Know If Your Feature Launch Is Actually Working
You shipped the feature. The question is whether the right users are adopting it at the rate you expected — and if not, exactly where and why the rollout is stalling.
The problem
- →Adoption curves look flat in the first weeks after launch because new feature events are buried in total event volume and require a deliberate filter to surface.
- →Segment-level adoption differences — by plan tier, company size, or user role — are invisible in aggregate numbers and only matter when you are trying to decide whether to gate, promote, or iterate on a feature.
- →Time-to-first-use varies enormously across user segments, but it is rarely measured because it requires joining user creation timestamps to first feature event timestamps across event tables.
- →Power users who adopt deeply in the first 30 days are the best signal for long-term feature retention, but identifying them requires a query that most product teams do not have ready.