Marketing Attribution

Attribution models assign customers and sales to channels to provide more visibility into marketing performance.

These models take all user sessions into account when calculating attribution. To illustrate: if Jane (a fictitious customer of Acme) discovered acme.com first via a blog post, then visited it a second time via an ad, and a third time via a newsletter hyperlink, all of those three channels would receive some credit for Jane’s purchases.

Here are some of the design stages that we followed to get to the final models that are built on Chord's data platform:

User Stitching User stitching is the process of assigning a single anonymous or user ID to all of the events recorded for a given user. This can be increasingly challenging in a world where users navigate websites from various devices and over many sessions before and after each purchase.

User stitching is not required for marketing attribution. You can always partition sessions by anonymous_id, but partitioning by user_id provides a more accurate attribution and allows for a better view of users across various devices and sessions.



Channel Mapping Next, we assigned a referring channel category to each session. We extracted sources and mediums from UTM tags. For sessions with no UTM tags, we inferred the source and medium from the referring url whenever possible. Then mapping source-medium pairs with channels, we were able to assign all sessions to one of the following categories:

These high-level channel categories can be drilled into to uncover attribution at a finer level of granularity. Chord recommends exploring this data from the "Marketing Attribution" explore and adding the following fields:

Adding all of the above fields will show how the combination of these fields determines the Session Attribution Channel and where there may be an opportunity to define or redefine mappings. There's also the option to drill down into each of the above fields and additional session fields more granularly, such as the First Page (or Landing Page) referrer.