Marketing: what is an A/B test?

A/B testing is a process applied in marketing that tests two versions of a variable: A and B, and also measures the impact of this variation. This method is frequently used in the digital marketing sector to test web pages, emails, forms, advertising visuals, landing pages, etc. But what exactly is A/B testing in marketing?

What is an A/B test?

A/B test, also known as A/B testing, is a scientific system that evaluates two versions of a certain web page. The real version of the web page is version A (this is the verification version), and version B is the processing page (modified page). Indeed, the performance of these versions could be measured easily if they are tested in parallel. The objective of this method is to identify the most reliable and effective version. To find out more about A/B testing, visit

Why is A/B testing important?

A/B testing is really important for your business, because it allows you to improve your marketing budget. For example: a manager offers a certain budget to get more traffic to his website, while opting for Google AdWords. The configuration of his A/B test will be followed by clicks on three different article titles. The duration of this test is one week, while it is necessary to make sure to use the precise number of ads for each option. Indeed, the results of the AB testing will help you to define which title gains the most clicks. Therefore, these data can be used to create your campaign, allowing you to have an important return on investment.

How to perform an A/B test?

To perform an A/B test, it is necessary to handle it in a scientific way. The first step is to define the overall purpose of the test. The whole process is divided into several steps: Identify the problem and examine the users' data: it is important to know why one' s content does not conceive conversions for example. It is necessary to properly analyze the reactions of the customers when they see the emails, even if it takes a lot of time. Therefore, it is crucial to target the relevant element on one' s content and design. Specify the hypothesis to be tested, then verify it: this involves determining precisely the elements to be tested, thereby minimizing the number of unknowns. Then, you can perform an A/B test between your current page and the new version with your target audience. Analyze the data and locate your new challengers: once the A/B test has been completed, you need to analyze the results to see if the article version has caused any change. Therefore, you need to find a challenger to test the best option.

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