A/B testing is a method of comparing two solutions in order to determine which one is better received by the audience. A/B testing is used for websites, banners, advertising, email newsletters, subscription forms, and calls to action. The method allows for testing various hypotheses and making a choice in favor of the better solution.
The principle of A/B testing is extremely simple. A company has a product that it wants to change, but is not sure if these changes will be effective. To find out, the company creates two versions of the product: the old one and the new one with the changes. Then the company shows both versions to its audience, with only half of the audience seeing each version. The company then looks at the results of the testing and decides which version of the product the audience reacted better to. To do this, the company must study web analytics and compare metrics for both versions. For example, for an email newsletter, this could be the email click-through rate. Based on the results of A/B testing, the company can make several decisions:
- if option A, i.e. the old version of the product, performed better than option B, then everything stays as it was;
- if the metrics for option B were better, then the company uses the new version of the product;
- if options A and B showed similar results, then the company chooses which version of the product they want to keep at their discretion.
Depending on the decision you plan to test, the ways of dividing the audience may differ. If it is about banner advertising, you can launch two separate advertising campaigns. For email newsletters, you can manually divide the contact base or use built-in A/B testing tools from the mailing service. You can even manually gather focus groups and have them test the solution. This approach will be effective, for example, for a website page.
A/B testing should be approached comprehensively and take into account a number of points before conducting it. First of all, you need to form a hypothesis that you want to test. You need to decide what exactly, why and how you want to change. This decision must be well-founded and have a specific goal. For example, increasing the number of subscriptions to the newsletter by changing the pop-up window. Next, you need to decide which element of the pop-up window will be changed. For A/B testing, only one element should be changed, otherwise, you will not understand which changes have had an effect. Also, before launching the testing, make sure that you have web analytics connected, which will tell you about the results of the testing.
