{"id":29984,"date":"2024-11-12T12:39:54","date_gmt":"2024-11-12T12:39:54","guid":{"rendered":"https:\/\/www.seobility.net\/en\/blog\/wiki\/ab-testing\/"},"modified":"2025-06-16T11:44:15","modified_gmt":"2025-06-16T11:44:15","slug":"AB_Testing","status":"publish","type":"wiki","link":"https:\/\/www.seobility.net\/en\/wiki\/AB_Testing","title":{"rendered":"AB Testing"},"content":{"rendered":"

Definition<\/span><\/h2>\n
\n
\n

\"AB<\/a><\/p>\n

Figure:<\/b> AB Testing – Author: Seobility – License: CC BY-SA 4.0<\/a><\/div>\n<\/div>\n<\/div>\n

A\/B tests (sometimes referred to as split tests) compare two versions of a website to determine which version is better suited to achieving a defined goal. Such a goal could be, for example, increasing conversion rates<\/a> or improving other performance indicators (KPIs). An A\/B test compares two website versions by randomly redirecting<\/a> visitors to one of the two variants and measuring user behavior. This allows webmasters and companies to test how user behavior is affected by changing a particular variable.<\/p>\n

The goal of A\/B testing<\/span><\/h2>\n

The goal of A\/B testing is to find the best possible website version to achieve a specific goal and to learn which changes can push website visitors towards a desired action.<\/p>\n

Compared to the costs of paid traffic<\/a>, the costs of increasing conversion rates through A\/B testing are rather low. The return on investment<\/a> of A\/B testing can be very high as even small changes to a website can lead to significant increases in leads and sales generated.<\/p>\n

How does A\/B testing work?<\/span><\/h2>\n

In an A\/B test, a second version of a web page is created in which a specific element is modified. This change can affect headings, buttons, images, or colors, for example. The change rarely involves a complete redesign<\/a> of a page.<\/p>\n

The next step in A\/B testing is to redirect half of the visitors to the original version of the page, and the other half to the modified version. Visitor behavior is measured and analyzed on both sides. This way, you can determine whether the change had a positive, negative or no impact on visitor behavior (for example, in terms of conversion rate).<\/p>\n

What can A\/B testing be used for?<\/span><\/h2>\n

You can use an A\/B test for optimizing landing pages<\/a>, emails or e-commerce pages with regard to conversion rate, leads, registrations, etc. The following elements, among others, can be modified and analyzed in an A\/B test:<\/p>\n