Practical guides on experiment planning, statistical methods, and conversion rate optimization frameworks.
A curated bank of 47 high-impact A/B test ideas for landing pages, checkout, pricing, CTAs, and email — each with the psychology behind why it works and an ICE-style impact estimate.
The statistics errors that make A/B test results lie: peeking, p-hacking, ignoring power, misreading confidence intervals, multiple comparisons, and more — explained simply with fixes.
A/B testing vs multivariate testing (MVT) explained: the difference, traffic requirements, when to use each, and a decision table. Most teams should default to A/B.
Compare the three big CRO prioritization frameworks — PIE, ICE, and PXL — with scoring breakdowns, a side-by-side table, and guidance on which to use for your team's stage.
Conversion rate optimization (CRO) explained: what it is, how to calculate conversion rate, the CRO process step by step, common tactics, and how A/B testing fits in.
Roughly 70-80% of A/B tests don't produce a winner. Here are the real reasons tests fail — weak hypotheses, underpowered samples, peeking, local maxima — and how to catch losers before you waste traffic.
Learn the exact formula and inputs needed to calculate the right sample size for your A/B test. Covers baseline rate, MDE, significance, power, and common mistakes.
Learn how to use the ICE scoring framework (Impact, Confidence, Ease) to prioritize your A/B test backlog. Includes scoring examples and common pitfalls.
The definitive guide to A/B test duration. Learn why minimum runtime matters, how to calculate it, and the costly mistakes teams make by stopping too early.
A step-by-step guide to writing structured, testable A/B test hypotheses using the If/Then/Because format. Includes 10 real examples across industries.
How to run meaningful A/B tests with limited traffic. Strategies for small sites including higher-funnel testing, qualitative methods, and sequential testing.
What is MDE, how to choose the right one, and why it's the most important parameter in your A/B test setup. Practical guide with examples and trade-off analysis.
How to apply Robert Cialdini's 6 principles of persuasion — reciprocity, commitment, social proof, authority, liking, and scarcity — to improve conversion rates.