Garner Better Results By A/B Testing your Campaigns

A/B testing 2020 in email marketing is the process of sending one variation of your campaign to a subset of your subscribers and a different variation to another subset of subscribers, with the ultimate goal of working out which variation of the campaign garners the best results. By testing different campaigns for the same audience, you can replicate the better performing campaigns for future campaigns. This allows the email to resonate better with the audience, improves their experiences with the data collected, and drives better results for your campaigns.
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One example includes Campaign Monitor’s A/B test on their email layouts, which resulted in a 127% increase in their click-through rates. Hence, it is important to test your campaigns regularly. Here are some best practices for you to understand your users better through A/B testing:
1. Set a goal for your test: Before conducting your A/B test, it is important to define the metrics you would like to use to measure the success of the tests. To begin, choose one Key Performance Indicator (KPI) to monitor your results, this can include benchmarks such as higher click-through rates, lower bounce rates or a decreased unsubscriber rate to determine which test is the most successful. According to Mailchimp, Government Agencies should be aiming for at least a 3.99% CTR and an average of 0.33% bounce rate!
2. Choose the right variable to test: There are a number of key areas you can test which includes your subject line, campaign design, headlines, call to action, etc. Choose the one that suits your campaign the most, based on your user analysis. According to OptinMonster 47% of your subscribers will open your email based on the subject line of your email. Meanwhile, 69% of users will mark your message as spam solely based on your subject line.  One way you can test your subject line is by personalising it to include your subscribers’ name vs. a more general subject line to see which works better for your recipients. 

 

 

One way you can test your subject line is by personalising it to include your subscribers’ name vs. a more general subject line to see which works better for your recipients. 

 

 

Another test includes the usage of emojis. Do emojis live up to the hype? There’s only one way to find out!

 

 

You can also test the placement of your content. For example, would placing the benefit right at the top or at the bottom work better to attract the users’ attention?

 

 

Additionally, A/B testing visuals also lets you determine how you would want to design your campaigns in the future. This can be testing the presence of buttons, images, etc!

3. Univariate & Multivariate Testing: If you wish to see the impact of one element on your campaign’s success, you should change only one variable at a time. For example, testing between your own name and your agency’s name in the ‘from’ section  However, if you wish to see how multiple variables interact with one another to affect your campaign’s success results, another method would be through changing multiple variables at once. For example, including your personal name so they know who it’s “From:” exactly, in combination with a subject line that contains an emoji vs using your company name with an all-text subject line.  
Fortunately you can experiment and see which test form works best for you! If many elements of your design can be changed at the same time to improve a single conversion goal, then use multivariate testing. If there is low traffic for your page that you want to test, consider using an A/B test instead of a multivariate test to obtain more measurable effects on your conversion goal
4.Focus on conducting A/B tests on your frequently sent emails first: Start by testing your emails that you frequently send your users, this can include monthly newsletters, etc. This is to reach a larger audience and start with users who are more familiar with your platform,  and who may be looking for a change!

5. Using a representative sample size: In order to get more statistically significant results, you can stick to the 80/20 rule where you focus on the 20% that will bring you 80% of the results. Send 10% of your audience test A and another 10% of your audience test B, before sending out the remaining 80% the variation that performed better.  To ensure accuracy in test results, ensure that your test sample size is representative with at least 50 people for each segment of the test.

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