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A/B Testing Guides
In-depth methodology guides written for CRO practitioners and data scientists who want to run statistically rigorous experiments.
Statistical Methods10 min read
A/B Test Sample Size: The Complete Guide to MDE, Power, and Significance
How Expected Lift (MDE), statistical power, and confidence level interact to determine how much traffic your experiment requires — plus the 50/50 split rule and the Sensitivity Table.
Read guideCommon Pitfalls8 min read
The Peeking Problem, One vs. Two-Sided Tests, and Inconclusive Results
Why checking results early silently inflates your false positive rate, when one-sided tests are mathematically superior, and how to run a diagnostic protocol on a flat result.
Read guideTest Design7 min read
How to Define Your Metrics Before an A/B Test to Avoid Data Dredging
The three-tier metric hierarchy — primary, secondary, and guardrail — and why defining it before traffic flows is the only valid defense against selective interpretation.
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