"A/B testing is an experimental method where one variable, such as the webpage's copy, size of a button or timing of a triggered offer, is split-tested against the original webpage to determine whether the variant performs better than the control webpage by delivering a better conversion rate."
"Conversions can be several things, depending on the target behaviour the marketer is interested in generating. It might be social shares, newsletter signups, E-Commerce sales... anything that will improve your website's commercial performance."
"A major pitfall that some fall into when A/B testing is guessing at what changes will improve your conversion rate. Specific UX optimisations should be informed by website analytics data and/or user testing."
A/B testing is an experimental method used to optimize website conversion rates by comparing a variant of a webpage against a control. The goal is to identify which version yields a better conversion rate, which can include social shares, newsletter signups, or E-Commerce sales. While A/B testing is straightforward, its simplicity can lead to misleading results if not executed properly. Using data to inform hypotheses is crucial, as it helps identify areas for improvement and generates effective split testing ideas based on user behavior and analytics.
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