways to purchase advertising today. Though it is used across many branding and direct response campaigns, it is particularly suited for verticals and campaigns intended to raise awareness.

For instance, if the CPM is priced at $2, and you wish to deliver 1,000,000 impressions, then the cost of the campaign is

(Total # of impressions / 1000) * $2
(1,000,000 impressions / 1000) * $2 = $2,000

Many advertisers running direct response or performance campaigns who pay for media based on CPM will often calculate an eCPC or eCPA as a KPI in order to track their success and to optimize toward lowering that KPI.

CPS

Cost per Sale, or the price an advertiser pays for each referral that ends in a sale. Essentially a subset of CPA, specifically used by verticals that require the audience to complete a sale.

CPV

Cost per View, or the price an advertiser pays for every time their video ad is displayed.

Creative

A promo tool advertisers create to get visitors to click through and take action. Examples include banners, pop-ups, email copy, text links, badges, etc.

Daily Budget

The budget limit for your campaign on a daily basis.

Deep Linking

A link that allows a website visitor to go to a product page directly. A basic tracking link simply goes to the advertiser’s homepage.

Disclosure

A notice on the partner’s website that notifies readers of the fact that the partner is getting paid for any purchases customers make through their links. It is important to have one to be compliant with FTC laws.

Double Opt-In

A two-step subscription system, in which a website visitor voluntarily fills out a form to receive notifications, and then confirms his or her subscription via email.

EPC

Earnings per click (EPC) is a measurement of how much commission partners tend to make on average for each click they generate for an advertiser’s program. This is a way for partners to estimate how much money they will make on a CPA basis, based on their expected click volume.

Gateway Tracking

A legacy tracking method developed by early affiliate networks. In this tracking method, users who click on an affiliate link are routed invisibly through a “gateway” hosted by the affiliate network, then redirected to the advertiser’s content. As the user passes through the gateway, the network places a tracking cookie in their browser.

Geo Target

Allows advertisers to target a specific country, state, province, city, zip code, postal code, area code, or DMA.

Impression

The number of times a banner ad is viewed by website visitors. One impression means that the ad is displayed only once.

In-House

Advertisers who manage their affiliate program by themselves using an affiliate software or tracking system instead of an affiliate network.

Incentivized Affiliates

Website traffic that is incentivized with actions that will ultimately result in the affiliate earning a commission. Incentives can be prizes, discounts, free subscriptions and others.

Influencer

A social media publisher with a large follower base who promotes brands through social media.

Influencer, Celebrity

Celebrities are often famous because of reasons outside of social media. They can be movie, tv, music or sports stars. Or they can be “cewebrities” – people who made their fame online, but now are recognized universally. (>1M followers).

Influencer, Macro

These larger influencers have often become popular due to social media. Some may be local celebrities whose renown have been amplified by social tools. Some may be digitally-famous category experts. (10K – 1M followers)

Influencer, Micro

These small influencers are numerous, and are often too fragmented to be managed in a high-touch way. Most of this segment is popular exclusively through social media. (<10K followers)

Influencer, Organic

This is a social influencer of any size who says good things about your brand, despite not being paid for those mentions.

Introducer

A partner who “introduces” a product or service to consumers, driving value early in the conversion path. Examples can include social influencers, content partners, and traditional media publishers like news sites and magazines. See also: “Contributor” and “Closer”.

Loyalty Affiliates

Similar to incentivized affiliates, in this case users make a longer term commitment to the advertiser and are required to purchase products and participating in activities. Many loyalty affiliates offer cashback to the user in exchange for purchasing from advertisers through their loyalty portal.

Multivariate Testing

A method for optimizing content in which multiple factors are modified, in an attempt to find the optimal combination. See also: “Split Testing”.

Niche Marketing

Targeting advertisements to a specific market segment.

Offer

Any type of content that’s created by advertisers (merchants) and promoted by partners, which are found in affiliate networks.

OPM

Outsourced Program Management (OPM) is a type of agency that will manage an advertiser’s partner program on their behalf.

Outbound Link

A link to a website other than your own.

Paid Search

An advertising model used on many search engines and content sites. In this model, advertisers bid on keywords and phrases that may be relevant to their target, then pay whenever a user clicks on their ad.

Partner

Any individual or business that works with another business for the purposes of promoting that other business’s products or services.

Partnership Development

The practice of discovering and recruiting individuals or businesses who indirectly sell to your target consumer; it also involves marketing to partners in order to incentivize them to take actions that bring in new customers, increase the frequency of repeat customers, and effectively grow your revenue stream outside of traditional sales and marketing channels.

Partnership Lifecycle Management

The complete set of activities used to forge, deepen and optimize an enterprise’s relationship with their partners. The purpose of Partnership Relationship Management is to manage the Partnership Lifecycle.

The five main stages of Partnerships are:

1) Identifying and discovering new partners
2) Engaging and recruiting them,
3) Onboarding them,
4) Activating them to start driving revenue and
5) Growing and cultivating partner relationships – thereby optimizing your partnership program.

Partnership Management

An approach in which a single business unit or department manages all of a businesses partnerships (such as affiliate, social influencer, and strategic partnerships) on a single platform.

Pay-per-post

A payment model often seen among social influencers, in which the advertiser pays the influencer a flat rate for each post or mention, regardless of performance.

Payment Threshold

The amount of commissions partners are required to earn before being able to withdraw them to their bank account.

Payout

Revenue per one sale or conversion.

Performance Marketing

Marketing programs in which the advertiser pays their media partners directly for some desired action like a sale, lead or click.

Performance Reporting

Visual and numerical reporting that shows how an advertiser’s partner program or ad campaigns are performing over time — such as how many sales each partner generated over a selected time period.

PPC

Pay per click model, in which an advertiser pays when their ad is clicked on.

PPL

Pay per lead model, in which an advertiser pays when their site visitor provides their contact information to the advertiser.

PPS

Pay per sale model, in which an advertiser pays the affiliate only when a sale happens.

Product Feed

Also called a product catalog, this is the file that contains a list of all products sold by a given advertiser. Usually includes names, descriptions and prices of the products.

Publisher

Also known as an partner. Owner of a website which hosts tracking links and promotes brands.

Raw Clicks

Total number of clicks that occur on the same affiliate link.

Redirection

Forwarding a URL to another URL.

Referring Domain

The domain from which a user came when they landed on a new domain.

ROI/ROAS

Return on Investment (ROI) or Return on Ad Spend (ROAS) are often used interchangeably in the media and paid marketing world to represent the value generated by specific marketing initiatives. It can be analyzed at a channel or campaign perspective, although channel managers who are managing a specific channel can use ROI/ROAS to optimize at a more granular level for their channel, such as ad groups and keywords for Paid Search managers, or placements and ads for Display and Video managers.

Search Engine Marketing (SEM)

Promoting of websites by increasing their visibility in search engine results.

Search Engine Optimization (SEO)

Maximizing the visitor volume to a website by optimizing the site to appear high in the list of search results.

Single Opt-In

The simplest conversion flow, where the site visitor only enters his or her information in the form without confirming it via email.

Split Testing

Also called “A/B testing”. The practice of testing two different versions of content, copy and/or ads to understand which one works best for the target audience. See also ”Multivariate Testing”.

Strategic Partnership

Also called a brand-to-brand partnership, B2B partnership, or Business Development/Biz Dev partnership, this is an arrangement in which one advertiser or brand promotes the goods or services of another advertiser or brand.

Super Affiliates

Group of select affiliates who generate most of the affiliate programs’ profits.

Targeted Marketing

Distinguishing between different market segments in a marketing campaign. Groups can be distinguished by location, age, interests, etc.

Tracking Link

A unique linking code that tracks activity of a publisher and publisher’s visitors for a brand. This code is embedded into a text or picture link and helps attribute visitors to the partners who sent them to the advertiser.

Tracking Software

Platforms like MediaRails that track and analyze partner marketing activity in a reliable way.

Traffic

All users that visit a website.

Two-Tier

An affiliate program that allows affiliates to earn commissions from their own sales and from the second-tier affiliates they recruited to participate in the program.

Unique Clicks

A type of reporting that allows you to see how many unique people click on your link or ad. This is different from Raw clicks as it doesn’t include duplicate visitors or clicks.

Marketing Intelligence

Addressable Media

Addressable media refers to any media that can be tied to an individual user, either through a probabilistic or deterministic identifier. For instance, a display ad served in-app can be tied to the user’s device id, making it addressable. However, an ad broadcasted on standard, traditional TV does not pick up any identifier and therefore cannot be traced back to a specific user or household and is therefore not addressable.

It’s easy to assume that all digital channels are addressable, but this is actually not accurate. Most marketers cannot retrieve specific identifiers from the Walled Gardens, leading to large sections of the digital marketing universe that remain non-addressable.

Likewise, it’s easy to assume that all offline channels are non-addressable. But once more, this is actually not accurate. Direct mail is very addressable, and the cable companies have been rolling out addressable TV to better compete against IP-enabled digital TV (Connected TV and OTT)

Algorithmic Attribution

Algorithmic attribution, also known as machine learning, is the process of assigning a portion of credit for a conversion to each touchpoint based on effectiveness. The key differentiator of algorithmic attribution is its use of advanced statistical modeling and inferences to determine an optimal, custom model that continually refines itself based on your data – put more simply, human assisted machine learning.

App Install

Many marketers do have very targeted goals of driving installs of apps they may have recently released, These are often run through Cost-per-install (CPI) programs where the marketer is able to pay their media partners for driving new users to install the app.

App install is often defined as the success metric for the CPI program, though many CPI programs wait until there is an actual post-app-install transaction before paying out. Because of their walled gardens, it’s actually quite difficult to measure whether the app install reported properly within certain advertisers. In cases where app installs need to be rewarded, the “install event” is often only recognized the first time the user starts up the app.

Attributed Conversions

Refers to the fractional conversions allocated by an attribution model to the channels, campaigns, keywords, placements or whatever attributable element. For instance, for a conversion path consisting of a paid search touchpoint followed by a display touchpoint leading to a single conversion, and assuming an even distribution of credit (i.e. a linear attribution model), the paid search channel gets an attributed conversion of 0.5 and the display channel gets an attributed conversion of 0.5

Attributed Revenue

Refers to the fractional revenue allocated by an attribution model to the channels, campaigns, keywords, placements or whatever attributable element. For instance, for a conversion path consisting of a paid search touchpoint followed by a display touchpoint leading to a single conversion worth $50 in revenue, and assuming an even distribution of credit (i.e. a linear attribution model), the paid search channel gets an attributed revenue of $25 and the display channel gets an attributed conversion of $25.

Note that advertisers can choose to provide pure revenue for their attribution analysis, but it’s usually better to use net revenue (which takes revenue and subtracts product costs) for your attribution calculation.

Attributed ROAS

ROAS means Return on Ad Spend, and is a derived metric that captures how effective your media investment was in delivering positive value versus how much you spent on that media. Since Return on Ad Spend (ROAS) is a derived metric, attributed credit is not directly distributed to these metrics. Rather, Attributed ROAS is calculated using Attributed Revenue.

The formula used is:
Attributed ROAS = Attributed Revenue / Media Cost

Attributed ROI

ROI stands for Return on Investment, and is a derived metric that captures how effective your media investment was.

