What is A/B testing?


A/B testing, also known as split testing, is sending 2 different versions of your email to your sample contacts in the email lists/segments to see which version performs better. The version that receives more engagement is then sent out to the rest of your contacts. You can read more about A/B testing here

In this article, you'll learn how to create an A/B testing campaign in Mailmodo. 


Your A/B test campaigns will be created in a series of steps. You start off with deciding what you want to test e.g. subject line or content and then select your lists/segments. You then set up the criteria to automatically decide which version should be selected as the winner and then you review and send the campaign. 


Step 1: Start with your A/B test creation 


After selecting the template and entering campaign details, to begin creating your A/B test campaign, click Create A/B test at the bottom of the page


Step 2: Choose what you want to test


You can select to test any of the variables i.e. subject line or content. If you choose content A/B testing you will be able to select 2 templates - Version A and Version B. While doing content A/B testing, we recommend preparing your template versions in advance so that you can select them easily here.  




Step 3: Select your contacts 


Select the segments/lists for your campaign and move to the next step to configure. 



Step 4: Decide the winning criteria for your A/B test 


In this step, you configure the sample size of your contacts that will receive your A/B tests, the winning criteria, and the time for which your A/B test should run before deciding the winner automatically. 

You can choose the winning metric as Open rate or Click rate based on your test. In case of a tie, we always select Version A as a fallback winner. 

You can review the campaign details and test the emails in the next step and schedule your A/B test campaign successfully. Once the campaign is scheduled, you will start seeing the A/B test performance and winner for your campaign in the A/B test dashboard.

Fallback Version as Winner