Measurement and evidence

What is marketing mix modelling (MMM)?

A statistical method that estimates each channel's contribution to an outcome by regressing historical sales against historical spend and external factors. Works without personal data and covers channels that cannot be tracked individually.
also calledMMMmedia mix modellingeconometrics

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what it means here

Here is what the term means for a UK buyer

The definition above holds anywhere. Buying media in the UK adds the detail below, including where AdBuyMCP does something different.

Attractive because it needs no identifiers and covers television, cinema and out-of-home. Limited because it is correlational, hungry for history, and sensitive to specification: two competent modellers can produce materially different answers from the same data. AdBuyMCP labels anything modelled as modelled and keeps it strictly separate from a powered causal result; a modelled estimate presented as evidence of causation is exactly the failure its evidence labels exist to prevent.

When does MMM make sense?

MMM needs a long history of spend and sales by channel, with enough variation in the spend for the model to separate one channel's effect from another's. It suits an advertiser with years of data and a settled channel mix.

A founder in the first year or two of paid media rarely has that history. A geo-lift test on one or two channels answers a narrower question with more confidence, and it can run on the next flight.

How should a modelled estimate be labelled?

AdBuyMCP uses four provenance labels: provider-reported, observed, modelled and powered causal. An MMM estimate belongs under modelled, and it keeps that label wherever it travels, including into a board pack.

Only a geo-lift test that passed its own power analysis earns powered causal, the one label that supports the word caused. No provenance label advances on the strength of sandbox or API-shaped data, which is why no sandbox campaign has reached a causal grade.

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same group

These terms are also in Measurement and evidence

What you can prove afterwards, and how to tell a number that means something from one that does not.

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