It looks at:

(a) the positive value associated with the user performing the desired action (for instance, making a purchase, where the positive value is the money they spent)
(b) the cost of the media
(c) the cost of goods sold (the cost associated with the product.

As you can tell, Return on Investment (ROI) is related to Return on Ad Spend (ROAS), but also adds the cost of the product in the calculation of the derived metric. Because Attributed ROI is a derived metric, attributed credit is not directly distributed to it. Rather, Attributed ROI is calculated using Attributed Revenue.

The formula used is:
Attributed ROI = Attributed Revenue / (Media Cost + Cost of Goods Sold)

Attribution

The process of identifying a set of user actions (“events”) ​that contribute in some manner to a desired outcome, and then assigning a value to each of these events. Marketing attribution provides a level of understanding of what combination of events influence individuals to engage in a desired behavior, typically referred to as a conversion.

In general, marketers and agencies will use attribution to determine how to distribute credit for a conversion event based on the kinds of exposures and engagement a specific user has gone through in their customer journey on the way to conversion

Attribution Model

An attribution model is a methodology that is applied to all of a campaign’s or advertisers conversion paths in order to determine how to distribute the credit for a conversion. If you are a retailer, for instance, and you find that $200,000 of your revenue in the past month were to users who were exposed to your paid media, attribution models help you figure out how to allocate the credit for the $200,000 across the elements of your paid media. Attribution models help you understand the value of channels, campaigns, placements, keywords, etc… based on the revenue they may have helped generate

Various attribution models can be compared against each other to determine which is the best fit for your goals and gain a more holistic view of each media’s contribution. There is no one perfect model, an organization should continuously update their models and examine their ability to predict future performance.

Baseline Conversions

Baseline conversions, in attribution, refers to the estimated number of conversions that would have happened even without any of the marketing activity being measured by the attribution model. For example, baseline conversions may have been caused by external factors such as hard-to-measure word-of-mouth marketing, or by offline advertising — which cannot be measured by attribution models.

By establishing the baseline conversions before running attribution, the marketer is able to more precisely calculate the lift provided by their marketing initiatives, and only allocate the incremental conversions to the addressable initiatives being analyzed by the attribution system

Bathtub Model

A bathtub model is a rules-based model that allocates a set amount on the first and last touchpoints of a conversion path, and taking the remainder and allocating an equal amount to the middle touchpoints. For instance, let’s say your conversion path consists of Email >> Video >> Display >> Paid Search >> Retargeting. If we configure the bathtub model to allocate 70% to the end points (meaning that Email gets 35% and Retargeting gets 35%) then the remainder gets distributed evenly to the intervening touchpoints (meaning that Video gets 10%, Display gets 10% and Paid Search gets 10%)

Note that events may happen beyond a particular lookback window — and these will not receive any credit. For example, if the marketer has a 30-day lookback window in the above example, and a Paid Social event actually happened 31 days before the conversion event — then that Paid Social event does not receive any of the credit because it occurred before the 30-day lookback window.

Bias

The models you use for attribution can introduce bias. For example, last click is biased in favor of channels that appear later in the buy cycle, such as coupon sites that often attract customers right before they buy, though they likely would have bought anyway.

Category-level Attribution

Attribution is typically run across all conversions that occur within a time period. However, E-Commerce marketers have an opportunity to get more granular, and analyze a subset of their conversions specific to a particular category.

They can run attribution at the category level in order to answer questions like:

* Which channels are best at driving revenue for high-margin categories, like lady’s handbags and shoes?
* Which ones are best at driving conversions for my top-selling men’s shoes category?
and so forth.

Channel

Attribution is about examining all the various channels that are part of the customer journey – both online and offline. Online channels include search, social, display, affiliate, email and so much more. Offline channels like print, television, radio and outdoor are equally as important in an omnichannel customer journey. The nuance here is that the offline channels must be addressable, i.e. they can be traced back to an online visitor in order for the offline channel to appear in the journey. At the aggregate level, both offline addressable and non-addressable explain overall customer response to marketing stimuli.

Channel Predictions

Channel Predictions predict how a marketer’s KPIs are likely to trend over the next 30 days, allowing them to see how they are pacing to their goals based on a number of inputs.

Using Channel Level Predictions or Forecasting, a marketers can know in advance when to sit back and relax (because pacing indicates they are likely to crush their goals) and focus on other areas of growth, or, if Forecasting extrapolate that they will miss their KPI goals, they get early-enough warning to go on overdrive and take additional actions to spur growth.

Click

Clicks refer to the action of engaging with the advertiser’s media. On a mobile device, it’s more appropriate to refer to clicks as taps.

Clicks on many paid search or standard banner ads will typically take users to the advertiser’s website or app.
However, this may not always be the case — clicks or taps on certain types of display ads may trigger a video or other interactive element that keeps the user on the same page.

Click Tracking

Click tracking allow tracking solutions such as Impact to track when the user clicks on something. In truth, clicks can either be tracked directly on the website (the user ends up clicking through into a landing page anyway) or can be trafficked in the advertiser’s ad management system as a 3rd party click through callout. In a web environment, the click tracker is often an executable tag, though pixels are also viable. In-app requires a dedicated API for click tracking since Javascript tags cannot be used within an In-app environment. All necessary contextual information about the referrer (the original publisher or media partner source of the click) is passed along with the click tracker

Consumer Journey

A consumer journey refers to the set of the advertiser’s marketing touchpoints that a particular user is exposed to or engages with over a period of time. It’s easy to confuse the consumer journey with the conversion paths — but they are not the same because many consumer journeys don’t end up with conversions.

Users who end up converting (i.e. in retail, a conversion is often a successful order. In auto, a conversion is often when a user chooses to ‘schedule a test drive’. Consumers who convert are typically exposed to a number of touchpoints beforehand. When customer journeys lead to a conversion, the customer journey is called a conversion path.

Not all conversions are driven by advertising. Some people just go directly to the advertiser’s website and make a purchase – even without receiving any exposure to any paid media. Such a conversion would essentially be organic and have a zero-length conversion path

Content Marketing

Content marketing refers to a marketing technique where the marketer publishes their own short or long-form content (in any format — written, audio, video) and pushes it out to their audiences in the hope that the intellectual property provides value for the reader. Content marketing can take on a variety of angles, such as beginner’s guides, educational pieces, infographics, thought leadership, research papers, buyer’s guides and more.

Content marketing stands in contrast to advertising, which is mostly paid marketing used to build awareness or persuade viewers to take action — the concept of intellectual capital is less pronounced in the advertising world versus the advertising world. However — they are very complementary in nature, since advertising can be used to promote and increase awareness of new content marketing pieces provided by the marketer.

Content marketing is distributed using a variety of methods:

a) Published on-site. Content marketing is often posted on the marketer’s website, and the marketer uses a variety of technique (paid advertising, organic social posts, email, etc…) to reach audiences and make them aware of the new piece of content marketing, and drive them to the site.

b) Published on 3rd party sites. Content syndication can happen in a variety of ways. A marketer may work with a trade association to publish their content marketing on their site (and other promotional channels, for example — content marketing may be disbursed to the 3rd party’s newsletters, etc…). A publisher may incorporate the piece of content marketing into their site as a “Sponsored Article” — which is a form of native advertising

Conversion

Conversions refer to success events — they represent actions that marketers want to their audiences to do. There are online conversions — success events that happen on the digital channel, and offline conversions — success events that happen in the physical world. When a user successfully checks out of the advertiser’s e-commerce site, then that’s an example of an online conversion. Another user may go to the advertiser’s brick & mortar location and buy something — an excellent example of offline conversion.

Conversion De-duplication

A marketer will typically use multiple systems to manage different channels. For instance, they may use an SEM like Kenshoo or Marin to manage paid search, and they may use an Ad Server or DSP like Doubleclick, Sizmek or the Trade Desk to execute their display ads. Each may track conversions independently — and if channel managers are not coordinating, each channel manager is watching their own conversion tracking, and the total number of conversions end up far exceeding the true number of conversions because they are getting overcounted across systems.

In our example above, if a marketer using different systems for SEM and Display noticed 50 conversions the past day, and noticed that all 50 involved both one Paid Search and one Display event each — then if no one does conversion de-duplication, then the marketer may wrongly conclude that they received 100 conversions over the past day — 50 from paid search and 50 from display.

That’s why cross-channel leaders recognize the importance of conversion de-duplication. Conversion de-duplication consolidates and reconciles all conversion events, so that duplicated conversion events recognized by separate systems are unified. It is a necessary step for any reliable Customer Journey Analytics or Multi-touch Attribution analysis.

Conversion Paths

A conversion path refers to the specific subset of consumer journeys that end with a user converting

Conversion Tracking

Conversion tracking allow tracking solutions such as Impact to track when the user converts on something. In a web environment, the conversion tracker is often an executable Javascript tag, though pixels are also possible. In-app requires a dedicated API for conversion tracking since Javascript tags do not run within the In-app environment.

Cookie

Cookies are still the primary deterministic identifier in the desktop and mobile web world. Cookies can either be first-party cookies or third-party cookies.

Apple Safari has been the most restrictive browser and does not allow setting of 3rd party cookies by default on iPhones (though users have the option to alter this behavior from their Browser Settings), and have dramatically limited the lifespan of even first-party cookies with its ITP updates.

Cookie formats are typically non-standardized as most companies maintain their own cookie pools. They are also pseudonymous – that is, they can be tied to personally identifiable information (PII) but when viewed on their own, don’t tell the viewer anything beyond a string of letters and numbers.

Cookie (First Party)

First party cookies are cookies that are issued by the domain that they are currently browsing on

Cookie (Third Party)

Third party cookies are cookies issued by a domain that is different from the domain the user is currently browsing on

Cost Importers

Cost importers are Impact’s tools for pulling in media cost data from 3rd party systems within the advertiser’s tech stack. Cost importers are generally IT-less (they do not require a technical resource to implement the integration) and can be fully configured by non-technical resources from the Impact platform directly.

CPA

CPA, or Cost per Acquisition or Cost per Action, is a metric that is tracked in many direct response and performance campaigns, particularly in verticals that are tracking user conversions — whether that conversion represents a sale or a form submission, depending on what the advertiser decides. This is why it’s also often referred to as Cost per Conversion.

Some marketers will include “clicks” as a viable action — in those cases, the calculation is essentially equivalent to a CPC (Cost per Click).

A related concept is eCPA, or Effective Cost per Acquisition. This is often calculated by advertisers who pay on another cost basis such as CPM or CPC, but wish to convert it to a Cost per Acquisition in order to optimize their media buying to some Cost per Acquisition target.

It is calculated as follows:
( sum of the relevant media costs / total # of acquisitions )

So, if a display campaign spent $1,000, and garnered 20 conversions, then the the eCPA = $1000 / 20 = $50

CPC

CPC, or Cost per Click, is a metric that is tracked in many branding, direct response and performance campaigns across any vertical. A click often refers to clickthru on an ad that directs them to the advertiser’s website, though many rich media campaigns may count a click on the ad that triggers some engagement (for instance, the user clicks on the ad to start playing a video, or playing a mini-game on the ad unit); in the rich media situation, this can also be referred to as Cost per Engagement (CPE).

