What is feature adoption rate?
Used in a sentence: Feature adoption rate for split bills is low, but most users who try it once come back, so this is a discovery problem.
How it works
Each feature gets a usage event that means real use: “autopay set up”, not “autopay screen opened”. Feature adoption rate compares users who fire that event with all active users in the same window, often the first few weeks after launch.
Teams track it alongside repeat use, because a feature tried once and abandoned has not really been adopted. Low adoption is then diagnosed: if few users ever open the feature, it is a discovery issue; if many open it but don’t complete the action, the feature itself needs work.
Example
An OTT app ships a “download for offline” option, but few users try it. The team adds a tooltip on the download icon for users who start watching on mobile data, and a short picture-in-picture video for users about to travel, based on their viewing pattern. Users who have already downloaded an episode are excluded. Adoption is tracked weekly against users who saw no prompt.
Feature adoption vs feature discovery
| Feature adoption | Feature discovery | |
|---|---|---|
| Question it answers | Do users actually use it? | Do users know it exists? |
| Typical event | Core action completed | Feature screen viewed |
| Fix when low | Improve the feature or its value | Improve placement and prompts |
Discovery comes first. Adoption only tells you something useful once enough users have found the feature.
Best practices
- Define adoption as completing the feature’s core action, and track repeat use alongside it.
- Use the eligible audience as the denominator when a feature applies only to some users.
- Introduce features in context, near the screen where they help, not in a generic announcement.
- Stop prompting users once they have adopted, so guidance doesn’t turn into noise.
How to do this with Digia Engage
A product team builds tooltips, spotlights or in-app videos in Digia’s no-code builder and triggers them on events already tracked in CleverTap, MoEngage or WebEngage, such as opening the screen where the new feature lives. Targeting excludes users who have already used it. Prompts can be changed or switched off without an app release. The Feature adoption use case shows common patterns.
Frequently asked questions
- How do you calculate feature adoption rate?
- Choose the event that means the feature was genuinely used, not just viewed, and a time window. Divide the number of users who fired that event by all active users in the same window, and multiply by a hundred. If the feature is only for some users, use that eligible group as the denominator.
- How do you increase adoption of a new feature?
- Show the feature where it is useful, at the moment the user needs it. A tooltip or short video near the relevant screen works better than a launch announcement on the home screen. Target users likely to benefit, measure repeat use as well as first use, and stop prompting once someone has adopted.
Related terms
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Part of the In-app engagement glossary.