What Is A/B Testing?

A/B testing is a method of testing and comparing two versions of a product, website, or content to determine which one performs better. It is also known as split testing or bucket testing. The goal of A/B testing is to identify changes that will lead to a better user experience or increased conversions.

More about A/B Testing:

A/B testing is done by randomly showing each version of an advertisement, post or campaign to a group of users and then measuring which version receives more clicks, conversions, or other desired actions.

This is done by splitting the target audience into two groups and exposing them to different versions of the content, then measuring the results and selecting the best-performing version for future campaigns. A/B testing is widely used in social media advertising to improve click-through rates, conversions and overall ROI.

A/B testing is widespread because it allows for a direct comparison of two versions and can provide statistically significant results quickly.

Look at the ads below that Nike created with two different videos to promote the new Nike Pegasus. This is an example of a/b testing where Nike used a/b testing to promote their new shoe.


The first known use of A/B testing in a digital context was by Google in 2000, when they used it to test different versions of their search engine results page.

Frequently Asked Questions

What are A and B in A/B testing?

In A/B testing, "A" and "B" refer to two different versions of something, such as a website or a marketing campaign. The goal of A/B testing is to determine which version (A or B) performs better by comparing data from each version.

For example, a website owner might create two versions of their website (A and B) and randomly show each version to different visitors. They would then compare metrics such as click-through rate, conversion rate, and bounce rate to determine which version performs better. A/B testing can test various website elements, such as headlines, images, and layouts.

What are the tools available for A/B testing?

Many tools are available for a/b testing, both paid and free. Below is the list of the six most commonly used a/b testing tools.

A/B testing tools:

  • Google Optimize: A free tool from Google allows you to conduct A/B tests on your website. It also includes features such as multivariate testing and personalization.
  • Optimizely: A popular tool that offers both A/B and multivariate testing. It also includes features such as personalization and targeting.
  • Unbounce: A landing page optimization platform that allows you to create and test different versions of your landing pages.
  • VWO: A tool that provides A/B and multivariate testing, as well as heat mapping, session recording, and form analytics.
  • AB Tasty: A tool that provides A/B, multivariate, and split testing, as well as personalization and analytics
  • Crazy Egg: A conversion rate optimization tool that includes A/B testing and heat mapping.

These are some of the popular tools that are widely used, but there are many other options available, depending on your specific needs and budget.

How do A/B testing tools vary?

A/B testing tools can vary in terms of features, ease of use, testing capabilities, integration, personalization and targeting, reporting and analytics, customer support, and price.

Some tools may be designed to be user-friendly and easy to set up, while others may require more technical expertise to use. Some may only offer basic A/B testing, while others may also offer multivariate testing and other advanced features.

Ultimately, the right A/B testing tool for business will depend on your specific needs and budget. It's important to evaluate your needs and research different options to find the best tool for you.

What is multivariate testing? Difference between A/B testing and Multivariate testing.

Multivariate testing is a method of testing in which multiple variations of a campaign are tested at the same time. It is different from A/B testing, which only tests two campaign variations simultaneously.

To simplify, the main difference between A/B testing and multivariate testing is the number of variations being tested. A/B testing tests two variations at a time, while multivariate testing tests multiple variations simultaneously.

A/B testing is simpler and easier to set up, while multivariate testing is more complex and requires more resources, but it can give more detailed insights.

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