Learn MMM, in order

Nine explainers, sequenced for someone who will eventually have to defend a measurement budget to a CFO. Concepts you can skim; the ones your vendor will test you on are 1, 4, 7, and 8. Quick definitions live in the glossary; the terminal decision lives on the decide track.

1. 01How MMM worksThe regression intuition without code: inputs, transforms, decomposition, validation. Read first.
2. 02MMM vs attributionWhat broke with iOS signal loss and where each method still belongs.
3. 03MMM vs incrementality testingModels allocate; experiments prove. Complements, not rivals.
4. 04TriangulationThe consensus stack: experiments + model + platform data, and how to resolve their disagreements.
5. 05Data requirementsThe unglamorous checklist: history, granularity, variation, revenue definition.
6. 06MMM outputsWhat a finished model hands you, and which output belongs in the board deck.
7. 07Bayesian vs frequentistWhy the modern stack went Bayesian, and what that changes when evaluating vendors.
8. 08MMM limitationsThe honest failure modes; read before trusting any model, including one you paid for.
9. 09The curve labInteractive adstock and saturation curves. The intuition, draggable.