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The Big Story: Why MMM Is Back In Fashion

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What if Meta graded everyone’s homework? Brands and agencies have long been skeptical of the platform’s penchant for “grading their own homework,” but now these same brands and agencies are trying on solutions like Meta’s Robyn, which does media mix modeling (MMM) for platforms.

Meta isn’t alone in building MMM tech. Amazon, too, is using MMM to clarify the relation between its sales data and brands’ overall marketing spend.  And Google is eyeing MMM, though it doesn’t have a product that’s been released yet.

On this week’s episode, we bring on John McDermott, the freelance writer behind our recent story about Big Tech building MMM. We dive into the details of each platform’s approach and consider what they mean for ad tech.

Meta, which dubbed its solution Robyn, is furthest along. Amazon’s solution is out there, but it isn’t formally productized. And Google is in a kind of exploratory phase – a nonconfirmation confirmation, if you will.

So far, buyers are finding Robyn useful, but they hold its results at arm’s length, not fully trusting Meta or its ability to measure firmly nondigital channels, such as radio.

The driving force behind tech platforms building MMM tools is data privacy. With less signal to process, they’ve had to get creative. MMM, with its blurry, channel-level analysis, is replacing user-level conversion tracking, which is increasingly showing up empty, blocked by Apple’s ATT and Safari cookie policies.

Listen in as we discuss why MMM, while it may not be privacy tech, is technology built for an ad tech future without precise tracking.



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