Calibrated Attribution
Align your MMM models with day-to-day attribution. Correct last-touch bias and recover the true contribution of each digital campaign.
The problem with traditional digital attribution
Traditional digital attribution (last-click, last-touch) suffers from fundamental biases. It attributes 100% of the conversion to the last touchpoint, ignoring the entire journey that led the consumer to purchase. "Bottom of funnel" channels like branded search or retargeting are systematically overvalued, while awareness channels (TV, video, social) are underestimated.
This bias leads to poor budget decisions: over-allocation to retargeting channels and under-investment in channels that actually generate demand. The result? Declining overall ROI despite seemingly strong attribution metrics.
How does Calibrated Attribution work?
mediaROI's Calibrated Attribution combines the best of both worlds: the day-to-day granularity of digital attribution and the statistical robustness of Marketing Mix Modeling (MMM).
The principle is simple: MMM results act as a calibration layer for day-to-day attribution. For example, if MMM shows that Branded Search represents 15% of real contribution, rather than the 40% claimed by last-click attribution, calibrated attribution redistributes conversions accordingly every day.
Macro view: real contribution by channel
Daily calibrated attribution designed to reduce bias
Recalibrated cross-platform attribution
mediaROI's calibrated attribution is cross-platform: it covers all your digital channels, including Google, Meta, TikTok, and Amazon, and aligns them with the reality measured by MMM. You get a unified, reliable view of campaign performance every day.
Daily
Attribution data updated every day, not once per quarter.
Cross-platform
Reliable comparison across Google, Meta, TikTok, Amazon and all your channels.
Bias-corrected
Reduce retargeting over-crediting and restore a fairer read on lower-funnel levers.
Discover the platform
30 minutes to walk through a complete model and ask your questions