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.
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.
