How it works
The model studies how sales moved as spend changed across channels over time, usually using two or more years of weekly data. It separates the effect of marketing from things like holidays, promotions and the economy.
MMM versus attribution
Attribution tracks individual users' clicks and visits. MMM works with totals, so it doesn't need cookies or user-level tracking and can include offline channels like TV, radio and billboards.
When it fits
MMM suits businesses spending across several channels with enough history and budget for the results to be meaningful. Free open-source tools like Google's Meridian and Meta's Robyn have made it more accessible, though it still needs skilled analysis.
Why Marketing Mix Modeling matters
As user-level tracking gets harder, MMM gives a privacy-friendly view of what marketing really drives, helping set budgets across channels with more confidence.
Finding what drove the busy months
A regional retailer spending on TV, search, social and direct mail couldn't tell which drove store sales. An MMM showed direct mail did more than its click-based reports suggested, and the company rebalanced its budget.
Common mistakes
Too little data
A few months of data can't separate channel effects. MMM needs long, consistent history.
Treating results as exact
Models give estimates with uncertainty. Test big changes with holdout or incrementality tests.
Running it once
Markets change. Update the model regularly as new data arrives.
Where we work on this