What Is A/B SEO Testing?

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What Is A/B SEO Testing?

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AB testing is essentially an experiment where two or more variants of a page are shown to users at random, and statistical analysis is used to determine which variation performs better for a given conversion goal.

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A/B testing is a way to test different elements of your website / marketing copy in order to see which performs better with your audience. Page titles, meta descriptions, calls-to-action, and even products descriptions are all elements you can test for the highest-performing variant. You can use Google Optimize to help you run the A/B testing. Or, if you’re short on time, you could always run a small paid ad campaign to test your preferred elements before making changes to your website.

The technical SEO concept behind A/B testing is that you will mask variants of a particular URL from search engines so that they can only be found by users. Then, a certain percentage of the visitors to your site will be exposed to a different variant and you can track how they react.

An A/B test, also known as a split test, is an experiment for determining which of different variations of an online experience performs better by presenting each version to users at random and analyzing the results. A/B testing can do a lot more than prove how changes can impact your conversions in the short-term.

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AB testing is essentially an experiment where two or more variants of a page are shown to users at random, and statistical analysis is used to determine which variation performs better for a given conversion goal

A/B testing is a method of comparing two versions of a webpage or app against each other to determine which one performs better. AB testing is essentially an experiment where two or more variants of a page are shown to users at random, and statistical analysis is used to determine which variation performs better for a given conversion goal.

AB testing is essentially an experiment where two or more variants of a page are shown to users at random, and statistical analysis is used to determine which variation performs better for a given conversion goal.