Feature adoption rate answers a simple question: of the people who used the product in a period, how many used this feature? It is the quickest way to find features nobody found, and features that matter more than you thought.
The formula
Feature adoption rate = people who used the feature in the period ÷ active people in the period × 100
Example: 400 people used your app in the last 30 days and 92 of them exported a report. Export adoption is 92 ÷ 400 = 23%.
Count people, not clicks. One person exporting 50 times is still one person.
Pick the event that means “used it”
Opening a page is not using a feature. Track the moment the feature did its job: Exported report, not Opened export dialog. Name events as past-tense actions and keep the list short. Ten well-named events tell you more than a thousand auto-captured clicks.
Read it in context
- Compare against who could use it. A feature only on the paid plan should be measured against paid accounts.
- Look at the trend after changes. If you add a tour pointing at a feature, adoption should move in the next two weeks. If it does not, the feature or the tour needs work.
- Low adoption is not always bad. Account settings should be low. Your core action should be high.
Go one step further: a funnel
Adoption says how many. A funnel says where people stop: Signed up → Created project → Invited teammate. The biggest drop is where your next tour or fix should go.
Tracking it
In OnboardingTours, add hintwick("track", "Exported report") where the action finishes. The overview lists every tracked event with the share of active people who used it, for 7, 30 or 90 days, and the funnel view takes any pages and events in order.
Try it on your own app
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