Marketing Mix Modeling
Also called MMM
By the AdFlint research team · Last reviewed July 2026
Estimates each channel's contribution by fitting aggregate sales against spend, seasonality, pricing, and external factors over time, without user-level data.
A regression over historical weekly or monthly data separates the effect of each media channel from seasonality, promotions, and macro noise, and can express diminishing returns and carryover. It appeals because it needs no cookies or identifiers and covers offline media. It demands years of clean history, cannot guide day-to-day bidding, and is correlational, so standard practice is to calibrate the model against real incrementality experiments.
Marketing Mix Modeling compared with
The settings this gets confused with, and how to tell them apart.
- Marketing Mix Modeling vs A/B Testing
- Marketing Mix Modeling vs Incrementality Testing
- Marketing Mix Modeling vs Conversion Lift Tests
- Marketing Mix Modeling vs Brand Lift Tests
- Marketing Mix Modeling vs Geo Testing
- Marketing Mix Modeling vs Holdout Testing
- Marketing Mix Modeling vs Multi-Touch Attribution
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