5 Winning Email Marketing Testing Methods- Better Campaign

What are the core email marketing testing methods to build a better marketing strategy? You’ll find out soon. 

Modern email marketers are somewhat like mixologists. They mix up a couple of elements to determine which goes down the hatch smoothly. In email marketing, this process is called A/B testing. 

Although the process is more like trial and error, some email marketing testing tactics can improve your test efficiency. Get familiar with these exciting testing tips we’ve provided below to yield massive improvements.

First, let’s examine the primary question:

What Is A/B Testing In Email Marketing?

A/B testing in email marketing is a way to try different designs and determine which works best. It’s also known as split testing. A/B testing can help you improve the performance of your emails. 

With split testing, you can try out different subject lines, designs, email bodies, or other elements to see what resonates with your audience.  It’s a great way to test out newsletter formats with different images and select the best. 

Best Email Marketing Testing Methods

The split testing tips below will help you set up your email marketing testing methods for success. 

person holding black iphone 4
Photo by Maxim Ilyahov on Unsplash

Set Achievable Goals

Setting goals is always the first important step to activating any process. A/B testing is no different. You need to determine what you want to achieve with your email campaigns and how to measure success. 

When you set your goals, you can structure your A/B testing to achieve these goals. Some marketers make the mistake of testing only one element of an email. 

For instance, the subject line or CTA alone. It’s best to try different aspects of your email, including the offer your email promises (for example, an ebook). 

This is how to cover more ground and achieve better results. 

Test Two Different Elements

A/B testing is a great way to test two different variations of email marketing campaigns. 

It’s about comparing different email variables to pick the most effective one. 

Commonly tested email elements include subject lines, body copy, call-to-action buttons, images, and more. 

Once you’ve decided on the aspects you want to try, it’s time to create two versions of your email. The performance of each campaign hints at which one connects better with your audience. 

Apply The Result To Your Next Campaign

Plan your action points ahead of each test. This encourages you to implement necessary measures based on the result of your A/B test. 

For instance, testing two variations of CTA means splitting your subscribers into two (A and B). Test the two versions on each group of subscribers. 

Check out the email with better performance email and send it to the other half of your subscribers. 

Test New Newsletter Format

You’d be shocked at how much positive change you can achieve with a new newsletter format. The new structure could be a change in the length, new images, more engaging words, etc. 

Note that your test results may vary depending on the goal of your email per time. 

That leads us to the next email marketing testing strategy. 

Conduct Tests Over And Over Again

A/B testing isn’t a one-off. You need to keep conducting a series of tests, as the results may change depending on the purpose of your email. Or the stage of each customer in their buyer’s journey. 

Moreover, you can discover better options that outperform your previous result. Remember, marketers never stop learning. 

Wrapping Up

A/B testing in email marketing allows marketers to improve their marketing tactics. 

The email marketing testing methods in this article are tested and proven. They help you create better campaigns that inspire your audience to act in favor of your brand

Testing should be an ongoing process to ensure your emails reach their full potential. Keep experimenting and tweaking until you find what works for your audience. 

The right strategies will certainly maximize the effectiveness of your email marketing efforts. 

Abir is a data analyst and researcher. Among her interests are artificial intelligence, machine learning, and natural language processing. As a humanitarian and educator, she actively supports women in tech and promotes diversity.

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