A/B testing guides
Make better experiments — and know when not to run one.
Practical guides for sample planning, low-traffic testing, pre-launch research and interpreting evidence.
A/B Testing With Low Traffic: What to Do Instead of Waiting
Learn when classic split testing is underpowered, how to estimate the traffic you need, and which pre-launch research methods can help you decide sooner.
GuideHow Long Should an A/B Test Run?
Estimate A/B test duration from baseline conversion, expected lift, traffic and statistical power instead of using arbitrary one- or two-week rules.
GuideA/B Testing Sample Size: How Many Visitors Do You Need?
Understand baseline conversion rate, minimum detectable effect, confidence and power, then estimate the sample required per A/B test variation.
GuideStatistical Significance in A/B Testing, Explained Practically
A practical guide to p-values, confidence, effect size and why a statistically significant A/B test is not automatically a useful business result.
GuidePre-Launch A/B Testing: Test Decisions Before You Have Traffic
Learn which product, positioning and creative decisions can be tested before launch and which claims still require live behavioral experiments.
GuidePreference Testing vs. A/B Testing: Which Should You Use?
Compare preference tests and live randomized A/B experiments, including what each method can prove, when each is useful and where teams commonly confuse them.