Feature launch impact analysis
When a feature is already launched, causal analysis helps estimate whether the release changed user behavior or merely coincided with a broader trend.
Rollout evidence
Use staged rollout timing, eligibility rules, and exposure logs as the backbone of the causal design.
Counterfactuals
Compare matched non-exposed users, pre-period trends, or regions without the feature.
Decision
Decide whether to expand, redesign, hide, or monitor the feature based on effect size and guardrails.
- Separate eligible users from actually exposed users.
- Watch for selection into beta cohorts.
- Report uncertainty, not just directional lift.