A related concept is eCPC, or Effective Cost per Click. This is often calculated by advertisers who pay on another cost basis such as CPM, but wish to convert it to a Cost per Click in order to optimize their media buying to some Cost per Click target.

It is calculated as follows:
( sum of the relevant media costs / total # of clicks )

So, if a display campaign spent $5,000, and garnered 250 clicks, then the the eCPC = $5000 / 250 = $20

CPCV

CPCV, or Cost per Completed View, is a metric that is tracked in many video-based campaign across any vertical. A completed view is often triggered once the viewer of the video reaches the end of the video, though due to the idiosyncracies of many video player platforms, it may be triggered when <100% of the video is viewed.

A related concept is eCPCV, or Effective Cost per Completed View. This is often calculated by advertisers who pay on another cost basis such as CPM, but wish to convert it to a Cost per Completed View in order to optimize their media buying to some Cost per Completed View target.

It is calculated as follows:
( sum of the relevant media costs / total # of completed views )

So, if a display campaign spent $10,000, and garnered 200 completed views, then the the eCPC = $10000 / 200 = $50

CPL

CPL, or Cost per Lead, is essentially a subset of CPA, or Cost per Acquisition, specifically used by verticals that require the audience to complete a form with their contact info. For instance, in the insurance vertical, an interested user may have to enter their personal info in order to request an insurance quote or have a broker contact them.

CPM

CPM, or Cost per Mille, or Cost per thousand impressions (mille is the latin word for thousand) is one of the most common ways to purchase advertising today. Though it is used across many branding and direct response campaigns, it is particularly suited for verticals and campaigns intended to raise awareness.

For instance, if the CPM is priced at $2, and you wish to deliver 1,000,000 impressions, then the cost of the campaign is

(Total # of impressions / 1000) * $2
(1,000,000 impressions / 1000) * $2 = $2,000

Many advertisers running direct response or performance campaigns who pay for media based on CPM will often calculate an eCPC or eCPA as a KPI in order to track their success and to optimize toward lowering that KPI.

CPvM

CPvM, or Cost per Viewable Impression, is a metric that is tracked in many campaign across any vertical. A viewable impression is generally measured based on IAB standards — that is, for a display ad, 50% of the ad appears on the screen for at least 1 second, and for a video ad, 50% of the ad appears on the screen for at least 2 seconds.

Since most display or video campaigns today are paid in CPM rather than CPvM, CPvM is usually calculated.

It is calculated as follows:
( sum of the relevant media costs / total # of viewable impressions )

So, if a display campaign spent $2,000, and garnered 200 viewable impressions, then the the CPvM = $2000 / 200 = $10″

Cross-Device Journey

Cross-device Journey depicts the customers journey regardless of which of their owned device a marketer’s touchpoint reaches them on. This is in contrast with a journey that does not factor in cross-device. A user who was exposed to the marketer’s media touchpoints across their mobile device, tablet and desktop will appear as three separate users with three distinct single-device customer journeys instead of one unified user spanning their many devices.

This has always been important, but is growing more and more so. In the US, the average user owns over 3 devices — and that number continues to increase each year. In order for marketers to have any reliability in their Customer Journey Analytics or Multi-touch Attribution solution — it must understand the users’ cross-device journey

Custom Model

Custom Models are rules-based attribution models that are completely defined by the marketer’s business rules. They can start with some base rules-based model (i.e. start off with a a linear attribution model) and can be customized to meet just about any business rule the marketer has. For instance, they can implement a Custom Rule that says “Allocate 30% of the credit to the first touchpoint unless the first touchpoint is a website visit. Allocate 20% to the final touchpoint and distribute the remaining credit to the rest of the central touchpoints.”

Altitude (by Impact) attribution models are very malleable, and Altitude provides pretty flexible ways to shape and customize the attribution model to fit exactly whatever business rule customizations are needed

Customer Journey

The value of attribution is to examine the journey that led to the desired action – this includes cross channel (online, offline) and cross device (desktop, mobile, tablet). 79% of users own three or more devices. Recent studies show that users switch between devices up to 27 times per hour.

Customer Journey Analytics

Customer Journey Analytics refers to a category of marketing intelligence products that deal with analyzing metrics and structures associated with the customer journey.

Marketers can, for instance, ask questions such as:

* What is the average number of touchpoints along the customer journey for converting paths?
The marketer may choose to anti-target a user who dramatically exceeds that average by a wide margin.

* What is the most popular way that converting paths start?
The marketer may choose to dial-up some of their investments on these first touch channels or campaigns

* What is the average duration of a conversion path?
The marketer may choose to anti-target users who far exceed the typical duration that most users take to convert

Many of these Customer Journey Analyses can be performed directly from the available Impact reports, though a user who would really like to dig deep into them can analyze individual paths through PAQL, Impact’s proprietary querying language for customer journeys.

In the future, we anticipate marketers to leverage Customer Journey Analytics to start activating marketing investments to guide users down higher-conversion rate paths.

Dashboard

A dashboard is a set of visual widgets that are used by specific roles within a data-driven marketing department to run their business and make decisions. Visual widgets can include longitudinal charts, snapshots-in-time breakdown charts, tables, lists, trending or forecast graphs, real-time KPI scoreboards, goal meters and many other innovative mechanisms to visualize numerical data in order to simplify and bubble up insights.

Generally, different members of the marketing organization will want to have organize, assemble and tailor their own dashboards to support their unique role, root-cause analysis methodologies and visual preferences. For instance, the CMO Dashboard will in general be far broader and shallower than the Paid Search Manager or Display Dashboards, which would be channel-specific and far more granular

Dashboards visuals generally fall into a number of major purposes:

* Monitor Performance – High-level mission control views to monitor on general performance on a regular basis to ensure that day-to-day performance is going according to expectation, and there are no major anomalies in the data (e.g. If one of your channel systems goes down, for instance, marketing leadership may immediately notice a drop in delivered impressions)

* KPI and Goal Monitors – A data-driven organization always measures KPIs and tracks it to strategic marketing goals. It’s important that every member of the marketing team keeps close tabs of how they are tracking to their goals, and constantly making the required adjustments to make sure they hit them

* Compare Longitudinally – Time is one of the most important dimensions in marketing analytics, and most growth organizations will want to ensure that certain important metrics (like Attributed Revenue or Return on Ad Spend) are growing month-over-month or year-over-year (particularly for seasonal businesses)

* Root Cause Analysis – These are drill-down widgets that allow you to look at anomalies and dig deeper into what might be causing a particular trend. The ability to get granular is a crucial part in being able to answer “Why?” questions and derive smart insights that can be used to take action and optimize wisely

Data Integration

With so much data available these days, the challenge is to consolidate it all and extract clear, actionable insights. Finding a platform that can systematically integrate data from various sources will help to tame your big data madness.

Data Quality

When it comes to data, many marketers intuitively believe in garbage in, garbage out. The data used in attribution modeling needs to be harmonized and cleaned to a common level of granularity so that it is useful. Utilizing data from various sources guarantees disparate data and finding a way to correlate it is critical.

Data Silos

Data silos generally refer to a particularly insidious issue in marketing intelligence that has arisen from the precambrian explosion of channel-specific systems over the past 20 years. As the number of ways for a marketer to reach their audiences through digital media have grown (and continues to grow), point solution systems have emerged to supply planning, workflow and optimization tools for those channels. These tools have generated an ever-growing mass of data, and marketing organizations have typically kept these point solution data as separate siloes to keep their channel teams’ management and optimization processes streamlined.

Unfortunately, data silos gave rise to a number of problems that have gotten in the way of providing reliable marketing intelligence (and many marketing intelligence systems have simply ignored many of these problems)

* No Omni-channel View – When data remains fragmented in siloes, then marketing leaders are not able to truly understand, at a holistic level, everything that is going on across their media. Many marketing organizations have taken to exporting reports from different systems, and manually patching together reams of unreconciled Excel spreadsheets together, an error-prone and time consuming task that often arrives too late after campaigns are already over, all in order to simply understand what is happening at a high-level

* Duplicated, Unreconciled Data – Most systems have mechanisms to optimize for their own channel. These often require firing a conversion tag when a user reaches a success event within the advertiser’s website or mobile app. Unfortunately, each channel system is firing and measuring its own conversion events in an unreconciled way, leading to each channel system claiming credit and resulting in the over-counting of conversions.

* Potential Bias – Several channel systems have stepped forward to offer themselves as a solution for consolidated channel tracking, but many of these systems are owned by enormous media owners. If the systems that are evaluating performance are also owned by the media owners who are being evaluated, then the potential for introducing bias is great

Deterministic Identifier

A deterministic identifier is an identifier that can be definitively tied to a specific user’s device.

The most common deterministic identifiers include:

* Cookies — which, despite many actions taken by Safari and Chrome, remain an indispensible identifier in the desktop and mobile web world

* IFAs — identifiers for advertisers, which are primarily used in the in-app world. Android and iOS platforms maintain their own proprietary scheme for device identification

* PIIs — short for Personally Identifiable Information, this refers to data that can be tied to an individual, such as login info, email, phone numbers, names, social handles and others

Device Fingerprinting

Device fingerprinting often leverage either proprietary or open-source methods for collecting data from digital transactions in order to uniquely identify a user.

This can sometimes lead to a surprising level of accuracy, depending on the technique used. A common fingerprinting mechanism, for example, leverages the specific collection and order of fonts on a user’s device to uniquely identify them.

Many companies may use some of these methods combined with their own. Because these are simply an approximation of the unique user versus s clear delineation of one, fingerprinting is a probabilistic method – and there is a chance that two users may collide and be confused for each other because they have the same fingerprint.

Because each vendor has their own secret fingerprinting recipe, the lifespan and scope of a fingerprint varies from vendor to vendor.

Digital Media

Digital media often refers to all media techniques delivered over the internet or wireless environment, including email, SMS marketing, paid search, paid social, digital video, display, native, digital audio and more. This is in contrast to offline media, which refers to all media techniques related to traditional pre-internet channels

It is often mistakenly referred to all digital media as addressable media which is erroneous because many digital marketing activities, such as advertising on YouTube or Twitter, actually non-addressable outside of the walled gardens’ tools.

Earned Media

The term Earned Media is often used in conjunction with the other two types of media: Paid Media and Owned Media. Earned Media, as opposed to Paid Media or Owned Media, represents word-of-mouth marketing (content that is generally not paid for) that helps build awareness for the brand, or drives visitors into the advertiser’s owned media.

Examples of earned media would include social mentions, likes, reviews, SEO, retweets, recommendations. Producing great content (eBooks, webinars, blog posts, etc…) is also an effective vehicle for driving earned media, because that content can be syndicated and generate inbound links, etc…

External Factors

A strong attribution model will take into account non-marketing elements such as seasonality, major holiday events, macroeconomic factors and competitive activities which can also greatly influence sales.

First Touch Model

A First Touch model is a rules-based model that allocates 100% of revenue to the very first touchpoint of a conversion path within a given lookback window.. For instance, let’s say your conversion path consists of Email >> Video >> Display >> Paid Search >> Retargeting. In a First Touch Model, 100% of the revenue is credited to the Email event since it is the first touchpoint in the conversion path.

Note that events may happen beyond a particular lookback window — and these will not receive any credit. For example, if the marketer has a 30-day lookback window in the above example, and a Paid Social event actually happened 31 days before the conversion event — then that Paid Social event does not receive any of the credit because it occurred before the 30-day lookback window.

