What is A/B testing in Email Marketing?

An effective email marketing campaign is the core of many online marketing strategies, and a/b testing is the best way to make an email campaign as effective as possible. The following is an explanation of exactly what a/b testing is in email marketing and how you can properly implement this practice in your campaigns.

What is A/B Testing in Email Marketing?

A/B testing compares two similar versions of the same content to see which is more effective. The method is used in almost all online marketing channels (e.g., web copy, pay-per-click ads, social media posts, and so on), and it is especially useful when writing email marketing campaigns. The method is also known as “split testing,” and it’s used outside of online marketing as well.

When Should You Use A/B Testing for Email Campaigns?

A/B/ testing is helpful anytime you want to make an email marketing campaign as effective as possible – and have time to perfect the campaign. It’s extremely useful when creating an introductory email series that will be sent to every new subscriber, but it’s less helpful when writing a holiday-specific email. By the time you have data on the holiday email, you’ll be writing for the next holiday that’s coming up. Once testing on an introductory series is complete, you can use that data to increase conversion rates among newly subscribed targets.

Whenever you want to conduct a/b testing for a campaign, the testing should be started as early as possible. Having data quickly will let you improve the campaign sooner rather than later. Additionally, testing should be ongoing for most campaigns. While you might identify the major features of a campaign early on from initial a/b tests, more tests can be continued to identify smaller changes that may still have an impact on open, click-through and conversion rates.

How Do You Execute Email Marketing A/B Testing?

To start an email marketing a/b test, decide whether you want to test the entire email or just a portion of it. It is generally best to isolate only one variable at a time, but if you are launching a new campaign, that variable may be a major item.

Set up two emails that have the changed variable text, and get ready to send the emails. The emails should be sent simultaneously and randomized across your target audience, so you can avoid other variables (e.g. time of day, gender) that could skew data. The larger your a/b testing group, the more comprehensive your data will be.

As you gather data, continue to compare until one of the two versions shows to be more effective. Consider open rate, click-through rate and other metrics as you compare – and follow the data. Once you have an improved email thanks to your a/b testing, “rinse and repeat” to improve another variable in the email marketing campaign.

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