Your question is Multiple Metrics in Experiments. 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're reviewing an experiment on a social product with several success metrics and guardrails. The team is debating how to interpret mixed results across primary, secondary, and diagnostic metrics, and how to control false positives when many comparisons are made.
How would you think about multiple metrics and multiple comparisons in an experiment?