Feature Adoption Rate measures what percentage of eligible users are actively using a specific feature. It is a leading indicator of feature value and helps PMs decide whether to invest further, improve discoverability, or sunset a feature.
After every significant feature launch, and ongoing to monitor the health of individual features.
- Define the feature's 'eligible' user base — who should potentially be using this?
- Define what 'use' means — a single interaction? A complete action? Recurring use?
- Calculate: (Users who used the feature / Total eligible users) x 100
- Set a target adoption rate for 30 days post-launch
- If below target, investigate: discoverability problem, value problem, or fit problem?
- Consider sunsetting features with persistent low adoption (<5%) after 6+ months
Collaborative Playlist — 6 months after launch: eligible users = all Premium users. Users who have ever added a track to a friend's playlist = 5.3% adoption. Low, but engaged users show 4x higher retention. Decision: don't sunset, but don't invest further in discoverability — it serves a niche but highly valuable segment.
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- Counting any single click as 'adoption' — define a meaningful threshold for genuine use
- Sunsetting features with low adoption without first investigating whether it's a discoverability issue
- Ignoring adoption signals for months — low adoption needs a response within 4-6 weeks
- Lean Analytics — Croll & Yoskovitz
- Continuous Discovery Habits — Teresa Torres