Master Causality for Smarter Marketing Decisions
Who is this course for?
What makes this course unique?
Most courses stop at theory or focus only on technical execution. This program is different.
We connect the foundations of causal inference with real-world marketing applications, showing you not just how causal methods work, but why they matter in day-to-day business decisions.
You will see how concepts like counterfactual thinking, causal graphs, estimands, and advanced estimation methods directly influence marketing effectiveness.
What will you learn?
Foundations of Causality
Observational Studies vs RCT , Pearl’s Causal Ladder, Bradford Hill’s criteria.
Applied Marketing Mix Modeling (MMM)
Translating causal concepts into actionable marketing insights.
Graphical Models
Directed Acyclic Graphs (DAGs), SWIGs, confounders, mediators, and colliders.
Causal Estimation Techniques
Difference-in-Differences, Synthetic Control, Propensity Score Matching, Instrumental Variables, Randomized Controlled Trials, and Ghost Ads.
Estimands in Depth
Learn how to define and interpret the most important causal quantities - Average Treatment Effect (ATE), Average Treatment Effect on the Treated (ATT), Conditional ATE (CATE), and Local Average Treatment Effect (LATE) and see how each applies to marketing contexts.
How do we teach?
- Rebranding campaigns to explain counterfactuals.
- Promotions and awareness drives to illustrate confounders and mediators.
- Hands-on demos with real-world MMM cases to apply methods like DiD, PSM, and IVs.
- Case studies on media synergies and channel effectiveness, showing how causality resolves practical business questions.
Bonus Tools - Learn by Doing
Featured Course
Build expertise in Causal Inference.
Each module dives deep into causal foundations and advanced estimation methods, with applications tailored to real marketing challenges.
Experimentation Course
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