Rajiv Gopinath·Sep 23Chapter 29: When the Model Isn’t EnoughExperiments create a cleaner test of cause and effect; Chapter 29 in the Marketing Effectiveness Series
Rajiv Gopinath·Aug 26What Belongs in the Equation — Specification as Causal ReasoningA missing variable can give credit to the wrong cause. A badly included one can take credit away from the right cause. Specification is the…
Ayushi·Aug 11The Most Important Skill for a Data Scientist Working on MMM in the Age of AIA few months ago I watched an automated pipeline fit a marketing mix model in about four minutes. Data pulled, transformed, adstocked…
Brian James Curry·Jun 3When Your Marketing Agent Optimizes the Wrong NumberAutonomous optimizers are only as good as the signal they chase. Here is an analytical and simulated demonstration that an agent trained on…
Sureshabhimanyu·May 31Understanding Synergy in Multiplicative Marketing Mix ModelsA Proposed Framework for Decomposing Standalone and Interaction EffectsA response icon1A response icon1
Bernardo Lares·Oct 18, 2025Stop Building MMMs Without Business-Backed HypothesesWhy answering business questions should be a prerequisite to building every Marketing Mix Model (MMM).
Brian James Curry·Sep 15, 2025Unraveling Marketing Metrics with Statistical & Causal Modeling in PythonIntroductionA response icon1A response icon1
Ofir Ben Yehonatan·Jul 6, 2025Beyond Impressions: Why Incrementality Is the Only Metric You Can Still TrustIf you turned off all your ads tomorrow, what would happen to your sales?
Emilysmithcreate·Jun 5, 2025From Translator to Translation Architect: Designing Predictive AI That Actually Gets UsedBy Emily Smith, Founder of Side Nerd AppsA response icon1A response icon1
