A/B testing is a valuable tool that business owners can use to improve their website’s performance. Performing A/B tests allows business owners to test different versions of their website to see which one performs the best. This allows them to make changes and improvements based on data, rather than simply guessing what might work better. This type of testing can help businesses increase their sales and conversions, as well as improve their customer satisfaction rates.
What is A/B Testing and How Does it Work?
This method of testing is one of the easiest ways to do a randomized controlled experiment. These tests show two sets of users two different versions of a product or website to determine which version has the most success for whatever your goal is. This answers questions such as, “What is most likely to make people click? Or buy a product? Or register with our site?”
How to Set Up an A/B Test for Your Website or Product
The Harvard Business Review gives a great example of how to start using an A/B test for your website. In its simplest form, you are testing to see if users on your website prefer “option A” or “option B”, hence the name, A/B test. For example, if you want to know what size to make a call to action button on your site, first decide what metric you will be measuring in. For this example, we want to know how many visitors are clicking on the button. Show two randomly assigned sets of users the different versions of your site (half will be seeing the larger button and half will be seeing the smaller button). You then analyze the data and determine which button size caused more visitors to click. This type of testing can also be used with marketing emails and ads.
Interpreting A/B Test Results
After completing your testing, you will have different conversion rates to analyze. One should be for the users that saw the control version and another for the users who viewed the version you are testing. Keep in mind that there will always be a margin of error with any type of test that needs to be accounted for. If your conversion rate for the new version is barely higher than the old and is going to cost a significant amount to put into place, it might not be worth the expense. However, if it is either largely higher than your original or slightly higher but inexpensive to change, it is worth making the change and seeing how it performs in real life. Some common mistakes made when it comes to interpreting test results are:
- Making a decision too quickly based on real-time data can cause you to have a misinformed decision that might be different if the test was allowed to come to an end naturally on its own.
- Having too many metrics to analyze can cause confusion and random fluctuations. It is more helpful to decide on a few that are significant to gain useful insight.
- Retesting is an important way to solidify your data and make sure you are making the correct decision.
Tips for Getting the Most Out of Your Tests
Like all randomized experiments, there are some variables that can impact your results. If you are testing parts of a website, for example, one of these variables would be the number of participants that are using a mobile device compared to a desktop. Although the groups are randomized, this can sway your results if you do not split them up equally amongst the groups in a process known as blocking.
A large appeal of A/B testing is their simplicity, however, a mistake that many individuals running these tests make is only testing two variables at a time and then sequentially testing other factors such as typeface on top of whichever test “won” first (for example if a blue colored button yielded more clicks than a red one). According to Kaiser Fung, who founded the applied analytics program at Columbia University, this way of testing is not optimal, as it does not measure what happens when factors interact. Although users may prefer a blue button over a red one, when combined with your typeface, they might have a different opinion. The best way to avoid this problem is by doing multivariate testing, meaning your A/B test may end up being an A/B/C test to test multiple variants at the same time.
A/B testing is essential in understanding how your customers interact with your website. Running these simple tests helps you gather data that will help you improve your website and boost your sales. However, it’s important to avoid common mistakes and to be sure to interpret the results correctly in order to make the most of your testing. With these tips in mind, get started on your own A/B tests and see how they can benefit your business!
