Why MMM makes marketers nervous - and why you should use it anyway | MarTech

"The reactions rarely reflect what MMM actually is or how it should be used. The excited crowd sees it as the cure for every attribution problem - a way to finally bring clarity to messy data. They're often channel managers burned by last-click reporting. The skeptics usually had a bad experience. In my client's case, the problem wasn't MMM itself - it was how they used it."

"That's the real danger: when every team picks the measurement system that makes them look best, no one gets the whole picture. The business ends up with conflicting numbers and no clear answer to the only question that matters - how do we optimize campaigns and budgets to drive real growth? Why MMM feels both scary and antiquated MMM gets a bad rap. It feels old-school - and for years, performance marketers have laughed at MMM decks while high-fiving the CFO over attribution reports."

Performance marketers often react to Marketing Mix Modeling with polarized enthusiasm or skepticism. Enthusiasts see MMM as a way to clarify messy attribution beyond last-click reporting. Poor outcomes typically stem from biased implementation or conflicts of interest where model operators favor channels they buy. Cross-channel teams defending platform or last-click metrics produce conflicting numbers that impede budget optimization. Privacy rules and tracking changes reduce the effectiveness of user-level multi-touch attribution, restoring MMM relevance because it does not rely on stitching user paths. MMM complements touchpoint-level attribution rather than replacing it.

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