Feature adoption

Feature adoption measures whether users are discovering and repeatedly using specific capabilities in your product.

It encompasses the full lifecycle from awareness (knowing a feature exists) to trial (trying it once) to habitual use (using it repeatedly).

Awareness: Does the user know the feature exists?

Discovery: Has the user found and opened the feature?

Trial: Has the user tried the feature at least once?

Repeat use: Is the user using the feature regularly?

Habitual use: Has the feature become part of the user's regular workflow?

In PLG, feature adoption is a key signal of whether users are progressing beyond initial activation into deeper value.

It also informs roadmap and pricing decisions, since heavily adopted features often justify premium plans or add-ons.

Low-adoption features may indicate opportunities for better onboarding, improved UX, or features to deprecate.

You can measure feature adoption using both breadth (how many accounts use a feature) and depth (how often they use it over time).

Segmenting adoption by plan, role, or acquisition channel helps you understand which features are driving value for which users.

Track adoption curves over time to see if new users are adopting features faster than older cohorts (indicating product improvements).

Improve discoverability with contextual prompts, tooltips, and in-app announcements.

Reduce friction in the feature itself—simplify the UI, provide templates, and offer sensible defaults.

Create feature-specific onboarding for complex capabilities that require learning.