A/B testing consists in the parallel operation of two versions of the same page, which differ in only one element. Both versions are shown to the same number of users, so you can check if the element with which the pages differ affects the movement of users and if so, which version is better. These types of tests help determine if the planned changes will affect the increase in conversions. It may be a good idea to add an element of qualitative analysis to the test, i.e. a survey, for example. The results of the A/B test show how users move around the site, and the survey allows you to determine why they took such actions.
Collect data
Before starting the test, you should find out which pages may need optimization, such as those with a low conversion rate.
Indicate goals
The next step to take before starting the tests is to answer yourself the question “what is the business goal?” , that is, what exactly is required of the user and what will be checked. This can be, for example, making a purchase, leaving your data, downloading materials.
Come up with solutions
At the moment when you have a set goal, you can start thinking about how to achieve them — what can be changed on the website? Is the current process sufficiently clear? How can you get more people to go to a specific subpage? etc. Such ideas can be implemented and it is they that will be translated into the “B” version of the page or application. You have to remember to identify ideas wisely and start testing with the ones that seem to be the most likely.
Create versions A and B
It is important to remember that versions must differ only by one element, so that you can be sure what affects the change in user behavior. The versions cannot therefore also differ in appearance or build quality.
Conduct a test
In the A/B test, it is important that approximately the same number of users benefit from both versions. Also, you can not forget about the correct configuration of analytical programs that will collect data.
Analyze the results
After collecting the data, it is necessary to analyze it - check which changes have affected the increase in conversions and what elements to implement accordingly.
Thanks to A/B testing, it is possible to quickly verify disputed issues and choose a better solution. That is why they are recommended in situations when there is a discussion about which version of the utility to choose.
