Published — v. 20

AB Testing

Owned by Former user (Deleted)
Last updated: Apr 26, 2022 by Product team

A/B tests allow you to verify the effectiveness of one or more variations of the same email. In email marketing, the most common A / B test scenarios are:

1) test on two or more variations of the email subject (best open rate)

2) test on the email call-to-action, for example in one email I insert an image and in the other a link (best click rate)

By sending the same email, but with slight variations, you can in fact understand which version of the sending offers a better result in terms of opening rate or clicks.


We suggest you choose to measure your open rate if your email versions differ only in subject matter. A more relevant object produces a higher open rate than everything else.
The click-through rate is best suited if the versions differ in layout, text, or images in the body of the message. In this case, for example, a lighter or darker image can lead to a higher click-through rate.  

Optimize a sending with A/B testing

In general, the A/B test is a technique with which to optimize various pieces of your digital strategy:

  • Web pages
  • Google Ads and Facebook campaigns
  • Direct Email Marketing campaigns.

The target? Increase performance by comparing two versions of the same tested element.

Now let's narrow down the field, and let's see everything there is to know about A/B testing applied to Email Marketing: conducting an A/B test (also called split testing) on ​​an email means submitting two or more different versions of the same message to a sample of recipients, to then analyze the reaction to each version and determine which of the two is more performing in terms of metrics. 


The procedure for doing the A / B test with MailUp is very simple:

  1. Create the two messages on which to perform the test. You can also make changes to a copy of the same message.
  2. From the menu "Messages => Email" select A / B Test.
  3. At the top right select "NEW A / B TEST"
  4. Select the two variants of the message and the percentage of recipients to be used for sending tests
  5. Choose whether to send the message that obtained the best open rate or the best click rate in the case of automatic choice, or choose to manually select the best performing one.
  6. Select how long to wait before making the final sending and choose the recipients.



Three messages will be queued: the two test messages and a third message will be chosen automatically by the procedure based on the best performance obtained or manually. For this reason, the timing of sending the third message is not displayed as it will be calculated directly at the time of sending the final newsletter. It is possible as an extension to create a matrix of variants, for example by testing combinations of different objects and images.

Thanks to multivariate analysis it is possible to analyze multiple combinations without trying them all.


OTHER RESOURCES: