The CARE Model is a framework for improving how your team engages with experiments. It addresses the four key pillars that determine whether experiments actually influence decisions: Communication, Accountability, Recognition, and Engagement.
Most experimentation programs fail not because of statistical methodology, but because teams don't engage with results. The CARE Model provides a structured approach to fixing that.
C - Communication
Make experiments visible. If people don't know about experiments, they can't engage with them. Communication is the foundation of experiment adoption.
Announce new experiments proactively
Don't wait for people to find experiments. Push announcements to where your team already works (Slack, email, meetings).
Share results within 24 hours
The longer you wait to share results, the less people care. Set a standard: results go out within one day of conclusion.
Create a dedicated channel
Give experiments a home. A #experiments channel in Slack creates a go-to place for all testing discussions.
Use consistent formatting
Template your announcements so people know what to expect. Include hypothesis, variants, timeline, and where to discuss.
A - Accountability
Assign ownership. Every experiment needs someone responsible for seeing it through from hypothesis to decision. Without accountability, experiments become orphans.
Name an experiment owner
One person is responsible for each experiment. They ensure it launches, runs correctly, and results drive a decision.
Require documented decisions
After every experiment, document what was decided. Ship, don't ship, or iterate. No experiment ends without a choice.
Track decision influence
Measure how often experiments actually change plans. If decisions never change, accountability is failing.
Include in retrospectives
Review experiment outcomes in team retros. Ask: Did we act on results? What did we learn?
R - Recognition
Celebrate experimentation. People repeat behaviors that get recognized. If experimentation goes unacknowledged, it becomes a chore rather than a priority.
Celebrate learning, not just wins
A well-run experiment that disproves a hypothesis is valuable. It prevented shipping something that wouldn't work.
Highlight interesting findings
Share surprising results in team meetings. Make experiments a source of interesting stories, not just data.
Track experiment velocity
Measure experiments per month by team. Recognize teams that run more tests as learning leaders.
Create awards and achievements
Monthly recognition for top experimenters, best hypotheses, or most impactful findings keeps experimentation visible.
E - Engagement
Make experimentation interactive. Passive observation doesn't build investment. Active participation creates ownership and accelerates learning.
Let people predict outcomes
Before results come in, ask team members which variant they think will win. Predictions create investment.
Create friendly competition
Leaderboards tracking prediction accuracy turn experiments into a game. People pay attention when there's something to win.
Use seasons for fresh starts
Periodic resets (monthly or quarterly) give everyone a chance to compete. New players can jump in without being too far behind.
Discuss predictions publicly
When people share their reasoning for predictions, the whole team learns. Create space for hypothesis discussion.
How to Apply This Framework
Audit your current state
Score yourself on each CARE dimension. Where are you strong? Where are you weakest? Focus on your biggest gap first.
Pick one dimension to improve
Don't try to fix everything at once. Choose your weakest area and commit to three specific changes.
Implement for 30 days
Give changes time to stick. Track leading indicators (participation, response rates) weekly.
Measure and iterate
After 30 days, assess impact. Did engagement improve? Adjust your approach and move to the next dimension.