You work on a product team that suspects a new feature, X, may be changing a key outcome, Y. The team wants to know whether the observed movement is truly caused by the feature or just noise, seasonality, or user mix changes.
How would you design a study to establish causality for feature X’s impact on metric Y? Explain how you would define success, choose the randomization unit, and decide whether the result is strong enough to ship.
