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 the order of the marketing touchpoint on a user's path to conversion.
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 only your data. It assigns fractional credit to all marketing touchpoints a user is exposed to, relative to their impact.
Each touchpoint (each combination of tier 1-5 values in your reporting) receives its own unique weight, which is determined by
- Breaking out the below cohorts against each marketing touchpoint
- 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
- Applying a logistic regression model against the data sets, which results in weights against each touchpoint representing the effectiveness in driving a user to convert
- Applying this weight as a relative value on the user's path to conversion. For example, a user's path to conversion might contain 2 marketing touchpoints. Touchpoint A has a weight of .05 and Touchpoint B has a weight of .025. When applied to a single path to conversion, Touchpoint A would receive 2x more credit than touchpoint B because the weight is 2x higher.
Overall Impact
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.