Your question is Causal Inference for Feature Growth. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
You launched a new growth feature and adoption rose afterward, but rollout timing and user selection may make the raw lift misleading. You need to separate true incremental impact from underlying trends and selection effects.
How would you apply causal inference to understand whether a new feature actually drove growth?