Short answer
MMM (Marketing Mix Modelling) uses aggregate weekly data and statistical models to measure the incremental impact of every channel, including offline. MTA (Multi-Touch Attribution) uses user-level click and impression data to distribute credit across digital touchpoints. They answer different questions and are best used together.
MMM is top-down and causal - it models total sales as a function of total marketing and business drivers. MTA is bottom-up and correlational - it stitches together user journeys and applies a credit rule (last-click, linear, time-decay, data-driven). MMM measures incrementality; MTA measures presence in the path.
MTA cannot see TV, out-of-home, radio, sponsorship, PR or word of mouth. Post-iOS 14 and with third-party cookies deprecating, MTA cannot even see the full digital path reliably. It over-credits the channels closest to conversion (search, retargeting) and under-credits upper-funnel media.
MMM cannot tell you which creative, keyword or audience won. It runs at weekly, channel-level granularity. For in-flight optimisation of a Google Ads account or a Meta creative rotation, MTA and platform diagnostics are faster.
Modern measurement stacks use MMM as the strategic source of truth (budget setting, channel ROI, scenario planning) and MTA plus incrementality tests for tactical optimisation. Geo-experiments and platform lift studies calibrate the MMM; the MMM in turn reality-checks the MTA. Neither alone is sufficient.
Bayesian MMM, calibrated with experiments, refreshed monthly, delivered as a decision system.
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