Algorithmic multi-touch attribution for retail media
Causal, algorithmic MTA that estimates the incremental contribution of each paid touchpoint—so advertisers optimize beyond last-touch reporting.
Segment-level
Incremental impact beyond last-touch reporting
Challenge
Last-touch reporting could not reflect multi-channel journeys. With rich first-party data and identifiable customers, the media division needed measurement that captured incremental contribution of each paid touchpoint—not just activity.
What we did
FocusKPI built an algorithmic multi-touch attribution system using causal inference, controlling for external factors while ML and sequential models captured cross-channel interactions and behavior. The solution integrated into the media platform for ongoing optimization and reporting.
Results
Advertisers received a more accurate, defensible view of channel performance and optimized spend with greater confidence—strengthening the media division’s measurement differentiation.
“This fundamentally set us apart from other media networks—we can now show impact at the customer segment level, not just activity.”
Why it worked
Complex causal modeling was translated into actionable platform insights focused on incremental sales—not vanity reporting.
Discuss a similar engagement
We typically start with a scoped proof of concept before production deployment.