Forecast

Attribution is no longer about just looking back to see what led to the desired action, it’s about being able to forecast how shifts in spending will ultimately affect your revenue. Forecasting, or marketing mix modeling, is a great tool to help marketers determine optimal media investments.

Goal Tracking

Goal tracking refers to a practice used by data-driven marketing organizations to measure and keep track of the pacing of their Key Performance Indicators. Well-designed marketing goals and KPIs are designed such that they support even higher-level cross-departmental business goals and KPIs

Granular Data

User-level customer journey data provides a level of granularity that isn’t part of marketing mix models (MMM). The ability to construct the exact sequence of touchpoints leading to a conversion provides a level of insight that can identify correlations between channels and make it possible to optimize your integrated marketing strategy.

Gross Rating Point

GRP stands for Gross Ratings Points, and is used to measure a combination of reach and frequency of a particular ad campaign across the population corresponding to the marketer’s desired audience. It is often used as a measurement of legacy TV reach.

GRP is calculated using the following formula:
GRP = 100 * Reach (% of Target Audience) * Average Frequency

For example, if a marketer wishes to reach females 18-30, and executes a TV campaign that airs on 5 TV episodes for a TV show that reaches 30% of the target audience of females 18-30, then the GRP is 150 (i.e. 100 * 30% * 5).

Homogeneous Data

Disparate data is the root of all evil when it comes to attribution. Mapping data from various sources into a single source of the truth is necessary to establish a homogeneous data set for modeling. Don’t start modeling until your data is homogeneous.

Identifiers

Identifiers are attributes or mechanisms that are primarily used to establish the identity of a user. They are an important building block in much of performance marketing because they help tie different marketing touchpoints (such as ad exposures and paid search clicks) to actual success events (conversion events).

Identifiers come in two flavors: deterministic identifiers (which can be used to definitively identify a user or device) and probabilistic identifiers (which can be used to approximate the identity of a user or device). The most common types of identifiers are cookies, IFAs, PII and device fingerprints/snapshots

Identity Graph

We’ll use the term identity graph and device graph interchangeably. A Device Graph (as per Digiday) is a map that links an individual to all the devices they use. This could include a person’s computer at work, laptop at home, tablet and smartphone. As the internet of things starts increasing the number of connected, digital, IP-enabled devices owned by a user, the identity graph will grow to also include their OTT/Connected TV, smart speaker, and other smart devices. Instead of counting each device as the behavior of a different person, a device graph counts them as one person, so there’s no duplication. Advertisers can then see things like what time of day a person was exposed to an ad and on which device, which helps show what role any particular ad had in a purchase.

Identity graphs consist of identifiers matched up with data assets that help link together different identifiers into something that may represent an individual.

A simple identity graph may consist two identifiers, like cookies, matched together by some shared unique data asset:

a) A more common identity graph might consist of a set of identifiers that have been mapped to a user through an abstract concept such as a User Id. In this case, we’re not tying the identity of the user to some pseudonymized piece of PII information such as a hashed email, but to a unique user identifier:

b) As you can see above, the identity graph attempts to “identify” a user by linking together a series of deterministic identifiers such as cookies, IFAs along with pseudonymized deterministic through hashed emails and cookie synching along with probabilistic links through device fingerprinting.

Identity Resolution Services

Identity Resolution Services refer to solutions providers such as TapAd, Drawbridge, Screen6 and others, whose primary activity is building out, enriching and maintaining an identity/device graph of users. These solutions are often integrated with other advertising systems to offer perceivable customer value to the marketer, such as the ability to provide accurate reach metrics, maintain frequency caps, perform smarter targeting, offer more reliable metrics and more.

Impact solutions such as Radius and Altitude leverage a combination of 3rd party Identity Resolution Services and its own proprietary identity graph, to recognize users across their devices to stitch together omni- channel customer journeys, provide deeper customer journey analytics and calculate more reliable attribution for smarter media optimization.

IFA

IFA stands for Identifiers for Advertisers, and are particularly relevant for the in-app world. These identifiers are maintained by the platforms they are on (usually Apple iOS or Google Android) and are useful for identifying a unique device across all apps on that device. It is typically inaccessible on the mobile browser though.

Like cookies, they are deterministic and consist of a string of 32 alphanumeric characters and are pseudonymous. Unlike cookies, they are controlled completely by the platforms they are on, and typically (with the exception of fraudulent device reset farms) have a long lifespan.

Impact Consortium

The Impact Consortium is Impact’s own proprietary identity graph, used to power Impact’s expansive attribution capabilities.

Advertisers who onboard into the Impact Platform have the option to join into the Impact Consortium. If the advertiser passes in customer identity data (say, their email address when the user logs into the secure area of the advertiser’s site) into our Universal Tracking Tag, Impact captures a deterministic identifier that ties a specific user to a device. When the user logs in across multiple devices, and when the advertiser fires the UTT tag across those devices, then the Impact platform is able to tie the user and their multiple devices.

The Impact Consortium is fully compliant to privacy legislation such as GDPR.

Impression Trackers

Impression Trackers allow platforms like Impact, with its powerful tracking capabilities, to track when the user receives an impression — usually of a display or video ad.

Impression trackers are often trafficked in the advertiser’s ad management system as a 3rd party impression callout. In a web environment, the impression tracker is often an executable Javascript tag, with an pixel trackers as backup for environments that do not allow Javascript to be executed.. In-app requires a dedicated API for Impression tracking since Javascript tags cannot be used within an In-app environment. All necessary contextual information about the publisher is passed along with the image tracker

Incrementality

Incrementality refers to a measurement of advertising effectiveness that can be measured by attribution at multiple dimensions of granularity: channel, campaign, keyword, placement, etc… It indicates the amount of lift to a particular metric (i.e. incremental sales, incremental conversions, etc…) that is brought about by the marketing investment — comparing, for example those who were exposed to or clicked on a particular channel, campaign, keyword, placement, etc… versus one who had not had that touchpoint.

Incrementality can often be measured effectively by more advanced attribution algorithms, such as ones that leverage advanced statistical or machine learning techniques that calculates the likelihood of an increase on the target metric based on the presence or absence of a particular touchpoint in both customer journeys that end in conversion and ones that do not.

Install Tracking

Install Tracking is specific to the mobile/tablet world and allows an advertiser to track when their ad campaigns have resulted in a new install. Many marketers run their own Cost-per-install (CPI) programs to encourage users to download their app and use it.

Since there’s really no way way for you to fire 3rd party tracking code directly in the app store, meaning that there is no way to detect the install event directly from the app store event, most advertisers usually end up firing the Install Tracking Event when it detects that the app has only been opened for the very first time by the new mobile owner.

Intra-Device

Intra-device is particularly applicable to the mobile world, and refers to the ability to recognize a user within the same device, but across mobile web and in-app. Recall that 3rd party cookies are often deactivated in many devices in the mobile web, and unless the user does not clickthru on an ad or affiliate link, there are few alternatives to recognizing the user outside of probabilistic identifiers. When the user goes to a mobile app, on the other hand, there is often a way to recognize the user through deterministic identifiers (IFAs).

Identity Resolution Services that can bridge the gap and recognize users as they move from mobile web to in-app can map out and include the intra-device journey, which can be woven into an overall understanding of the user’s cross-device journey

Javascript Tracking

Javascript Tracking is used to signal events to a Tracking Service in the web environments where Javascript is enabled (which will happen in most cases — most users browsing the web on desktop or mobile will usually have Javascript enabled). In web environments where Javascript is disabled, tracking can usually still be accomplished by image trackers. In the in-app world, tracking is usually achieved through API tracking integrations.

Javascript tracking can be used to track any important web events: impression events (when ads are shown to a user), click events (when ads are clicked on, or when the user lands in one of the advertiser’s properties through an outbound link from an ad or a link from another site, a clickthru from an influencer mention or affiliate link, etc..) and conversion events (when the user makes a purchase, or completes a lead gen form, etc…). It can also measure other related metrics typically associated with web analytics, such as session-level duration, # of pageviews, etc…

KPI

A KPI, or Key Performance Indicator, is a measurement that will directly affect your marketing objectives. They can be identified by examining your strategic business goals, and deciding how to measure your progress towards those goals. Every business has unique KPIs so be sure you are measuring the most meaningful metrics to make more educated marketing decisions.

KPIs sometimes correspond to individual metrics, but more often, they are calculated from a series of metrics you are tracking. One common example of a KPI for advertising is ROAS (return on ad spend). ROAS is a measurement that evaluates gross revenue generated for every dollar spent. The math is simple if you have the tracking data you need. ROAS = revenue from ad campaign, minus the cost of the ad campaign, divided by the cost of the ad campaign.

Last Click Model

Last Click attribution assigns 100% credit to the final touchpoint (i.e. clicks) that immediately precedes a sale or conversion. While last click is important in identifying the closer, marketers should be sure to also examine the introducer (first click) and influencers (middle touches) as well.

Lifetime Value

The Lifetime Value (or LTV for short) captures the total value generated by a particular customer for a given advertiser, usually because of repeat purchases or conversions made by a given customer. Consumers with high LTV are a brand’s most valuable consumers, and many marketers rightfully attempt to locate audiences that increase their average LTV.

Linear Model

A linear model is a rules-based model and one of the simplest ones for those who are starting out when moving from single-touch attribution models to multi-touch attribution models. A linear model allocates an equal amount of credit to all involved touchpoints of a conversion path. For instance, let’s say your conversion path consists of Email >> Video >> Display >> Paid Search >> Retargeting. The linear model allocates an equal amount to each touchpoint, so Email gets 20%, Video gets 20%, Display gets 20%, Paid Search gets 20% and Retargeting gets 20%.

Optimizing marketing channels based on an even model means that the advertiser is rewarding frequency alone but not any external factors such as seasonal or macro-economic factors. An issue with this model is that diminishing returns and relative channel effectiveness are not accounted for as all channels and path positions are credited equally so more spend leads to linearly more conversion.

Note that events may happen beyond a particular lookback window — and these will not receive any credit. For example, if the marketer has a 30-day lookback window in the above example, and a Paid Social event actually happened 31 days before the conversion event — then that Paid Social event does not receive any of the credit because it occurred before the 30-day lookback window.

Lookback Window

A lookback window represents the amount of time (usually specified as a number of days) prior to a conversion that a marketer decides would be a reasonable period of time for a marketing touchpoint to have credibly influenced a customer’s decision to convert. The lookback window is applicable for both single-touch and multi-touch models — both rules-based and machine-learning attribution models.

If a marketing event took place prior to the lookback window, then it is not considered when the attribution model is applied. For example, if the marketer decides to use a 30-day lookback window (meaning, consider only marketing events 30 days prior to a conversion, but no more), then if a paid social event happened 31 days before a conversion, then it would receive no credit whatsoever for that conversion, regardless of attribution model.

For most products, a 30-day lookback window is reasonable and standard. Certain types of products, such as autos and durable goods, may opt for a 90-day lookback window as more appropriate to reflect the longer purchase and decision-making cycle for those types of products

Machine Learning Attribution

A machine learning algorithm leverages advanced statistical techniques such as linear and nonlinear regression, cooperative game theory and other data mining methods, to allocate credit in the fairest possible way possible, based on a touchpoint’s propensity to increase an audience’s likelihood to convert. It looks at all the touchpoints — both the presence and absence of touchpoints — and their role in driving incremental value — looking at both the baseline, converting paths and non-converting paths.

