Design basic A/B tests to compare two versions and measure impact.
A/B testing compares two variants to see which performs better on a chosen metric. Define a single hypothesis and metric, randomize assignment, and run the test long enough to collect meaningful data. Avoid multiple simultaneous changes that confound results. Analyze differences with simple statistics and consider practical significance, not just p values. Document the test and iterate based on findings. Small experiments guide design choices and reduce guesswork.
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