Marketing Science16 min read

Practical optimizer scenarios in MMM: A step-by-step guide

Walk through real-world MMM optimization scenarios using Mixed Integer Programming. See how to discretize response curves, formulate constraints, and solve practical reallocation problems with actual numbers.

Cyril Noirot

Lead Data Scientist

August 21, 2025

About the author

Cyril Noirot

Lead Data Scientist

Freelance data scientist. I design and ship decision systems — forecasting, pricing, marketing measurement, optimization — for teams making high-stakes calls.

ROI Is Not Enough. You Need Time-to-ROI.

Two initiatives can show the same ROI and still deserve very different decisions. The missing variable is time-to-ROI: how fast the initial investment is recovered.

Marketing Science8 min

From Propensity Scores to Learning Systems: What Most CRM Teams Get Wrong

Most CRM organizations don't have a feedback loop. They have a broadcasting system. The shift from propensity to uplift modeling changes everything.

Marketing Science6 min

Your MMM Should Not Predict Revenue

Revenue is a derived quantity. Marketing influences demand, units sold, not price. Modeling revenue directly entangles two mechanisms and produces misleading attribution.

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