What is MMM vs MTA?
Marketing mix modeling (MMM) uses statistics on aggregated historical data, such as weekly spend by channel, sales, prices and seasonality, to estimate how much each channel contributed. Multi-touch attribution (MTA) tracks individual users' ad exposures and clicks before a conversion and divides credit among them. MMM is privacy-friendly and covers offline media; MTA is granular but increasingly limited by tracking restrictions.
Marketing mix modeling dates back decades in consumer goods. It sees TV, radio, digital and even promotions, but needs a lot of history and gives channel-level rather than ad-level answers. Open-source tools such as Meta's Robyn and Google's Meridian have made it more accessible.
Multi-touch attribution promised precise, user-level credit, improving on last-click attribution, but signal loss from cookie blocking and Apple's App Tracking Transparency weakened it. Many marketers now triangulate: MMM for budget allocation, incrementality tests to calibrate it, and platform attribution for day-to-day optimization.