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

  1. Breaking out the below cohorts against each marketing touchpoint
    1. Users that were exposed to marketing and convert
    2. Users that were exposed to marketing and DIDN’T convert
    3. Users who convert without any marketing touchpoints
  2. 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
  3. 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.

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