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.