It is often perceived to be the most bias-free of distributing credit, but receives pushback from marketing organizations due to the perceived black box nature of its algorithm, particularly for those unfamiliar with its specific methodology or data science techniques in general. Most attribution vendors will have their own proprietary implementations of data science methodologies and will mix in some of their “secret sauce” in order to provide what they believe, would yield the most optimal set of incrementality calculations for their customers.

Marketing Event

A marketing event represents a trackable event such as an exposure to a display ad, watching a video ad, clicking on a paid search or paid social ad, tapping on an affiliate or influencer link, clicking through from an email or newsletter into the website, etc… These marketing events or touchpoints become the basic building blocks of a customer journey, and can be stitched together to illustrate all of the ways the brand has engaged with their audiences in hopefully persuading them to eventually convert.

Marketing Intelligence

Marketing intelligence refers to the systems, skills and processes that allow marketing organizations to make smart, data-informed decisions, usually through well-designed reports, KPIs, dashboards. For our purpose, we hone in on a particularly important marketing question: how to allocate their marketing spend most effectively based on the ROI and incremental value provided by their different marketing investments.

In order to make informed, holistic decisions specifically around allocating spend, marketers need to look at all aspects of the marketing problem. Marketers thus have to capture information across multiple marketing domains, including customers (which includes current customers and prospective customers), channels, media, customer behavior, sales and more. Marketing intelligence consolidates all this information into a centralized location so that the marketer has an overarching view that they can use to make smart and informed decisions regarding their marketing initiatives and spend.

Note: The use of the term “Marketing intelligence” can be confusing because it is used quite broadly. For instance, you can read various trade journals and magazines to receive “marketing intelligence” around the latest developments in the industry. This is not what we mean by “Marketing Intelligence” though.

Salesforce.com, a salesforce automation tool, may provide some marketing intelligence around the prospect funnel. Marketo, a marketing automation tool, may provide some marketing intelligence around customer engagement on the marketer’s email or landing pages. Many of these martech tools might even have sophisticated KPI trackers, visualization or querying platforms to provide intelligence to specific questions in marketing.

But for our purposes, these are not true “Marketing Intelligence” systems because they focus on very specific problem siloes rather than providing systems that allow marketers to receive marketing intelligence across the larger marketing universe – across channels, campaigns, devices, audience types and vendors – as a whole – which is necessary for answering the larger marketing question focused on smarter allocation of media spend.

Marketing System of Record

A marketing system of record or marketing source of truth (we use the two terms interchangeably) allows users to consolidate all their data into a single platform, and leverage it for to achieve marketing intelligence by applying various data applications such as KPI/goal tracking, scorecarding, dashboarding, reporting and attribution on top of the consolidated data.

Why do marketing organizations need a system of record?

Because marketing organizations are experiencing an explosion of marketing technologies that have come about in the past few years to deal with the growing complexity and proliferation of channels they have had to oversee. With over 5,000 marketing technologies available in the market, marketing organizations have a harder and harder time gaining visibility into their investments, what media efforts are truly making an impact on their customers, and which marketing initiatives are delivering positive net value.

A Marketing System of Record, does the following:

Collect. Automates the ingestion and consolidation of the marketing campaign data from different systems and different sources stretched out across different channels Reconcile/Normalize. Data consolidated into a single system need to be cleaned up, unified and normalized. Customers who may be recognized by an email address in one system, a cookie in another, and a device id in a third system needed to be reconciled into a single identity Apply. Knowledge-based applications could then be built over this robust source-of-truth for marketing data. This runs a gamut, from analytical applications such as reports, KPI measurement and visualization tools to advanced data applications such as customer journey pathing and attribution analysis

Media Mix Modeling

A media mix model is an econometric top-down model that bridges the online world with the offline one. Media Mix Models are great for assessing whether non-addressable media like TV, radio, print, out-of-home and others are pulled into the media mix model, along with external factors such as macroeconomics, weather and seasonality – all these elements can also be factored into the Media Mix Modeling’s longitudinal statistical analytics.

Media Mix Models, marketers receive guidelines, informed by advanced econometric data, that tell them which factors are most impactful in driving a lift in revenues or conversions, thus giving marketers directional recommendations on how to allocate their media budgets across offline AND online advertising to maximize impact.

Model Overfitting

Overfitting is a modeling error which occurs when a function is too closely fit to a set of data points, which is a no-no in data science and limits the practical usability of a model. One can, in theory, create a model that explains all the data points of a particular test data set extremely well to the point that too many parameters are used to explain away most residual variation (i.e. all the noise). The consequences of using an overfitted model is that the overfitted model becomes ill- suited to explain the behavior of another data set representing the general population, because it has been over tailored to the test data set.

Model Validation

The statistical model used to generate attribution findings should be validated with in-sample as well as holdout sample, or “control” (a sample of data not used in fitting a model) – the holdout sample is used to assess the performance of the models.

Multi-funnel Conversion

Most conversion funnels are simple – eCommerce funnels often involve only one: Land on the site > shop for a product > add it to cart > checkout > order confirmed!

However, some businesses rely on far more complicated conversion paths, and may leverage multiple conversion funnels, thus we use the term Multi-funnel Conversions to describe this. Conversion funnels often lead to intermediate “success events”, and it’s not uncommon for marketers to optimize towards these immediate “success events” – especially when the conversion process is complex, lengthy and true value only gets realized after the user makes their way through subsequent conversion funnels. For example, marketers may optimize towards driving users to subscribe to a service/create an account, but not necessarily use the service or perform some revenue-generating task. This is when it’s important for platforms to support the concept of “multi-step conversion funnels”

Analyzing the behavior across multi-funnel conversions allow marketers to define multiple “success events” and effectively stitch together conversion funnels. By doing so, marketers maintain a view of their short-term conversion performance (which media is driving the most account signups) but are also able to determine which media investments introduce customers who provide true value in the final conversion of a multi-step conversion funnel process (which media is driving the account signups that eventually perform some revenue generating activity later on).

Multi-touch Attribution Models

Multi-Touch Attribution Models (or MTAs for short) are more complicated than Single-touch Attribution Models. MTAs seeks to distribute credit across more than one touchpoint in a conversion path. One of the biggest deficiencies of single-touch attribution models is that it does not recognize a fundamental fact around marketing and advertising: that is, that that marketing and advertising is usually a “team sport” and that multiple touchpoints cooperate together to convince a prospect to eventually convert.

It’s usually not a one-person effort. Certain type of video advertising may be good in building out awareness. Rich media advertising or email campaigns may be good at building out interest and purchase intent. Paid search may be the final step after the user decides that they already want to make a purchase. All these channels come together to successfully drive a conversion.

Non-Addressable Media

Non-addressable media refers to any media that cannot be tied to a unique user because no unique identifier can be extracted when the ad is delivered. For instance, when an ad is delivered through traditional TV, Radio, or when an ad is printed on a newspaper or on a billboard, that ad is generally classified as non-addressable. This is in contrast to addressable media, which CAN be tied to an individual user, either through a probabilistic or deterministic identifier. For instance, a display ad served in-app can be tied to the user’s device id, making it addressable.

It’s easy to assume that all offline channels are non-addressable. But once more, this is actually not accurate. Direct mail is very addressable, and the cable companies have been rolling out addressable TV to better compete against IP-enabled digital TV (Connected TV and OTT)

Likewise, It’s easy to assume that all digital channels are addressable, but this is actually not accurate. Most marketers cannot retrieve specific identifiers from the Walled Gardens, leading to large sections of the digital marketing universe that remain non-addressable.

Non-Converting Paths

Non-converting paths represent customer journeys that do not resolve into a conversion. This may be because the user has not converted yet, or may never actually convert at all. It is important for marketing intelligence solutions to understand both converting paths and non- converting paths in order to truly understand, from an attribution perspective, how influential different touch points are in truly driving lift and increasing users’ propensity to convert.

Normalized Data

Normalizing data for the purposes of marketing intelligence is the process of organizing data from disparate data sources — often representing different channels and data models — into a centralized repository with data structures that can support all the necessary data regardless of source. Normalization also makes the assumption that the data is de-duplicated and redundancy is reduced, and all important dependencies between the data set are captured in the most efficient way possible

Offline Conversion

Offline conversions refer to success events that happen outside of addressable digital channels, such as sales in brick & mortar locations, or closing a sales through the advertiser’s call center, or closing a lead through a third party agent or franchisee. There is usually enough PII information collected from the offline conversion (information such as names, credit card numbers, etc…) that allow marketers to identify the individual performing the offline conversion.

Through integrations with marketers CRM systems, it should be possible to tie a user’s digital activities (including their marketing journey and online conversions) with offline conversion events.

Why would a marketer want to do that?

Because conversions, whether offline or online, do not happen in silos — and being exposed to marketing messages online has been shown to drive sales in the brick & mortar world. Because of the online/offline divide, too many marketers have taken the easier route of associating offline conversions with offline marketing, and online conversions with online marketing — but customers don’t think and behave in such a simplistic manner. By looking at customer journeys that drive both online and offline conversions, marketers are able to obtain a far more accurate picture about the incremental effects of their digital marketing on ALL types of conversion events

Offline Media

Offline media is often used to refer to legacy media techniques that predated the rise of the internet, such as TV, Radio, Print, Direct Mail, Call Centers, Cinema Advertising, Billboards and more. This is in contrast to digital media, which refers to all media techniques related to the internet

It is often mistakenly referred to as non-addressable media which is erroneous (many direct mail and call center techniques are highly addressable marketing activities).

Omni-channel

Omnichannel is defined as a multi-channel sales approach that focuses on an integrated shopping experience across all channels. Customers may encounter many touchpoints and move between online and offline channels, such as ordering online for in-store pickup. Each channel’s role is considered in relation to others and the customer experience is designed to be seamless and consistent.

Owned Media

The term Owned Media is often used in conjunction with the other two types of media: Paid Media and Earned Media.

Owned Media refers to all media efforts that are in full control of the advertiser, and generally does not incur any variable payout to an external publisher (i.e. An ad creative may be fully designed and built by the advertiser, but in order to disseminate it, you need to pay publishers to place it on their site). Examples of Owned Media include the advertiser’s website, any media properties or microsites they may own, any mobile apps they build, any blogs they maintain, posts and tweets they may do on any social channels they maintain, customer base email marketing they may do, etc… Furthermore, when marketers invest in enriching one’s owned media, it also pays dividends on the Earned Media front (and, to an extent, on the Paid Media front — for example — better quality landing pages on the advertiser’s site can help improve quality scores on their Paid Search efforts).

Paid Marketing

Paid Marketing refers to all initiatives undertaken by a marketing organization that requires some form of payment for delivery of exposure, engagement or conversion from the advertiser’s prospective audience. Paid Media, which is often used to describe advertising-like activities, is a subset of Paid Marketing. Apart from advertising, other initiatives that go under paid marketing could include affiliates, influencers, business-to-business strategic partnerships, local and client brand ambassadors and many more.

