Define adoption
Use event definitions and dimensions to make adoption measurable.
Use case
Improve feature adoption with better experiment inputs
Use customer evidence and event definitions to shape adoption experiments that go beyond launch announcements.
Free to start. Built for teams that talk to users and run experiments.
Feature adoption improves when teams understand who needs the feature, why it matters, and what behavior should change.
Find the audience
Use customer context to choose who should see the experiment.
Learn after launch
Roll up whether the change drove the intended behavior.
Outcomes
Build the habit of learning before scaling.
- Clearer adoption metrics.
- Better launch experiments.
- More useful post-launch learning.
Questions
Direct answers for product teams
What is a feature adoption experiment?
It is a test that helps a team learn how to increase meaningful use of a product capability.
Why does a data dictionary matter for adoption?
It helps teams define the event and dimension that prove adoption happened.
Keep exploring
Use case
Run product experimentation as a team habit
Use case
Turn customer conversations into growth experiments
Use case
Help product teams work from the same evidence
Use case
Plan activation experiments from real customer friction
Use case
Use customer evidence to shape retention experiments
Use case
Run onboarding experiments that teach your team faster
Use case
Shape pricing and packaging experiments with customer signal
Use case
Turn product discovery sprints into experiment plans
Use case
Give growth teams an operating system for experiments
Turn customer signal into better experiments.
Start with the kit, then use Personify to synthesize, plan, report, and share what your team learns.