Industry Applications of Causal Inference

This course translates causal designs into the decisions companies actually make. The examples are framed around marketing incrementality, pricing, recommendations, retention, feature rollouts, marketplaces, policy settings, and the final step that often matters most: turning an estimate into a decision memo.

The objective is to show how causal inference becomes operational work. By the end of the course, a reader should be able to map business questions to estimands, choose designs that match available variation, identify the operational constraints around launch decisions, and communicate results in a way that separates evidence, assumptions, risks, and recommendations.

Figure: Campaign-launch revenue trends, connecting causal design to the kind of business question that teams actually face (adapted from Lecture 01: Marketing Incrementality).

Lecture Sequence

01. Marketing Incrementality

This lecture connects Marketing Incrementality to business context, estimand choice, diagnostics, tradeoffs, and recommendation quality.

02. Pricing and Promotions

This lecture develops Pricing and Promotions with examples that make assumptions, diagnostics, and interpretation visible.

03. Recommendation Systems and Ranking

This lecture uses Recommendation Systems and Ranking to clarify the analyst’s question, evidence, assumptions, and decision implications.

04. Customer Retention and Churn Interventions

This lecture connects retention and churn interventions to targeting, timing, treatment cost, and customer-level decision rules.

05. Product Launches and Feature Rollouts

This lecture frames Product Launches and Feature Rollouts as a decision problem and asks what evidence can be trusted, challenged, and communicated.

06. Marketplace and Platform Interventions

This lecture builds intuition for Marketplace and Platform Interventions and ties the result to model choice, uncertainty, and action.

07. Health, Education, and Policy Applications

This lecture applies Health, Education, and Policy Applications with emphasis on diagnostics, tradeoffs, and evidence limits.

08. From Causal Estimate to Decision Memo

This lecture develops From Causal Estimate to Decision Memo as a practical pattern for analysis, diagnostics, and decision support.