Paid Media

The term Paid Media is often used in conjunction with the other two types of media: Owned Media and Earned Media.

Paid Media is often referred to as advertising, and often refers to media exposure that is paid for at either a CPM or fixed-fee typed basis (though much advertising DOES get paid for through alternative payments models like Cost per Click (CPC), Cost per Lead (CPL), Cost per Install (CPI) or Cost per Acquisition (CPA).

Paid Media typically consist of these formats/channels: Standard Banners, Rich Media, In-Stream Video, Digital Audio, Native, Paid Search, Paid Social, Digital Out of Home, and of course, traditional offline formats/channels such as TV, Radio, Print (Magazines or Newspapers), Outdoor, Cinema, etc…

Pathing

Pathing refers to the process of stitching together customer journeys and analyzing their structure, metrics and characteristics for additional insight. Stitching customer journeys together can often be a tedious, difficult and error-prone process, and one that cannot be done manually without technological solutions to support it.

Here are a sampling of difficulties that come from doing this:

1) Collection and Assembly of Touchpoints. Most marketers on average leverage 12+ different systems to manage and launch their campaigns. Cost and transactional data need to be either ingested into a central system, or the data can be captured through Javascript, Image or API Trackers deployed on every system that needs it.

2) Reconciliation of Touchpoints across Devices. Most audiences today own 3-4 internet-enabled devices, and that number continues to do up. Stitching together customer journeys require a deep understanding of assembling a cohesive multi-device identity graph to ensure you have a reconciled customer path across all their devices.

Pathing and Attribution Querying Language (PAQL)

The Pathing and Attribution Query Language, or PAQL for short, is a proprietary patent-pending language for marketers to collect customer journeys, across multiple devices and multiple channels, in order to generate custom pathing and attribution marketing insights.

PAQL can also be used to tailor the behavior of rules-based attribution models in order to fulfill just about any custom business rules required by an organization. PAQL is a highly flexible way of creating bespoke attribution models necessary to meet the unique attribution modeling needs of any marketing organization.

People-based View

People-based view refers to looking at marketing data, not as a series of unrelated marketing touchpoints and events, but as a stream of inter-related events tied to a particular person. This means, the marketing intelligence solution needs to normalize and stitch all marketing events and related data points into a unified customer journey, rather than just flat and unreconciled exposure, engagement and financial data. It needs to be able to recognize that disparate events that appear to be happening in different devices owned by the same user (on the user’s desktop, tablet and mobile), even events that appear to be happening in different parts of the same device (mobile web versus in-app) and recognize that these are all the same person.

When marketing intelligence solutions provide a people-based view, it represents a far more accurate picture about how their marketing initiatives are truly driving prospects into customers, and leads to better optimization decisions versus non people-based views.

People-based views require that the customer journey:

1) Represents de-duplicated events. Without a people-based view, different channel systems may lay claim to their own conversion events, leading to significantly over-estimating how many conversions your marketing is actually doing

2) Represents a cross-device view. Media has long worked in conjunction with each other across a users’ different screens. An old adage says that users don’t think in screens or devices, but marketers, due to the difficulty of managing the proprietary complexities of each device, sometimes have to look at their data device-by-device, instead of recognizing the user behind multiple devices.

3) Represents an intra-device view. Just because it’s not easy to stitch together the probabilistic world of cookies for mobile web with the deterministic world of IFAs in mobile app, doesn’t mean it shouldn’t be done. Though mobile web only represents 15% of the mobile minute, it is still a significant presence in the mobile channel, the fastest growing channel. Being able to recognize the same user across mobile web and in-app within the same device is paramount for a people- based view

PII

PII is short for Personally Identifiable Information and generally refers to data that contains personally identifiable information, such as login info, emails, phone numbers, names, social handles, etc… They can be used to link together other identifiers and are a highly reliable, deterministic identifier.

Because it is information that has been entered by the user, it is often very reliable. It can also be used to bridge the online/offline identification challenge. PII need to conform to the growing demands of privacy legislation such as GDPR.

Pixel Tracking

Pixel Tracking is used to signal events to a Tracking Service in the web environments where Javascript is disabled. Fortunately, in most web environments, Javascript IS enabled, so the preferred methodology is to use Javascript Trackers instead of Pixel Trackers. In the in-app world, tracking is usually achieved through API tracking integrations.

Pixel tracking can be used to track any important web events: impression events (when ads are shown to a user), click events (when ads are clicked on, or when the user lands in one of the advertiser’s properties through an outbound link from an ad or a link from another site, a clickthru from an influencer mention or affiliate link, etc..) and conversion events (when the user makes a purchase, or completes a lead gen form, etc…)”

Post-click Conversion Rate

Post-click conversion rates represent a measure of users who have both clicked on an ad AND converted.

The formula is:
( # of converting users who have clicked on an ad / # of impressions )

Post-impression Conversion Rate

Post-impression conversion rates represent a measure of users who have both clicked on an ad AND converted.

The formula is:
( # of converting users who have been exposed to an ad / # of impressions )

Probabilistic Identifier

Probabilistic identifiers do not rely on deterministic identifiers that uniquely identify an individual. Rather, probabilistic identifiers are simply an approximation of a unique user versus a clear delineation of one. Meaning, there is a chance that two probabilistically identified users may collide and be confused for each other because their probabilistic identifier mistakenly conflates them as the same user. Naturally, the chance for collision is highly dependent on the strength of the probabilistic identification mechanism.

Product Attribution

Product Attribution allows users to run their attribution models at the product-level versus the order or conversion-level. Generally, most attribution companies treat conversions as indivisible units when drawing their path-to-conversion. But, in truth, a conversion could actually represent an order that contains multiple products purchased.

Product Attribution allows the marketer to recalculate pathing and crediting at the more granular product-level instead of simply limiting pathing and attribution at the conversion level. This allows the marketer to see the attributed quantity and revenue for any given product, and is tremendously useful in helping advertisers drive product-specific marketing and media strategies

Query

Most people think of search when it comes to a query – the search query is the word or the string of words entered in the search box of a search engine to access some information on the web. The study of search query trends is key to search engine marketing (SEM) optimization.

Retargeting

Retargeting is a lower-funnel technique to target users who have visited the advertiser’s website. In the E-Commerce world, retargeting may get to the granularity of knowing when visitors visited one or more of their product pages, added items to their cart and/or started but did not finish their checkout. Understanding user behavior at this granular level allows retargeters to employ a series of optimization techniques, such as valuing and bidding more for users who are especially deep in the advertiser’s web conversion funnel, or personalizing the ad through dynamic creative.

ROI/ROAS

Return on Investment (ROI) or Return on Ad Spend (ROAS) are often used interchangeably in the media and paid marketing world to represent the value generated by specific marketing initiatives. It can be analyzed at a channel or campaign perspective, although channel managers who are managing a specific channel can use ROI/ROAS to optimize at a more granular level for their channel, such as ad groups and keywords for Paid Search managers, or placements and ads for Display and Video managers.

Rules-based Model

There are various rules-based attribution models such as last touch, first touch, first and last, position-based, time decay and linear. The difference between rules-based and algorithmic models is that rules-based applies the same rules to each and every conversion while algorithmic learns from your data to continually refine a custom data-driven model. Algorithmic takes into account correlations between your media and even external factors like economic conditions and seasonality.

Single-touch Attribution Models

Single Touch Attribution Models are the simplest kind of attribution model, because they allocate 100% of the credit for a particular conversion to a single touchpoint. The most common type of single-touch attribution model is called the Last Click model, which awards 100% of the credit for a conversion to the touchpoint that generated the last click before conversion happened (assuming that the click happened within a particular lookback window).

Statistical Significance

In the simplest of terms, when a statistic is significant, it simply means that you are very sure that the statistic is reliable.There is a lot of math behind this calculation but what you need to understand is the “p-value” which represents the probability that random chance could explain the result. In general, a 5% or lower p-value is considered to be statistically significant.

Subway Graph

A subway graph visually shows the marketing touch points along a conversion path according to the “days before conversion” that the marketing touchpoint occurred.

Success Event

A success event is an event within a website or an app which an advertiser decides they want their website/app visitors to do. These can be revenue or lead-generating events such as successful checkouts, or completion of a lead-gen event, or noteworthy intermediary events, such as the creation of a new account, adding items to the shopping cart, or first starting with a lead gen form.

Time Decay Model

Time decay models reward the media touchpoint closest to conversion most and the others receive less credit the earlier they are in the path. Time decay models reward path position regardless of the relative effectiveness of each of the channels in the customer journey. Just like most rules-based models, they ignore external factors.

Note that events may happen beyond a particular lookback window — and these will not receive any credit. For example, if the marketer has a 30-day lookback window in the above example, and a Paid Social event actually happened 31 days before the conversion event — then that Paid Social event does not receive any of the credit because it occurred before the 30-day lookback window.

Trafficking

Trafficking refers to the operational process used to set up and launch an ad campaign. Trafficking processes exist on both the demand-side and the supply-side. On the demand-side, it usually involves ad operations personnel on the media agency side, executing campaign workflows on their 3rd party ad server or demand side platforms.

On the supply-side, it usually involves ad operations personnel on the publisher side, executing complementary campaign workflows on their publisher-side ad server or supply-side platforms. Because so much of attribution relies on firing impression, click and conversion trackers through Javascript or Pixel trackers — these are usually set up and implemented as part of the trafficking process by ad operations people on the demand-side.

TV Attribution

TV Attribution Models allow marketers to understand the impact of various dimensions of their TV advertising, such as the TV Ad Network (ABC, Fox, CBS, NBC, …), TV Program and TV Ad Airing Spot, on their website traffic, online sales and other digital activities. It has long been accepted by marketers that airing commercials on legacy TV can often lead to conversions online — but due to the non-addressable nature of TV Advertising, the impact is hard to accurately quantify.

With TV Attribution Models, marketers can collect TV data in aggregate (GRP), and analyze their incremental impact on driving conversions in the online world.

Unique Contribution/Revenue

When assembling a path-to-conversion, it is quite possible to find a number of paths that consist of one marketing touchpoint followed by a conversion. It is easy to conclude that, if that marketing event had NOT happened, then the conversion event may not have happened at all. We therefore measure unique contribution or unique revenue based on the amount of conversions or revenue delivered by a particular touchpoint where it is present in a single-touchpoint conversion path.

Unique contribution represents the number of conversions driven by a channel or media investment that you would not have received if it was not for that media investment’s sole contribution.

Unique revenue represents sales revenue driven by a channel or media investment that you would not have received if it was not for that media investment’s sole contribution.

With the complex channel overlap of today’s marketing environment, you want to measure each media’s unique contribution and unique revenue so you know where you’re getting the most bang for your buck.

For example, if a marketer, by analyzing their conversion paths, find that 50 conversion paths looked like this: Paid Search Click –> Conversion, delivering about $1,000 in revenue. Then the Unique Contribution of Paid Search would be those 50 conversions, and the Unique Revenue would be $1,000.

View-through Conversion

View-through conversions represents instances where an audience was exposed to a particular ad (in whatever format — display, video or other), but did not click on the unit to go to the advertiser’s website. However, the user may have registered the exposure to the advertiser’s message in their head. They may go to the advertiser’s site at some point in the near future and take the desired conversion action. When the exposure event occurs within the lookback window duration of the conversion event, then we say that the user has had a “view-through conversion”.

