A Survey of Causal Inference Applications at Netflix

This post surveys various applications of causal inference at Netflix, highlighting its use in understanding the incremental impact of localization (using double machine learning and synthetic control), designing holdback experiments for product innovation, adapting recommendation models with a Causal Ranker Framework, and calculating incremental account lifetime value. It emphasizes the shift from purely associative machine learning to understanding causal mechanisms for better decision-making.