Short answer
Marketing Mix Modelling (MMM) is a statistical technique that decomposes sales, revenue or profit into the incremental contribution of every marketing channel and non-marketing driver, so you can measure ROI and reallocate budget with evidence.
MMM fits a regression, usually Bayesian in 2026, with a KPI (sales, revenue, profit) on the left and every plausible driver on the right: media spend by channel, price, distribution, promotions, weather, macro, competitor activity. The model separates a slow base from the incremental contribution of each driver. Divide contribution by cost and you have channel ROI.
Platform reporting and last-click attribution double count, ignore offline media, and cannot see cannibalisation between channels. MMM is the only method that measures TV, out-of-home, sponsorship and brand alongside digital in one consistent framework: and the only method a CFO will sign a budget off against.
Weekly data, two to three years of history, Bayesian priors informed by geo-experiments and lift tests, adstock and saturation modelled per channel, and monthly refreshes feeding a scenario tool. If your MMM is annual, uncalibrated and delivered as a slide deck, it is a legacy MMM: not a decision system.
MMM does not tell you which creative won, which audience clicked or which keyword converted. Pair it with incrementality tests, brand tracking and platform diagnostics for the tactical layer.
Yes. Marketing mix modelling, media mix modelling and market mix modelling all refer to the same technique.
Ideally 2-3 years of weekly data across all channels and a KPI, plus context on price, distribution and promotions.
Bayesian MMM, calibrated with experiments, refreshed monthly, delivered as a decision system.
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