Attribution modeling is, at its core, an analysis of the co-occurrence of events. This make intuitive sense – if each purchase was only affected by one channel, there would be nothing to attribute! From your own every day experience, you’ve been exposed to emails, catalogs, display ads, social media, tv… with each playing a different role in influencing your purchases. What was the magic combination? What combinations were lackluster?
Measuring attribution at the ID-level exposes information that channel-level analysis will never see. That has always been our major hang-up regarding Marketing Mix models (MMM). MMM models were state of the art when they were invented. These models were pioneered by CPG companies as soon as they gained access to syndicated bar code scanner data. The techniques correlate response to signals of increases & decreases in marketing. However, the major shortcoming of these models is the underlying data.