How to do an A/B Testing: 10 steps for a split test

How to do an A/B Testing: 10 steps for a split test

The level of conversions depends on the page that receives our visitors, so it is important to apply A/B testing practices on the home page because in this way we can make decisions based on real data about the behavior of visitors and avoid make uninformed decisions.

 

When we talk about A/B Testing, it is about presenting two versions of the same website to two groups of people, where the effectiveness of elements such as forms, Call To Action and other elements that affect navigation will be evaluated.

 

The purpose of doing these tests is to find ways to improve conversion rates. The conversion rate largely depends on the homepage of a website, so it is essential to evaluate the user experience in order to improve and optimize it.

 

When applying the A/B testing you first have to define:

  • The variable you are going to test
  • What metrics are you going to base it on?
  • Ask yourself, are the groups divided correctly?
     

 

Steps for an effective split test
 

What is the split test? “Split testing or redirection testing consists of comparing several versions of the same element to check which of these two versions works better. We can say that Split testing is a type of A/B testing”, explained the AB Tasty portal in this regard.

 

1. Analyze your website data. A strong split testing campaign starts with your website data. Use a website analytics tool and find weak spots in your conversion funnel, bounces, and your top landing pages. This will help you determine the correct approach and prioritize test ideas.

 

2. Choose the tool that you are going to use to carry out the split test, which can be Google Analytics or HotJar, for example.

 

3. Decide which will be the two elements to which you will apply the test.

 

4. Always test the two elements or pages simultaneously, not one page after another, they recommend on the Blue Host portal.

 

5. Draw your conclusions only after you have had a significant number of visitors.

 

6. In addition to the previous point, it is essential that after the tests you make decisions based on data. “Weigh the impact of each variant on conversion rate, which variation of your website generated the most conversions?”, ask yourself that question, advises AB Tasty.

 

7. Split sample groups equally and randomly, HubSpot recommends: “For tests where you have more control over the audience, like with emails, you should test with two or more audiences that are the same to get results. conclusive”.

 

8. Request comments from real users to not only have the data generated by the tests, but also to have real feedback, with arguments, on why users prefer a certain website over another.

 

9. To determine which website performed better, you should do a comparison of conversion rates and evaluate the elements that worked in the navigation.

 

10. Segment audiences to understand how each group of people/users reacted to variations on the websites you presented in the tests.

 

In this video we explore the concept of A/B testing, how we can prepare for it, and what we can use. A/B testing allows us to conduct accurate and efficient studies of our website marketing strategy, plus optimizations can be made quickly, boosting our conversion rate.

 

What is A/B testing with an example?

A/B testing is a test that is applied to users to determine the browsing pattern on a web page and the effectiveness of the conversion rate. For example, when creating a web page, two homepages can be built and subjected to an A/B test to evaluate how users react to each one and determine which one had the best performance and conversion rate.

What's your A/B testing process?

Depending on what you want to test, there are many ways to implement A/B Testing. Among the most used tools are Adobe Target, Google Optimize, SplitHero, UserZoom, Visual website Optimizer.

What are the benefits of A/B testing?

"A/B tests are design tests that allow us to carry out variations of the same page to compare the behavior of users in the different options and thus assess which of the versions is the one that obtains the best results", they explain in an article in Marketing 4 Commerce.