Data teams run experiments and analyze results. But the biggest challenge isn't statistics—it's getting the rest of the organization to actually use the insights.
ExperimentBets transforms data teams from gatekeepers into enablers. When stakeholders predict outcomes before seeing results, they become invested in the analysis. Results presentations go from lectures to conversations.
Common Challenges
Results fall on deaf ears
You spend hours analyzing experiments, but stakeholders skim the summary and move on without changing anything.
Low statistical literacy
Non-technical stakeholders don't understand confidence intervals or sample sizes. They want simple answers.
Post-hoc hypothesis creation
Stakeholders claim they 'knew it all along' after seeing results. No accountability for predictions.
Data team as bottleneck
Everyone waits for the data team to prepare analysis. Experiment velocity is limited by analyst capacity.
How ExperimentBets Helps
Pre-commit predictions
Stakeholders must predict outcomes before results are available. No more hindsight bias. Everyone's thinking is documented.
Natural statistical learning
Through betting, non-technical people develop intuition for sample sizes and effect sizes. They learn by doing.
Self-serve experiment discovery
Results are announced in Slack automatically. Less time creating presentations, more time on high-value analysis.
Prediction accuracy as credibility
Leaderboards show who actually understands user behavior. Data-backed credibility emerges naturally.
"Our analysis used to go into slide decks that died. Now stakeholders come to us asking about experiments they bet on."
Other Use Cases
ExperimentBets for Product Teams
Get your product team engaged with A/B testing
ExperimentBets for Growth Teams
Increase experiment velocity and team alignment
ExperimentBets for Engineering Teams
Get developers invested in experiment outcomes
ExperimentBets for Executive Leadership
Build experimentation culture from the top down