Newsletters and email campaigns are an incredibly effective way to create repeat customers, gain new ones, and increase your profit margins. By agreeing to receive emails from you, everyone on your list has expressed an interest in your brand or product. Converting that interest into a sale should be as easy as shooting fish in a barrel.

While it is true that converting sales from an email campaign is easier and more cost-effective than going after cold traffic, it is still critical that you are optimizing these emails to properly target your audience and create the greatest number of conversions possible.

A/B testing allows you to do just that! With A/B testing, you can test two different versions of an email to see which one is most impactful. Send half of your email list variation A and the other half gets variation B. The one that meets your target criteria, be it open rate, click-throughs, or conversions, is your “winner.” This information gives you valuable insight into how your audience is thinking and what appeals to them.

How to A/B Test Your Emails

To create a successful A/B email test, there are some things you need to keep in mind.

What to Test?

First, you need to decide what you will be testing. There are likely many variables you want to test but if you test them all at one time, you will never be able to determine which one had the most impact. For the most accurate results, stick to testing one thing at a time. Things that are tested most frequently include a subject line, message layout, images, call to action, personalized salutations vs formal ones, and the name of the sender.

What you decide to test will be determined by what you want to learn. Testing one call to action against another, for example, will have a direct impact on your click through and/or conversion rates. Testing different subject lines will impact your open rate. Study your current analytics to determine which piece should be tested first.

Sample Size

Now that you have decided what you are testing, it is time to decide how many people will be a part of the test. The larger your test pool, the more accurate your results will be. Lots of times, it is worth testing your entire list. But if you have a massive list and are paying by the email, it may be better to test on a smaller group. Another time a smaller sample might be a benefit is if you are testing something risky or way outside of the box. A small sample can minimize damage if your idea does not go over well. No matter the size of your sample, make sure the recipients are chosen at random. Randomness will produce the most accurate results.

Define Success

Before you begin your A/B testing, you need to define what success looks like. If you are testing your open rate, for example, what do you see as an acceptable result? To determine this, you need to know what your numbers have been in the past. What is your previous open rate? If you are unable to see an improvement after one A/B test, you might consider running another one with different variables.

Remember…

When sending your emails, you want to make sure that your voice, tone, and branding are consistent with your website. If your site looks dramatically different than your emails, customers may feel confused about you as a brand. Stark differences between the two can also leave your customers wondering if the link you provided has even taken them to the right place. If people feel confused or uncertain, they are not likely to buy from you.

If you are offering a sale or discount in your emails, you need to make sure it is easy to find the deal on the site. Even perfectly optimized emails will fail to convert if your site is not clear to your visitors.

Running an A/B test for your email campaigns is a powerful way to understand your customers. By testing different variables, you will be able to determine what connects with your audience and what is likely to be effective in your advertising campaigns going forward. Take advantage of these insights to stay ahead of your competition and build a happy and loyal customer base.