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What is A/B split testing?

A/B split testing is one of the easiest ways to increase conversion rates and learn more about your audience, but it is still underutilized by many otherwise very switched on, online marketing professionals. This is often because any form of testing is wrongly assumed to be very technical, time consuming and difficult to implement; however this is just not the case.

A/B testing is a simple way to test changes to your page against the current design and determine which ones produce positive results. It is a method to validate that any new design or change to an element on your WordPress site is improving your conversion rate before you make that change to your site code.

What are A/B testing and conversion rates?

A/B testing does pretty much what the name suggests, it tests a control, version A, against a different version, version B to measure which is the most successful based on the metric you are measuring.

In the online world A/B testing allows you to split traffic on your website so that visitors experience different web page content on version A and version B of a page while you monitor visitor actions to identify the version that gives the highest conversion rate. A conversion rate is the rate at which visitors perform a desired action on your site. By testing with live visitors on your site you learn from real users which appearance they prefer.

A/B Testing provided by the Popup by Supsystic

A/B test in Popup plugin involves testing two or more versions of a popup window — an A version (original) and a B versions (the variation) — with live traffic and measuring the effect each version has on your conversion rate. Start an A/B test by identifying a goal for you then determine which popup on your site contribute to the successful completion of that goal.

For example, imagine a blog, that publish the world news. The blog’s ultimate goal is to get more subscribers and increase their popularity.

The “Sing up” button on popup window is the main element visitors interact with at the start of the subscription. Let us assume that making the button more prominent on the popup would lead to more clicks and therefore more subscribers. Using A/B Testing of Popup plugin сreate test popup (version 1) and set a red color for button, then save the test.

Another thing that affects on the subscription is the number of fields that must be filled. So can suppose that reducing to minimum the information which must enter the potential subscriber, would lead to more subscribers. Create one more test popup and disable Name field of Subscription, then don’t forget to save the changes. In main popup leave everything as is.

variation-of-popups

Thereafter all visitors to the blog are bucketed into a variation. They are equally divided between the version 1 with red button, version 2 without Name field and the original popup. A/B testing feature of Popup by Supsystic measures the number of visitors who saw each version of the popup and the number of visitors who subscribed.
Once enough visitors have run through the test, using the Statistics, we can see the results of A/B test – on the graphs, you have the ability to observe the increase of subscribers, also it allows you to know as a percentage of how many people subscribed to each of popups or shared on different social networks.

statistics-popup-by-supsystic

On the graph you can see that approximately with the same number of views of all popups, the number of subscribers is much higher in test versions than the original popup. Especially well observed the growth of subscribers in version 2 of popup.

The results show that 36% of visitors clicked on the red button (version 1), 55% clicked the “Sign up” on the popup without Name field (version 2) and 10% clicked on the original version of popup. Version 2 of test popup led to a significant uplift in conversion rate – 69,1%, while the conversion rate of version1 – 49,1% and original popup only 13,2%.

ab-testing

By measuring the impact that changes have on your metrics such as sign-ups and social shares, you can ensure that every change produces positive results. Quantitative data speaks for itself. You and your coworkers may have hunches about how site visitors will respond to certain design elements; A/B testing  allows you to show visitors several versions of the same popup and let them determine the winner. Constantly testing and optimizing your popup can increase subscribers, social followers, and user generated content, while providing teams with valuable insight about their visitors.

Click here to see example of A/B test