Work with A/B tests
Sitefinity CMS enables you to deliver to your audience different variations of a page and test which variation performs better at making visitors complete a specific goal. You do this by designing variations of page layout, content, and page elements to optimize the page and convert more visitors of your existing traffic.
You create and manage A/B tests in Sitefinity CMS and then you examine reports on test results in Sitefinity Insight. To do this you:
- Create an A/B test and specify:
- The original page to conduct A/B test on
- The duration of the test
- The number of variations of the page you will test
- Traffic distributions between the original page and its variations
- The conversion goal(s) that you want to optimize
- Design variations of the original page:
- Add one or more variations
- Experiment with various page elements, page templates, and page layouts
- Preview variations
- Track and measure test results:
- Examine reports of the current test results in Sitefinity Insight
- Find out the conversion rates of each variation towards the A/B test goals you defined
- Find out the statistical significance of the results
- Choose the variation to replace the original page on your site
Once you start an A/B test, a visitor to your website can see just one variation of the page you want to optimize for the whole duration of the test. You can see test results in Sitefinity Insight only after any of the page variations are visited and data is accumulated. For more information, see A/B testing.
You want to increase the number of website visitors that submit a Contact Us
form and thus collect more contact data. To do so, you define an A/B test on the Contact Us
page, to ensure maximum goal completions on this page, based on the page layout and content. What you do is the following:
- In Sitefinity CMS, set up an A/B test, which lasts for 30 days and serves an alternative version of the page to 50% of visitors. The other 50% see the current original version of the page.
- The new page variation has the Contact Us form in a different location than the one on the original page – instead of below the map, it is displayed above the map.
- The goal of A/B test campaign is form submission.
- Once you start the campaign, you get an early preview of the first results. Clicking on the results link redirects to Sitefinity Insight where the full report is displayed.
- When the duration of the test is over, review the results. The goal completion rate of page variation is higher, and the system highlights that the results are statistically significant. Therefore, you end the campaign and make the new variation the default content for the page.
A/B testing in multilingual mode
When working in multilingual mode, there are two options for the content of your pages:
- Content is not synced, that is, versions of pages in different languages are completely different.
In this case, you can only create and manage A/B tests on pages for the culture, for which you have publishing permissions.
- Content is synced, that is, pages have the same content, translated in different languages.
In this case, when you edit a page in a specific culture, changes are applied to all language versions of the page. For more information, see Manage A/B tests.
A/B testing and personalization
A/B testing and content personalization are two ways to increase conversion rates and engagement. The difference is how you segment your audience. A/B testing is a verification tool to test a hypothesis about the effectiveness of your marketing strategy by split testing it on a large group of your audience. On the other hand, personalization is a process, in which you target specific audience segments to improve their experience with personalized and relevant content.
In Sitefinity CMS, you cannot run A/B tests on personalized pages and vice versa.
NOTE: You can run tests on pages with personalized widgets. However, we do not recommend this option since in the test results you get in Sitefinity Insight, reports do not have statistics of goal completions of variations per user segment and vice versa. Consequently, statistical significance is considerably lowered.