Your visitors, users, and customers are different. They live in different places, speak different languages, access your website from different media, browsers and devices, etc. What resonates with one person, doesn’t work with another one.
Advanced segmentation in A/B testing refers to the practice of dividing your audience into smaller, more specific groups and running A/B tests on each of those groups. By doing so, you can more accurately measure the impact of your changes on each subgroup, rather than lumping everyone together and hoping for the best.
For example, if you segment the results of an A/B test by device type, you may find that customers who access your website from a desktop computer convert much better than average. Whereas people with mobiles and tablets barely convert at all. Perhaps you should take a closer look at how your website is displayed on these smaller devices and test changes to improve it there.
Noticing which segments respond well (or not all) to particular treatments can make the difference of making money or not. In this post we will talk about the steps to follow to implement segmentation in A/B Testing and get more accurate results.
Before Starting Segmentation
When you use segmentation in A/B testing, you divide your audience into smaller groups and test different variations for each group. While this can help you get more accurate and relevant insights, there are also some risks to be aware of that I discuss below.
Firstly, if your sample size for each segment is too small, it doesn’t give you the full picture – you’re only seeing a small percentage of your visitors and it can be hard to get statistically significant results you can rely on. This means you may not be able to draw accurate conclusions from your test results.
Secondly, if you only test variations on certain segments of your audience, you may miss out on insights that could be relevant for other segments. For example, if you only test variations on visitors who have already made a purchase, you may miss information that could be relevant regarding those who haven’t yet. This cherry-picking to find a result is known as selection bias, and it can skew your test results and make them less useful.
Lastly, another risk is complexity. The more segments you test, the more complex your testing strategy becomes. You want to strike a balance between testing enough segments to get relevant insights and keeping your testing strategy manageable.
To minimize these risks, it’s important to approach segmentation in a thoughtful and strategic way. Test only the segments that are most relevant to your business goals and make sure you are not selectively adapting your sample just to find a result you can declare as definitive on an otherwise unclear or unexpected result. Let’s see the steps you should follow.
Step 1 – Identify Your Key Segments
Before you start testing, you need to identify the different segments you want to target. There are many different common segments that can be useful to test on websites.
For example, consider creating geographic segments. By tailoring your website content to specific geographic regions, you can make it more relevant and appealing to your visitors. Thus, you could test different default language versions on your website or different pricing for different regions. Moreover, you could also create language segments and create different A/B test specific only for a group of language speakers.
You can also segment your audience by device. For example, you can test different variations of layouts, navigation, menus and font sizes of your websites for mobile and desktop devices to see which variations perform best on different devices. Or, you can test different feature placements and image sizes for different browsers, such as Chrome, Firefox, and Safari or for different screen sizes or for different operating systems and see what variations performs better in the different segments created.
Traffic source is also one of the most useful segmentation in A/B testing to better know the behavior of your audience: test variations for visitors who come from different traffic sources, such as search engines, social media or email campaigns. For example, you can test different headlines, images and call-to-actions to your visitors who arrive through different paid advertising versus those who arrive through organic search or versus those who arrive through social media.
Finally, you could also create customer segments and test different variations for visitors who are at different stages of their customer journey. For example, you can test different variations of new customers versus repeating customers who have already logged in your website.
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Step 2 – Choose Your Testing Tool
There are many different A/B testing tools available, each with their own strengths and weaknesses. Choose one that allows you to target specific segments of your audience and track their behavior over time.
We strongly recommend you use our product, Nelio A/B Testing, for segmenting your A/B Tests. When creating an A/B test, you have a very complete set of different types of segmentation rules to establish the visitors who can participate in an A/B test. You can segment by URL parameter, referrer, language, location, user login, day and/or time of visit, browser, device type, operating system, window width, cookie, and IP address.
Moreover, with Nelio A/B Testing, you can create multiple segments and include different condition rules for each one. For example, suppose you want to make a test for Spanish speakers but you want to differentiate between those who are Spain and those who are in a different country. You can create two different segments, with all Spanish Speakers located in Spain and a second one with all Spanish speakers located in country other than Spain.
Nelio A/B Testing will also show you an additional segment, called the Default Segment. This special segment includes the results of the union of all segments. In this example, it will include all Spanish speakers.
Step 3 – Create your Test
Creating an A/B test for one or more segments of visitors is very easy if you have selected the proper tool to do so. With Nelio A/B Testing, you start by selecting what you want to test (page, post, menu, headlines, product pricing, theme, CSS style, etc.) and creating some variations (e.g. different layouts, content, or calls to action).
For example, you can create an A/B test of a product of your WooCommerce store and add different variants where you may tweak the product’s original name, short and detailed descriptions, featured image, gallery images, and regular and sale prices.
Once the variants of the test are defined, you must specify the conversion goals.
Finally, you just need to create your segments with the users you want to participate in the test.
And that’s it. Your test is ready to be launched.
Step 4 – Run your Test
Launch your test and see the progress of your test and its results. Make sure you collect enough data to ensure statistical significance.
With Nelio A/B Testing you can see the progress of any test including information about the number of visits and conversion rate in each variant. For product tests you can also get information on revenues.
Step 5 – Analyze Results
Once your test is complete, i.e. you have obtained statistically significant results, analyze the results per segment. Compare them to each other and to the segment that includes all participants. Look for patterns and trends that can help you understand what worked and what didn’t.
For example, you may find that one variation performs better for a specific demographic segment, while another performs better for a different segment. This can provide insights into the effectiveness of the variations for different user groups and help you make data-driven decisions about which variation to implement.
Use this information to inform future tests and optimizations.
To Sum Up
By implementing advanced segmentation in your A/B testing strategy, you can improve the accuracy of your results and make more informed decisions about how to optimize your website for different segments of your audience.
And remember: the more specific and relevant your segments are, the more accurate and useful your A/B testing results will be. So take your time to identify the segments that matter most to your business and tailor your tests accordingly and avoid the risks involved in segmentation mentioned above.
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