Walled Gardens

Walled gardens represent areas in the digital media space where paid media can be purchased, but limited or no tracking data can be extracted at the event level. Most walled gardens will certainly ingest advertiser data in order to optimize campaign performance within the walls of their walled garden, but often do not provide granular (or any) data back to advertiser to allow them to optimize throughout their initiative (across both walled garden and other publishers). The social channels are probably the most famous of the Walled Gardens, including Google YouTube, Facebook, Instagram, Twitter and others.

Walled gardens present a particularly large and existential challenge for marketers and other players within the digital media space since most media dollars are actually captured by the walled gardens

Yield

It’s all about the results. It can take a lot of time and effort to build a statistically-significant, accurate attribution model but don’t lose sight of the ROI. Keep your investment balanced with the potential savings or increase in revenue. You wouldn’t spend $100,000 to save $10,000 now would you? But if you have a large revenue stream, a 1% improvement in close rate can easily pay for your investment in attribution.

Fraud Protection

Ad Blocking

Prevents ads from showing up in brand unsafe environments where offensive content has been detected.

Ad Fraud

Actions taken to siphon money from the digital advertising ecosystem without delivering valid audience engagement in return.

Ad Injection

Placement fraud caused by a malicious publisher who owns a browser extension, uses it to inject ad impressions when a user visits certain premium sites, and enjoys premium CPMs for these hijacked impressions.

Ads.cert

An Interactive Advertising Bureau protocol augmenting ads.txt that uses cryptographically signed bid requests (a technology similar to blockchain) to authenticate inventory and record its path.

Ads.txt

An Interactive Advertising Bureau text file that lists all approved traffic partners, intended to mitigate inventory sales by unauthorized traffic vendors.

Advanced Parameter Spoofing

Distributed fraud technique combining device ID spoofing and bundle ID spoofing to make it look like many mobile devices are sending requests across many different publishers.

API

Application Programming Interface that has a set of rules, routines and protocols that are used for building software with graphical user interface components. APIs allow businesses to access data in an automated fashion.

ATF / BTF

Above The Fold, meaning the ad is viewable upon opening the browser without the user having to scroll. Ads placed lower that do require the user to scroll are Below The Fold.

Attribution Fraud

Occurs when a publisher games an advertiser’s attribution model (by way of click injection, cookie stuffing, etc.) to claim undue credit for driving a payable event.

Automated Traffic Detection

Sophisticated algorithms that can accurately identify traffic from botnets, hijacked devices, malicious script injection and other automated means.

Behavioral and Network Analysis

Techniques that compare traffic characteristics like IP address and ISP info to a variety of fraud databases that are built off of historical fraud activity to detect invalid traffic through list-based filtration mechanisms.

Botnet

A network of corrupted devices manipulated within a command and control architecture to execute malicious instructions and accelerate the velocity of fraudulent activity.

Brand Safety

Verification that the content against which an ad is shown satisfies the advertiser’s threshold for brand integrity (no adults only content, violence, political extremism, etc.).

Brand Safety Categories

There are a standard 12 categories that the advertising industry and marketers consider brand unsafe: obscenity, military conflict, illegal drugs, adult content, firearms, crime, piracy, death/violence, hate speech, terrorism, spam/harmful sites, tobacco.

Browser and Device Analysis

Looks at the remnant clues such as attributes around the browser session for traces of malware, anomalous on-page behavior, faked domains and app ids, deceptive placement handling by malicious publishers and mobile botnets that convincingly, but imperfectly, mimic legitimate traffic.

Bundle ID

A bundle ID is a mobile app’s identifier, much like a domain identifies a mobile website.

Bundle ID Spoofing

Occurs when bad actors misrepresent their inventory’s bundle ID to buyers so that it appears to be associated with a premium app (and a higher CPM), when it’s coming from a dud, low quality traffic source instead.

Click Fraud

Clicks feigned or spoofed to fool advertiser KPIs, defraud CPC campaigns, or steal attribution for a payable event.

Contextual Classification

Categorization of the page based on some standard (such as the IAB Tech Lab Content Taxonomy) or custom taxonomy.

Conversion Fraud

Fraud techniques engineered to exploit performance marketers’ CPA spend by faking or spoofing conversion events.

CPA

CPA, or Cost per Acquisition or Cost per Action, is a metric that is tracked in many direct response and performance campaigns, particularly in verticals that are tracking user conversions — whether that conversion represents a sale or a form submission, depending on what the advertiser decides. This is why it’s also often referred to as Cost per Conversion.

Some marketers will include “clicks” as a viable action — in those cases, the calculation is essentially equivalent to a CPC (Cost per Click).

A related concept is eCPA, or Effective Cost per Acquisition. This is often calculated by advertisers who pay on another cost basis such as CPM or CPC, but wish to convert it to a Cost per Acquisition in order to optimize their media buying to some Cost per Acquisition target.

It is calculated as follows:
( sum of the relevant media costs / total # of acquisitions )

So, if a display campaign spent $1,000, and garnered 20 conversions, then the the eCPA = $1000 / 20 = $50

CPC

CPC, or Cost per Click, is a metric that is tracked in many branding, direct response and performance campaigns across any vertical. A click often refers to clickthru on an ad that directs them to the advertiser’s website, though many rich media campaigns may count a click on the ad that triggers some engagement (for instance, the user clicks on the ad to start playing a video, or playing a mini-game on the ad unit); in the rich media situation, this can also be referred to as Cost per Engagement (CPE).

A related concept is eCPC, or Effective Cost per Click. This is often calculated by advertisers who pay on another cost basis such as CPM, but wish to convert it to a Cost per Click in order to optimize their media buying to some Cost per Click target.

It is calculated as follows:
( sum of the relevant media costs / total # of clicks )

So, if a display campaign spent $5,000, and garnered 250 clicks, then the the eCPC = $5000 / 250 = $20

CPCV

CPCV, or Cost per Completed View, is a metric that is tracked in many video-based campaign across any vertical. A completed view is often triggered once the viewer of the video reaches the end of the video, though due to the idiosyncracies of many video player platforms, it may be triggered when <100% of the video is viewed.

A related concept is eCPCV, or Effective Cost per Completed View. This is often calculated by advertisers who pay on another cost basis such as CPM, but wish to convert it to a Cost per Completed View in order to optimize their media buying to some Cost per Completed View target.

It is calculated as follows:
( sum of the relevant media costs / total # of completed views )

So, if a display campaign spent $10,000, and garnered 200 completed views, then the the eCPC = $10000 / 200 = $50

CPI

Cost per Install, or the price an advertiser pays for each install event in which a user downloads their app.

CPL

CPL, or Cost per Lead, is essentially a subset of CPA, or Cost per Acquisition, specifically used by verticals that require the audience to complete a form with their contact info. For instance, in the insurance vertical, an interested user may have to enter their personal info in order to request an insurance quote or have a broker contact them.

CPM

CPM, or Cost per Mille, or Cost per thousand impressions (mille is the latin word for thousand) is one of the most common ways to purchase advertising today. Though it is used across many branding and direct response campaigns, it is particularly suited for verticals and campaigns intended to raise awareness.

For instance, if the CPM is priced at $2, and you wish to deliver 1,000,000 impressions, then the cost of the campaign is

(Total # of impressions / 1000) * $2
(1,000,000 impressions / 1000) * $2 = $2,000

Many advertisers running direct response or performance campaigns who pay for media based on CPM will often calculate an eCPC or eCPA as a KPI in order to track their success and to optimize toward lowering that KPI.

CPS

Cost per Sale, or the price an advertiser pays for each referral that ends in a sale. Essentially a subset of CPA, specifically used by verticals that require the audience to complete a sale.

CPvM

CPvM, or Cost per Viewable Impression, is a metric that is tracked in many campaign across any vertical. A viewable impression is generally measured based on IAB standards — that is, for a display ad, 50% of the ad appears on the screen for at least 1 second, and for a video ad, 50% of the ad appears on the screen for at least 2 seconds.

Since most display or video campaigns today are paid in CPM rather than CPvM, CPvM is usually calculated.

It is calculated as follows:
( sum of the relevant media costs / total # of viewable impressions )

So, if a display campaign spent $2,000, and garnered 200 viewable impressions, then the the CPvM = $2000 / 200 = $10″

Creative Fraud

Creative fraud, or malvertising, is when bad actors inject malicious code in ads in order to cause some type of fraudulent activity, such as generating fake clicks or additional ad calls.

Data Center

A large network of computer servers typically used by bad actors to remotely execute various ad fraud techniques.

Data Mining, AI, and Machine Learning

Data mining techniques can be used to surface anomalous patterns that are found in automated botnet traffic, device farms, emulators and other perfidious fraud tactics. Naturally, any machine learning algorithm works best when monitored, trained, calibrated, and supervised by data scientists with deep fraud expertise.

Device Farms

User fraud technique in which agencies and performance partners who are asked by advertisers to “drive performance” for their ad campaigns hire hundreds of low-cost workers in developing countries to browse fake or real websites and “click” on the advertiser’s ad or “install” and open the advertiser’s app.

Device Hijacking

Occurs when a user downloads a malicious app on their smartphone or tablet, often from a trusted source like the App or Play Store. The app hijacks the device to inflate traffic numbers and steal ad dollars by rapidly loading hidden ads and emulating human behavior. This happens in the background, even when the app is minimized or the device is sleeping.

Device ID

A device ID is the unique identifier for a particular mobile device.

Device ID Reset Marathons

Device ID reset marathons are able to achieve exploitation on a mass scale when device farms execute events (like clicks or installs) and are then reset, each device obtaining a new device ID, and the process runs from the beginning again.

Device ID Spoofing

Fraud operators have started manipulating device ID information (misreporting the device ID associated with their inventory) in order to simulate more normal-looking browsing patterns and fool increasingly sensitive detection methodologies.

Device Manipulation Recognition

Detection methodology that looks for anomalies within traffic to identify instances of device manipulation, where a fraudulent user or bot uses operating system and browser manipulation to spoof their real identity and simulate traffic.

Display Advertising

Commonly understood to mean “banner ad”, but formats have evolved to include rich media ads. Display ads can be static or animated and can remain within their placement on the publisher’s page or expand out of it. Typically tag based.

Domain Cloaking

Occurs when a malicious publisher serves ads in a series of nested iFrames and attempts to cover their tracks by falsely representing one of the intermediate iFrames as originating from a premium publisher.

Domain Spoofing

Occurs when bad actors build malicious sites and sell their inventory to legitimate resellers (networks and exchanges) at a premium by misrepresenting their actual domains and masquerading as premium publishers.

Engagement Metrics

Measure a user’s engagement with an ad beyond the minimum viewable impression standards. These metrics may include custom viewability measurement (such as the duration a video ad was played) and interactivity measurement (such as direct mouse interactions with a rich media display ad).

Fraud Intelligence Database

A fraud intelligence database must be dynamic to capture momentarily current lists of fraudulent IPs and forensic reputation data. This catches the bad actors in digital advertising that tend to use the same tactics to commit fraudulent activity repetitively.

Full-Funnel Detection

A fraud database that spans impression, click, install, and conversion events. Evaluating traffic for fraud across the entire funnel enables sharper detection at each point of the conversion path and allows us to offer unique capabilities- like install attribution fraud detection.

