The easiest way to maximize the success of your email marketing content is to conduct A/B tests, also referred to as split tests. Utilizing an A/B test can help your business determine which versions of your email will perform better.

A/B testing consists of changing a single variable within your email marketing strategy and sending a different version of the content to each half of your test audience.

Based on the results of the test, you can evaluate and predict which version of the content will be more successful in the future. However, there are several common mistakes that can adversely affect your results. Keep reading to learn more about how you can avoid them.

Mistake #1: Multiple Variables

In order to use an A/B test effectively and get the best results, only a single variable should be manipulated. If there are multiple differences between A and B, it can be hard to correctly determine which change caused the disparity in performance.

Although it may seem more time-consuming to conduct several tests over a longer period of time, you will have a much easier time analyzing your results if there is only one variable.

Mistake #2: Sample Size

Your sample group should consist of a subset of your entire audience. This way, the majority of people will eventually receive the “winning version.” However, it is important to note that each group, A and B, should still have an equal and significant number of recipients.

Sending both versions to too small of a group will give you statistically insignificant results. Using a sample size calculator will ensure that you are reaching the correct number of people and getting the most accurate results.

Mistake #3: Timing

Many elements of A/B testing are related to the timing of your tests. Make sure you aren’t testing too early. Run your campaign and send out content ahead of time to provide a baseline before you make changes. This way, you will have data to compare to your results. Without identifying the control, it will be much harder to compare the results.

Furthermore, don’t end your testing too soon. Using data collected over a few days, rather than weeks, will provide you with convenient data, not representative data. If you feel that a test has failed, or isn’t providing you with the anticipated results, let the test continue to run. You never know what data the test will ultimately provide until it has run its course.

Mistake #4: Lack of Focus

A common mistake when A/B testing is failing to identify the goal. One of the most important steps is choosing a primary metric to focus on. Don’t conduct a test by randomly making changes to see what happens. Rather, determine what you are trying to achieve, and then make changes that will help you gather relevant data.

For example, if you are trying to increase your open rates, you could test the effectiveness of subject lines with and without personalization. Determining the purpose of your test ahead of time will make the process more focused and efficient.

Mistake #5: Confounding Variables

Aside from focusing on a single variable for each test, you should also control for confounding variables. These variables are outside influences that may affect the accuracy of your results. An example of a confounding variable is time. If you send version A and version B at a different point during the day, you are unknowingly skewing your data.

If version A is received at a time when recipients are likely to be checking their inbox, while version B is sent at a time when most recipients might be busy and more likely to ignore, you are adding another variable into the mix. To guarantee that your test is valid, send both versions at the same time and control for all other variables that might influence your results.

To Wrap It Up…

When you’re running a test in an effort to improve your email marketing, you don’t want to waste time testing things the wrong way and getting misinformation. We hope you found this post useful so you can avoid these 5 frequently made mistakes at all costs.

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