A/B testing
A/B · Showing two versions of a page, ad or e-mail to different people over the same period and measuring which performs better.
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Why it matters
Changes based on guesswork sometimes make results worse; A/B testing bases the decision on data. For a reliable result, only one element should change at a time, and the test should run long enough to reach enough visitors. Decisions taken on small samples can mistake chance for success.
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Example
Half of a landing page's visitors see a “Get a free quote” button, the other half “We will assess your project within 24 hours”. After three weeks the second version brings significantly more forms and becomes permanent.
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Common mistake
Ending the test early as soon as a difference shows in the first days. Early results fluctuate; no decision should be made before the planned duration and sample are complete.
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Related terms
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