Optimize clickable elements with A/B testing email

An A/B test allows marketers to compare two or more versions of digital content – such as a website, a landing page or a marketing email – and determine which version performs better based on the objective they want to achieve (for example, to get higher open rates or conversion rates).

To increase your email click rates, test different versions of the elements within your email. For example, you can test the call-to-action (CTA) buttons, as they usually have the biggest impact on the conversation rate of your campaign. But you can also test the wording, the image, the products or services promoted, and more. In order to be able to identify the element impacting your results, only test one version at a time. Test the different versions on a sample of the contact list, and send the version generating the highest click-through rate to the rest of your subscribers to optimize your results.

How to create an A/B test

Make sure to use an Email Service Provider (ESP) that offers an A/B testing feature, and set up your test:

• Customize your campaign by adding the appropriate subject line, wording, images, etc. Once this campaign has been created, you have the version A of your test. 
• Then, create a new version of your campaign (which will be a copy of the version A) and only change one variable within your email – such as the wording, the positioning, or the color of your call-to-action button. Once it’s done, you have your version B. 
• Create as many versions as you want. For example, you can create a version A, B, C, and D to test four versions of your call-to-action button. 
• Once you have created different versions of your marketing campaign, set the test sample size and the criteria for selecting and sending the winning version. Here, the winning version will be the one generating the best click rate. 
• Schedule when the test sample and winning version will be sent. Once the A/B test has been completed, you will be able to view data and to gain insights as to what your customers liked or not about your different versions, and improve future email campaigns.