What is an A / B Test?

The definition of A / B Test refers to the development and launch of two versions of the same element to measure and check which one works better. In the field of digital marketing industry This test is used to optimize an email marketing strategy or improve the effectiveness of a landing page.

What is an A / B Test?

A / B testing is a technique that compares the effectiveness of different elements. A version is shown to a part of the users and the other version to another group, to then review through statistics and data which is the most convenient option and the one that has given the best results.

Carrying out these a / b analytics tests allows detecting different problems on a web page and even specifying certain elements that cause difficulties, such as a low number of users interested in subscribing, a high bounce rate or a low number of conversions that They can be linked to aspects such as font size, excess informational content, or design problems. In analítica web, A / B tests are essential to choose the option that offers the best result.

To carry out this type of test it is necessary to use different tools to apply A / B test. Through software such as Analitycs or Yadex it is possible to measure the actions.

How to do an A / B test?

Below we show how to do an A / B testing in a simple way and in several steps.

  • When you perform an A / B test it is because you actually detect a problem on your site or you think there is a need for improvement. You check, for example, that your conversion rates may be better or that you have a higher bounce rate than the industry average.
  • Analyze available data: check Analytics to see which pages show the best and worst results and which ones have a lower bounce rate or a greater number of page views, and from there try to detect common aspects.
  • Create a hypothesis: handle several solutions to improve the statistics of your page. If, for example, your landing is not attractive, you may have to consider the possibility of changing the image for a more cheerful one, and if your page shows too many abandonments, it would be convenient to incorporate a greater number of links at the end of each post.
  • Specify the test time: set the period that the test will last.
  • Start the A / B test with the variations: Among the A / B test examples are alternatives such as putting the buttons of the links in blue, as always, and in the other version in yellow, or showing your landing page original and another with a more attractive image.
  • Study the data and draw conclusions: depending on the conversion, it will be time to validate or reject the hypotheses raised.

A / B test in e-commerce

A / B Test Calculator

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