Geometric Analysis

A method of data collection and analysis to produce viewability measurement. Commonly utilizes a JS API to measure the coordinates of the ad unit on the page respective to the browser viewport. If the coordinates are outside the browser viewport, the ad is not viewable. When ads are served within unfriendly iFrames, using only the geometrical approach can produce only a small share of measurable impressions, so supplementary viewability measurement methodologies may be used.

Ghost Site

Sites designed to receive bot traffic, and not meant for humans.

GIVT

General Invalid Traffic (GIVT) is traffic that can be easily identified as invalid through routine, list and parameter-based filtration techniques.

Hidden Ads

Is placement fraud caused by a malicious publisher placing ads behind other elements on the page, stuffing ads into nonviewable 1×1 pixels, or loading ads off-screen.

IAB

The Interactive Advertising Bureau is a the standardizing body in the digital advertising ecosystem, developing industry guidelines, conducting research, and providing legal support.

iFrame

An HTML document embedded in a publisher’s site, used to enable third party ad exchanges and networks to insert ads without compromising that publisher’s security or quality.

Image Pixel

Establishes a browser to server connection allowing IP, UA, and other data points to be passed in the HTTP header.

Impression Fraud

Fraud techniques engineered to exploit advertisers’ CPM spend by faking or spoofing impression events.

In-Stream Video

Video advertising that generally shows up before, in the middle of, or after other primary content video stream.

Inappropriate Domains

Domains that are unbefitting for ads and would compromise brand image. Examples include pages that feature terrorist sentiments or pornographic elements.

Incentivized Traffic

Traffic from users that were offered incentives (like an in-app reward) for clicking through to another other sites. This constitutes user level fraud when supply side players misreport it as organic traffic.

Influencer Fraud

Occurs when a paid influencer uses an illegitimately inflated follower count to ask higher rates of an advertiser for engaging their audience with brand sponsored content.

Install Attribution Fraud

Certain partners cheat performance marketers’ CPI campaigns by faking or stealing credit for the actions that led to a user installation.

Install Fraud

Fraud techniques engineered to exploit performance marketers’ CPI spend by faking or spoofing payable app install events.

Intersection Object

A viewability measurement technique specific to Chrome; creates a shape containing only those areas where all components overlap (for example, an ad container). A point is part of an intersection if it is inside both objects (the ad and the ad container).

Invalid Traffic

Traffic that does not legitimately fulfill the agreed upon user and placement specifications according to which the ad or audience engagement was purchased.

Javascript Tag

Gathers information directly from the page, enabling both server-side and session-side analysis. A JS tag integration is necessary for viewability and other verification measurements.

Keyword List

A list of words that a brand does not want adjacent to their ads.

Legitimate Bots

There’s a significant number of “good bots” that crawl the web and participate in healthy internet function.

Location Spoofing

User level fraud technique in which malicious apps report fake location data (latitude, longitude) to media buyers in order to collect high payouts based on a (falsified) premium location.

Malicious App

A bad behaving publisher that siphons money from the adtech ecosystem by perpetrating various fraudulent actions such as aggressively calling non-viewable ads and running ads in the background of device when it is not even in use.

Malicious Bot

A bot designed to perpetrate ad fraud.

Malicious SDK

A software development kit into which a malware author has written malicious code, which a developer then embeds into its app. Once embedded, the malicious SDK can commit various ad fraud techniques from within the app itself.

Malware

Software that is intended to corrupt devices and device systems. Malware can be used to perpetrate ad fraud by hijacking devices, creatives, browsers, apps, and SDKs.

Measurability rate

The rate at which impressions can be measured for viewability. Measurability rates vary by viewability measurement techniques, technologies, and vendors.

Measurable impressions

Indicates the number of impressions for which viewability measurement was possible. Factors that impede viewability measurement include unfriendly iFrames, which prevent viewability measurement vendors from accessing information about the iFrame’s parent site.

Mobile Advertising

In the mobile space, ads can appear on either mobile web or in-app. Mobile is often used to refer to both smartphone and tablet experiences.

MRAID

Mobile Rich Media Ad Interface Definitions is the IAB’s standardization of one common API for in-app rich media ads, supported by multiple SDKs. MRAID is essentially the translator that reconciles the app’s and the ad’s languages. It has been commonly used beyond its intended purpose to measure in-app ad viewability.

MRC Accreditation

The Media Ratings Council standardizes excellent media measurement across vendors and performs annual external audits of rating service operations to determine whether a rating service meets their rigorous standards.

Native Advertising

Has a wide definition, but includes ads that seamlessly blend into the look-and-feel, styling parameters, and editorial content of a publisher site in order to minimize obtrusiveness.

NHT

Non-human traffic is automated invalid traffic. NHT compromises any campaign optimized on human engagement and distorts performance metrics.

OMID

The Open Measurement Interface Definition API allows third-party verification vendors to collect viewability measurement signals specific to the in-app environment, supplanting the need for apps to implement each third party vendor’s SDK.

OTS

Opportunity To Be Seen benchmarks whether an ad was served under conditions that meant it had the potential to be seen by a user, agnostic to whether the user actually viewed it.

Out-Stream Video

Video advertising that acts as a fusion of rich media and in-stream formats, served against non-video content.

Packet Sniffing

In-app fraud detection technique that includes listening to ad requests from an app, loading any ads returned, and recording on and off-screen activity to compare what is showing on screen to the actual ads loaded by the app. The sniffer does not use a proxy so the app will not know that its network activity is being monitored.

Performance Marketing

Marketing programs in which the advertiser pays their media partners directly for some desired action like a sale, lead or click.

Placement Level Fraud

Ad fraud technique in which the user is real, but the ad placement is fake or manipulated.

Placement Verification

Uncovers domain/app masking and spoofing by analyzing discrepancies between referring sources passed through headers, exposing the top level environment in which the user is actually receiving the ad.

Post-bid Fraud Detection

Analyzes the user and placement of an impression after the ad impression is delivered. It can be applied to both premium buys (when advertisers/agencies deliver ads directly to publishers) and programmatic buys (when advertisers/agencies deliver ads via a DSP). Post-bid verification can also measure the viewability of an ad.

Pre-bid Filtering

Evaluates a placement for brand safety, contextual appropriateness, and ad fraud before a bid is placed. A bid is only placed if verification conditions determined by the advertiser are met.

Pre-bid Fraud Detection

Is a solution to use under a variety of contexts before the bid request to make a media buying or monetization decision based on that risk assessment.

Proxy Piercing

In cases where a user is is browsing via a proxy (like a sophisticated botnet tunneling traffic through multiple devices), proxy piercing techniques can analyze the ad request IP and the end user IP to tease out unacceptable mismatches, in part by recognizing correlations between IP mismatches and other types of fraud.

Reason Code

Reason codes provide event-level classification of the traffic characteristics that tripped fraud risk thresholds.

Retargeting Fraud

Bots acquire retargeting cookies and mimic human browsing behavior in order to collect on the premium CPMs typically associated with retargeting campaigns. Advertisers suffer for investing in audiences that provide no engagement value and relying on distorted campaign performance metrics.

Risk Scores and Ranges

A 0-100 scale provides a simple fraud risk metric – the higher the score, the higher the likelihood of that traffic having fraudulent characteristics.

This scale is broken down into risk ranges:

< 3% (Premium): high quality traffic. Invalid traffic activity may be due to false positives.
3-6% (Low): invalid traffic is not likely. Some invalid traffic may occur at the event level.
6-10% (Moderate): some invalid traffic is likely, concentrated at the event level. Traffic mixing between valid and invalid sources is likely.
10-20% (Elevated): invalid traffic is likely, some concentrated at the event level. Traffic mixing between valid and invalid traffic sources is highly likely.
20-30% (High): Invalid traffic activity is likely to affect the entire source. Traffic mixing between valid and invalid traffic sources is highly likely.
30-100% (Critical): It is not recommended to buy from sources with invalid traffic levels within this threshold.

ROI/ROAS

Return on Investment (ROI) or Return on Ad Spend (ROAS) are often used interchangeably in the media and paid marketing world to represent the value generated by specific marketing initiatives. It can be analyzed at a channel or campaign perspective, although channel managers who are managing a specific channel can use ROI/ROAS to optimize at a more granular level for their channel, such as ad groups and keywords for Paid Search managers, or placements and ads for Display and Video managers.

SDK

A Software Development Kit is a grouping of software that’s used to develop applications respective to a particular device or operating system.

SIVT

Sophisticated Invalid Traffic (SIVT) is inclusive of complex, advanced fraud types and cannot be easily identified through list or parameter-based filtration. Instead, it takes advanced analytics, multipoint corroboration, and human intervention to uncover and suppress.

Social Advertising

Social ads often appear in walled gardens such as Facebook, Twitter, Instagram, Snap, YouTube and more. Most of these ecosystems don’t utilize the standard IAB-defined mechanisms that are common in display, video and mobile.

Sourced Traffic

Traffic acquired from third parties to augment a publisher’s audience.

Stacked Ads

Is placement fraud caused by a malicious publisher stacking multiple ads in nested iframes and monetizing the entire stack on a CPM basis, when only the top ad was viewable.

TAG Accreditation

The Trustworthy Accountability Group awards seals such as “Certified Against Piracy” and “Certified Against Fraud” to buyers, sellers, and intermediaries in the digital supply chain who meet rigorous traffic verification requirements.

Tunneling

Some of the most pernicious fraud techniques include tunneling through VPNs, such as botnets operating through proxies. A lot of “mobile web” fraud is really desktop GIVT coming from server farms tunneling through proxies to infected devices.

Unfriendly iFrame

Does not allow third party participants like ad exchanges or verification vendors to access information about the publisher site in which the iFrame is embedded. This poses a significant challenge to viewability measurement.

User Level Fraud

Ad fraud technique in which the user is fake, and the ad placement could be real or fake/manipulated.

vCPM

Viewable Cost per Mille, or the cost per 1,000 delivered viewable ad impressions. Calculated only after the impressions have been verified as viewable.

Verification

In the ad tech ecosystem, verification has come to include fraud detection, viewability measurement, brand safety assurance, and contextual categorization.

Video Advertising

Refers to ads that leverage sight, sound, and motion to communicate the advertiser’s message. Includes “in-stream video” and “out-stream video”.

Viewability

Analyzes whether a delivered ad has truly been seen by the user. The IAB dictates that an ad is viewable if 50% of its pixels are visible on the user’s screen for at least 1 second if display and at least 2 seconds if video.

Viewability Fraud

Bad actors can artificially inflate their viewable ad count by using techniques like placing ads in 1×1 containers and loading ads on top of each other.

Viewable Area

Is the portion of an ad that could be seen by a human user, expressed as a percentage.

Viewport

The area of a website that the user sees immediately upon opening a page, without scrolling up or down.

Viewtime

The duration of time an ad meets viewable area criteria.

VPAID

Video Player Ad-Serving Interface Definition is a script first introduced by the IAB to enable interactive elements in video ads. It’s important for its video viewability measurement benefits.

Whitelist / Blacklist

a whitelist defines the domain/apps on which ads exclusively may run. Conversely, a blacklist defines the domains/apps on which ads should not be placed.