Why MMM matters
Click-based attribution went blind as privacy rules and platform walls cut tracking, and MMM returned from the enterprise attic: it reads outcomes from the top down, capturing what pixels can’t see, offline effects, halo between channels, and diminishing returns per dollar. For heads allocating serious budgets, it’s the counterweight to platform-reported numbers grading their own homework.
What MMM estimates
- Channel contributionSales attributable to each line of spend
- Diminishing returnsWhere the next dollar stops paying
- Base versus incrementalWhat sells without marketing at all
- Scenario planningPredicted outcomes of budget shifts
Questions
Does MMM make sense below enterprise scale?
Increasingly: open-source frameworks and vendor tools brought it to mid-size budgets, with the honest requirements being enough spend history and variation to model. Below that, disciplined incrementality tests answer the same questions more directly.
MMM vs attribution: which to trust?
Different instruments: attribution is fast and granular but tracking-limited; MMM is slow and strategic but sees the whole. Mature teams triangulate, MMM for allocation, experiments for causality, attribution for day-to-day steering.