MMM

Media Mix Modeling is a statistical technique that uses historical spend and outcome data across all channels to estimate each channel's contribution to overall results, independent of individual-level tracking.

MMM's biggest structural advantage is that it doesn't rely on cookies, device IDs, or individual-level tracking at all — it works at the aggregate level (total weekly spend per channel vs. total weekly sales), which makes it resilient to the privacy-driven tracking degradation that has hurt platform attribution since iOS 14.5. This is a major reason MMM has come back into fashion since 2021 after being seen as a somewhat old-fashioned, TV-era technique.

MMM's tradeoffs run the other way from platform attribution: it typically needs a long history of data (often a year or more) to produce reliable estimates, is usually refreshed periodically (monthly or quarterly) rather than in real time, and works best at aggregate channel-level decisions rather than individual-campaign optimization.