Optimize Your Email Marketing With A/B Testing 

How to Use A/B Testing to Optimize Your Email Marketing

November 2, 2023

As inboxes keep filling up, marketers are constantly trying to stand out. From personalization to limited-time membership offers, they use many strategies and techniques to get the attention of their industry, but what really works? Instead of making assumptions, take a data-driven approach. A/B testing your email campaigns can help you not only determine what is and isn't working in your email strategy but also achieve better results without increasing expenses. 

The value of A/B testing   

A/B testing, also known as split testing, involves comparing two different email versions to determine which performs best. The most common way marketers utilize A/B testing is by sending an email with two different subject lines to see which one gets the highest open rate; however, there are many variables to test. Ultimately, the goal of A/B testing is to understand what drives email engagement and conversions. From these learnings, marketers can modify and make their email marketing more effective. It's a trial-and-error process, but a sure-fire way to prove what works.  

Blog_A-BTesting-Email-Graphic1

Best practices 

When setting up an A/B test, be sure to follow these guidelines: 

1. Isolate test variables 

When conducting A/B testing, it’s crucial to ensure that test variables are isolated and not simultaneously affecting the same email performance metrics. For instance, it is acceptable to test one variable's impact on email open rate and another variable's impact on click-through rate. However, testing two variables that both influence the open rate should be avoided. Similarly, comparing different creative layouts or button styles within an email is acceptable, but not within the same email. Testing multiple variables concurrently will make it difficult to identify which variable had the greatest impact. 

2. Keep a control version  

Once you get started with A/B testing, it's important to maintain a control version of each email. Although the goal of A/B testing is to find out what generates the most engagement, that doesn't mean you should delete your original emails. You may want to use them again in the future, or you may want to refer to them when updating your marketing strategy. Having a control version of each email helps you keep track of what’s been tested and what hasn’t yet.  If you delete or overwrite your original messages, you won't be able to go back and pick out new elements to use as variables.  

3. Randomize your subscribers 

It's important to randomly split up your subscriber list to conduct A/B testing. By using randomization, you ensure that the test groups are representative and unbiased, allowing accurate comparisons between different variations of your email campaigns. This practice minimizes the risk of skewed results due to factors like audience preferences or external influences. Ultimately, it enables you to make data-driven decisions and optimize your email marketing strategies for better performance and higher chances of engagement.

Email variables

When conducting an A/B test, there are several variables to experiment with but for accuracy, it’s best to measure one variable at a time. Additionally, having a statistically significant sample size and established tracking metrics are important to yield the best results. 

Subject lines 

  • Test different lengths, such as short and concise vs. longer and descriptive. 
  • Try different approaches, such as posing a question, creating a sense of urgency, or highlighting a benefit. 
  • Avoid using too many emojis, all caps, or spam language. 

Preview text (salutation) 

  • Test different salutations or preview text to entice recipients to open the email. 
  • Experiment with personalization, including using the recipient's name or location. 
  • Evaluate different lengths of text or tone of voice on their level of engagement.  

Sender name 

  • A/B test using a person's name vs. a company name as the sender. 
  • Try using a combination of both to see if it affects open rates or trustworthiness. 

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Visuals   

  • Experiment with different types of visuals, such as product images, lifestyle photos, or illustrations. 
  • Assess the use of videos, GIFs, or interactive elements to see their impact on metrics. 

Design elements  

  • A/B test different email designs, including the layout, color scheme, and overall aesthetic. 
  • Switch between including or excluding certain design elements like borders, dividers, or background images.

B2B_Blog_AB testing_graphics

Copy formatting  

  • Test the effectiveness of different font styles, sizes, and colors on readability and engagement. 
  • Experiment with bolding, italicizing, or underlining key phrases or words to draw attention. 
  • Try breaking up the text differently, shorter paragraphs or utilizing callout boxes to optimize readability. 
  • If you often use only plain text or HTML, determine which you should really be using by testing both to see which one your subscribers are more likely to engage with. 

Litmus_HTML

Litmus HTML email

Offer structure  

  • Test different ways of presenting offers, such as percentage discounts, free shipping, or buy-one-get-one deals. 
  • Experiment with different messaging strategies, such as scarcity or exclusivity, to see what resonates best. 

CTA

  • Play around with CTA text, colors, sizes, and placement within the email to optimize click-through rates. 
  • Experiment with wording, using action-oriented phrases or personalized CTAs to drive engagement.  

B2B_Blog_AB testing_CTA

Timing  

  • A/B test sending emails at different times of the day or days of the week to find optimal open and click-through rates. 
  • Consider testing specific triggers, such as sending emails immediately after a user takes a specific action, like signing up or making a purchase.    

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Conclusion  

A/B testing offers valuable insights for optimizing email marketing performance and engagement. By testing variables like subject lines, content layouts, timing, and more, businesses can draw actionable conclusions to improve future results. Continuous testing and optimization are key for delivering personalized content and building stronger subscriber relationships. 

 

 

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