How to A/B Test Email Campaigns to Improve Performance
A/B Testing Your Emails: What to Test, How to Do It, and Why It Works
In the fast-moving world of digital marketing, open rates remain one of the most reliable indicators of email performance. They serve as the first line of engagement – if recipients aren’t opening emails, they’re not clicking, converting, or connecting with the brand.
But open rates are more than just a metric. They reflect the trust and interest a subscriber has in a brand’s communications. They also impact sender reputation, deliverability, and long-term list health. For marketers looking to get more from every send, improving open rates is one of the highest-leverage tactics available.
The Value of Testing in a Crowded Inbox
Recent studies suggest the average person receives over 100 emails per day. Standing out in that clutter requires more than just good design or clever copy. Even small changes—such as the time a message is sent or the way a call to action is phrased—can influence whether a subscriber engages or scrolls past.
According to Mailchimp’s 2024 benchmarks, the average open rate across industries sits around 34%, with click-through rates averaging 2.9%. Yet marketers who consistently run A/B tests often see performance gains of 10% or more over time. These improvements may not seem dramatic at first, but they compound with each campaign, especially for companies sending to large lists.
Testing eliminates guesswork. It transforms opinions into evidence, giving marketing teams confidence to iterate and improve without fear of making the wrong call. And because email results are typically easy to measure, it’s one of the most accessible and effective channels for experimentation.
What Can (and Should) Be Tested
A/B testing works best when it’s focused and controlled. Rather than overhauling an entire campaign and comparing two completely different emails, it’s more effective to isolate one variable and measure its impact. The most commonly tested elements tend to fall into three categories: subject lines, content, and timing.
Subject lines are a popular starting point. A slight rewording—such as posing a question rather than making a statement—can increase open rates significantly. Marketers also test personalization (e.g., using the recipient’s first name), word order, emoji use, urgency cues, or length.
Content variations are useful for testing body copy, imagery, layout, calls to action, and even sender names. These changes influence not just whether the email is opened, but whether the recipient clicks and converts. For example, testing two different CTA buttons (“Shop Now” vs. “See What’s New”) might reveal which one drives more engagement.
Timing is another area with significant potential. Testing different send times across weekdays and hours can help uncover when subscribers are most likely to engage. Some email platforms even offer send-time optimization tools, but manual testing can still offer valuable insights for brands with consistent send schedules.
Setting Up an Effective Test
Successful A/B testing starts with a clear hypothesis. What do you believe will improve performance, and why? This could be something simple, such as “emails with a personalized subject line will have a higher open rate than those without.”
Once the variable is chosen, both versions of the email should be identical in every other way. This ensures any difference in performance can be attributed to the change being tested. For example, if you’re comparing subject lines, the email content, layout, and send time should remain exactly the same for both versions.
Sample size is also important. Small lists or short tests might produce misleading results. To achieve statistically meaningful outcomes, marketers should use a large enough audience and allow the test to run for a full engagement cycle—usually at least 24 to 48 hours. Many ESPs (email service providers) offer built-in testing tools that automatically calculate statistical significance and roll out the winning version to the remaining recipients.
Avoid testing too many things at once. Multivariate testing (where multiple variables are tested simultaneously) is more complex and better suited for high-volume senders with advanced analytics capabilities. For most teams, simple A/B tests run consistently over time are more practical and just as effective.
Why A/B Testing Works
The biggest benefit of A/B testing is that it transforms email marketing into a process of learning and refinement. Instead of relying on opinions or copying competitors, marketers build a knowledge base rooted in data from their own audience.
For example, one brand might discover that their subscribers prefer plain-text emails over image-heavy designs, while another finds that urgency-driven subject lines consistently outperform softer messaging. Without testing, these insights remain hidden and opportunities are missed.
A/B testing also helps mitigate risk. Rather than rolling out a major change to an entire list, marketers can try it on a smaller segment first. If it works, great. If not, the impact is minimal. Over time, this approach creates a steady cycle of feedback and improvement that compounds with every campaign.
The practice also reinforces alignment between creative and performance teams. Writers, designers, and marketers can use testing results to collaborate more effectively, focusing on what works rather than
Common Pitfalls to Avoid
Despite its simplicity, A/B testing can lose effectiveness when not managed carefully. One of the most frequent mistakes is changing more than one element at a time. This creates ambiguity and makes it difficult to attribute results to any single factor.
Another issue is ending tests too early. Just because one version is leading after an hour doesn’t mean it will win once a larger segment engages. Patience is essential. Allowing a test to run for at least 24 hours (or longer for less frequent campaigns) helps ensure the outcome reflects real subscriber behavior.
It’s also important to resist overfitting. A single test might show a certain subject line performed better, but that doesn’t mean it will always be the case. Consistent testing across different campaigns and segments is key to spotting reliable trends.
Finally, some marketers run tests but fail to act on the insights. A/B testing only adds value when the results are reviewed and used to shape future campaigns. It’s not just about proving one idea works—it’s about building a system that helps every email perform better than the last.
The Path to Continuous Improvement
A/B testing isn’t a one-time tactic. It’s a mindset. Marketers who treat every campaign as a chance to learn something new consistently outperform those who rely on assumptions or outdated best practices.
Even when results don’t show a clear winner, testing still provides useful information about what your audience responds to (or doesn’t.) Over time, these lessons form the foundation of a smarter, more responsive email strategy.
As inboxes grow more competitive and customer expectations rise, the ability to experiment, analyze, and adapt becomes a defining skill for marketers. A/B testing offers one of the most accessible and impactful ways to do just that.
In a channel where every open, click, and conversion counts, taking the time to test could be the difference between being ignored and being remembered.
Smarter, More Effective Email Marketing Starts Now
Even the best marketers can fall into these traps, especially when juggling tight timelines, multiple campaigns, and evolving business goals. But fixing them doesn’t require a complete overhaul. With the right strategy and support from a capable email service provider, brands can build smarter, more effective campaigns that truly connect with their audience.
By segmenting thoughtfully, optimizing for mobile, perfecting subject lines, focusing on meaningful metrics, and keeping your list clean, you’ll not only avoid these common mistakes – you’ll outperform brands still stuck in the old habits.