Your quick guide to A/B testing

This article is focused on the importance of A/B testing for Conversion rate optimization.

Remember that saying “comparison is the thief of joy”? Well, when it comes to optimising your website, comparison may, in fact, be a source of joy.

After all, there will always be room for improvement, and how else can you find out what your visitors want? That being said, by testing as many options as possible, you are making sure that the final result is as optimised as possible.

As Dan Gingis highlighted, you are competing with all the other experiences that your customers have had. You might not be able to read your visitors’ minds, but in this data-driven world, you can come close to that through A/B testing. So, it comes as no surprise that A/B testing is the most used conversion rate optimisation (CRO) method.

Keep reading to find out how you can take your business from ordinary to extraordinary by optimising your website with A/B testing.

What is A/B testing?

When you do A/B testing, you are essentially creating two versions of a web page and presenting them to different audiences simultaneously to find out which one performs better. This way, the results represent user behaviour during the same time period.

While A refers to ‘control’ and represents the original variable, B is the newer option. That being said, although conversion metrics vary depending on what you are focusing on, the variant that has the most positive impact on conversion metrics is the one that wins.

Essentially, this conversion rate optimisation method is all about tailoring your website according to visitor behaviour.

Why should you do A/B tests?

When it comes to the ever-changing digital world, gut feelings and intuition are simply not enough anymore. So, what better way to reduce uncertainty than by conducting tests?

Keep reading to find out more about the benefits of this CRO method!

• Increases conversions: A continuously optimised website also means increased conversions. Besides, thanks to A/B testing, you’ll understand user behaviour better as you’ll discover what works and what doesn’t for your visitors.

• Improves user engagement: From headline to call to action forms, layouts, fonts, and even colours, you can test how these changes sway user behaviour. That being said, tailoring your website according to visitor behaviour will also reduce the bounce rate.

• Makes data-driven decisions: When you test everything, the chances of making poor decisions decrease. Therefore, not only are you reducing risk factors, but by doing that, you are also reducing the time and money you would have spent tweaking your website according to subjective evaluations.

How to Do A/B testing?

Let’s get one thing straight: However, if you want to conduct A/B tests the right way, there are some steps you should follow.

• Pick one variable: It’s normal to want to optimise everything, but it is also crucial to take it one step at a time. Otherwise, you’ll find yourself even more confused, as you won’t know which changes have made an impact. So, pick one variable and think of its variations. For example, if you are testing a call to action (CTA) button, you can test the text, the position, and even the colour.

• Set up your hypotheses: After you’ve identified your variable, you need to establish your hypotheses. Let’s continue with the CTA button as an A/B testing example. In this case, your hypotheses could be that changing the CTA button’s placement would increase conversions.

• Choose your conversion metric: In order to not get overwhelmed, you need to choose a primary metric to track before you start conducting tests.

• Divide sample groups: The audience samples should be divided equally and randomly. You should also keep in mind that sample sizes vary according to what you are testing.

• Test variations: The only way you can ensure that the results from your A/B test are accurate is by running the tests simultaneously. However, it is implied that if you are testing timing, you will need to run variations at different times of the day, as that is the main point of the test.

• Analyse your results: A/B testing is useless if you aren’t interpreting your results and applying the findings. Besides, A/B testing tools make this step easier. However, if the tested variable didn’t have an impact on results, you can either test another variable or continue with the original.