Ronny Kohavi and GrowthBook cover the A/B testing best practices for designing experiments that drive long-term growth.
Khan Academy went from vibes-based prompt testing to running A/B experiments on their AI tutor, Khanmigo, in production. Kelli Hill shares the journey, including a fascinating iterative case study on latency vs. math accuracy.
Only 10–30% of experiments produce a clear winner — and that’s not a problem, it’s reality. This article shows how high-performing teams design experiments to learn faster and make better decisions, even when results are neutral.
For week 3 of our Launch Month, we're releasing SQL Explorer, which lets you query your data and visualize results.
This release includes an exciting new feature flag rule, a long-awaited addition to experiment results, an integration sure to make
GrowthBook 3.5 enhances user experience with a revamped Dev Tools extension, a data-driven Power Calculator, an Experiment Decision Framework, and comprehensive SDK updates.
Discover how Multi-Armed Bandits revolutionize A/B testing in GrowthBook. Learn to optimize experiments automatically, reduce opportunity costs, and make data-driven decisions faster.
GrowthBook now supports quantile testing for Pro and Enterprise customers.
GrowthBook's updated Bayesian engine enables new capabilities and improved estimation in small sample sizes.
CUPED is now available for the Frequentist engine in GrowthBook 2.0!
Experiment analysis queries in GrowthBook now run up to 2X faster! Read about the improvements
In under two minutes, GrowthBook can be set up and ready for feature flagging and A/B testing, whether you use our cloud or self-host.
