Tag: marketing-mix-modeling
All the articles with the tag "marketing-mix-modeling".
-
Your MMM's Control Coefficients Are Not Findings
In a marketing-mix model you add seasonality, price, and competitor spend so your media coefficients come out clean. Then someone reads those control coefficients as insights. That's the Table 2 fallacy, and in an MMM it comes with two extra ways to get burned.
-
What Decades of Marketing-Mix Data Actually Tell Us
Forty years of scanner data and split-cable experiments converge on a few numbers that are remarkably stable across brands and categories. Knowing them turns a media model from a free-for-all into something with priors.
-
The Illusion of Significance: Why p-value Variable Selection Breaks Marketing Mix Models
Stepwise regression produces overconfident models with biased estimates — here's why that matters for MMM, and how Bayesian shrinkage priors fix the problem without breaking your causal identification.
-
Noisy Covariates Bias Your Coefficients Toward Zero
When a predictor in your regression is measured with error, its coefficient shrinks toward zero in a predictable, quantifiable way — here's the math and the Bayesian fix.