How Bayesian priors keep your MMM honest when data is thin
Most scaleups have two or three years of weekly data and a dozen channels. Without priors, a model will happily hallucinate certainty it has not earned. Priors are the guardrails.
Measurement, budget allocation, and Bayesian MMM - written for the people who own the number.
Most scaleups have two or three years of weekly data and a dozen channels. Without priors, a model will happily hallucinate certainty it has not earned. Priors are the guardrails.
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