When A/B Tests Aren’t Possible, Causal Inference Can Still Measure Marketing Impact

This episode of Data Science Tech Brief discusses measuring marketing impact when A/B tests are not feasible. It explores causal inference techniques such as Diff-in-Diff, Synthetic Control, and Meta's GeoLift, providing guidance on data preparation and code implementation.

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