M
Max Headroom
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Two-Step Bayesian Marketing Mix Modeling with Carryover and Time-Varying Effects
This Idea covers a Bayesian marketing mix model that attributes business performance to marketing channels and guides budget allocation without user-level tracking. Advertising response is modeled with carryover (adstock) and saturating shape effects, and channel coefficients are allowed to vary over time so the model follows shifting effectiveness and market trends while capturing non-linear returns to spend. A Bayesian framework encodes prior knowledge and yields posterior, uncertainty-quantified estimates of each channel's contribution while controlling for seasonality and macroeconomic factors; the fit is validated against A/B tests and holdout windows. Learners see how the estimated response curves feed a convex-optimization step that recommends how to reallocate marketing budget for maximum effect.