Multi-Touch Attribution (MTA) Model overview
What is Multi-Touch Attribution (MTA)?
Multi-touch attribution enables you to see the true impact of each placement in driving a user to convert, regardless of what number touchpoint it is.
This ensures that mid-funnel and upper-funnel placements are receiving the necessary credit.
In contrast, the traditional last-touch model assigns 100% of the credit to the last marketing touchpoint, under attributing all other touchpoints.
MTA Model Methodology
Rockerbox MTA is custom-built off your data. It assigns fractional credit to all marketing touchpoints a user is exposed to, relative to their impact.
Rockerbox builds your MTA model from three groups of data:
- Users that were exposed to marketing and convert
- Users that were exposed to marketing and DIDN’T convert
- Users who convert without any marketing touchpoints
Rockerbox applies a logistic regression model against the data sets, which results in weights against each touchpoint representing the effectiveness in driving a user to convert
Using the MTA model will allow you to identify placements and tactics you may have been over or under-investing in. This will unlock opportunities to allocate more spend or increase bids for placements.