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.
Writing on how decisions get modeled, built, and deployed. By Cyril Noirot.
Most CRM organizations don't have a feedback loop. They have a broadcasting system. The shift from propensity to uplift modeling changes everything.
Revenue is a derived quantity. Marketing influences demand, units sold, not price. Modeling revenue directly entangles two mechanisms and produces misleading attribution.
A comprehensive guide to deploying production-ready Marketing Mix Models—covering data ingestion, model training, cloud deployment, and real-time optimization APIs for budget allocation
Deep dive into gradient boosting trees with quantile regression for robust uncertainty estimation in travel retail forecasting.
Learn how Mixed Integer Programming (MIP) with discretized response curves solves marketing budget allocation problems using branch-and-bound methods.
How to build robust forecasting models that account for uncertainty, seasonality, and external shocks in the travel retail sector.
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.
Exploring structural causal models using DAGs, counterfactual reasoning, and frameworks like DoWhy and PyMC-Marketing
How Google's Meridian brings causal inference to marketing mix modeling at global scale
Interactive tools and calculators for practitioners — built to explore ideas, not to sell software.
Available for consulting engagements in forecasting, pricing, and decision systems. More about me