Guide stub

Calibrating MMM with lift tests

Experiments don't replace MMM; they stress-test whether the model's channel effects live in the same world as causal evidence.

Calibration is optional in many audits, but when you have geo-lift or other incrementality results, ignoring them is a missed control. This stub outlines what a full guide will cover.

Outline

  1. What “calibration” means (and what it doesn't)
  2. Matching experiment design to MMM grain (geo, time, channel)
  3. When disagreement is informative vs noisy
  4. Incorporating lift into Bayesian / constrained MMM workflows
  5. Reporting calibrated vs uncalibrated decision impact
  6. Common failure modes: wrong cell, wrong KPI, wrong window

Related: validation checklist · what is an MMM audit

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