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Michael Kaminsky


Choosing Your Attribution Model

Introduction to Media Mix Modeling

Michael and the team at Recast are on a mission to rid the world of wasted marketing spend. Before founding Recast, Michael was Director of Analytics at Harry’s.

In This Article:

What is Media Mix Modeling (MMM)?

Media Mix Modeling (MMM) is a statistical modeling technique that marketers use to determine which channels in their marketing mix are driving their sales, acquisitions or other business KPIs. MMM helps brands reallocate budgets to the highest-performing areas of their media mix and cut down on wasted ad spend.

The most important goal of MMM is identifying the incremental return on investment into every media channel in a marketing mix. Incrementality is a measure of what actions would not have happened without a specific intervention.

Consider a brand running ads on Meta. Adding up the users who bought their product after being shown an ad is not the same thing as counting the users who bought their product because of an ad.

Some users who saw the ad would have bought their product anyway, even if the brand had not run their campaign. This is incrementality.

Media Mix Modeling is one of the most popular and practical methods used by brands to estimate the incrementality of each of their marketing channels.

Media Mix Modeling

How does Media Mix Modeling work?

Media Mix Modeling uses machine learning and statistical algorithms to find patterns in historical observational data. At a high level, it looks for variation in marketing activity and attempts to line that up with variation in a business KPI.

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