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A/B testing, at its simplest, is randomly showing a respondent one version of a design or page—version A or version B—and tracking the changes in behavior based on which version they saw. Version A is normally your existing design ("control" in statistics lingo); and version B is the "test," with one copy or design element changed. In a "50/50 A/B split test," you are randomly selecting which version of a design to show. A classic example would be comparing conversions resulting from serving either version (A) or (B), where the versions display different headlines. A/B tests are commonly applied to many forms of copy testing (including digital tests for clicked-on ad copy and landing page copy) to determine which version drives the more desired result. [1] [2]


  1. ^ SEMPO. SEM Glossary. <http://www.sempo.org/?page=glossary> (cited 1 April 2015).
  2. ^ American Marketing Association. Dictionary. <https://www.ama.org/resources/Pages/Dictionary.aspx> (cited 1 April 2015).

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