Just as a chef may gauge diners' preferences and refine recipes based on a tasting menu with multiple small dishes, email A/B testing presents your subscribers with different variations of content to sample and assess their reactions. The feedback you collect allows you to optimize your email segmentation strategy and start serving tantalizing engagement.
Convenient food metaphors aside (that was just an appetizer), email A/B testing isn’t quite as simple as throwing a would-you-rather content comparison together. It requires intentional planning and attentive organization to help motivate and interpret the best results.
Use these email best practices for A/B testing to increase ROI and inspire messaging that resonates with your recipients, from the start of your campaigns to the very last conversion.
Balancing Your Email Segmentation
All impactful email A/B tests are built atop a foundation of email segmentation. By dividing your audience into segments based on demographics, firmographics, behavior, or preferences, you can ensure that your tests become far more targeted and your content far more personalized.
Remember, relevant content yields the highest returns!
For an in-depth look at this process, take a refresher with our guide to email segmentation best practices.
Once you've properly segmented your audience, you can then design A/B tests that specifically target each segment. For example, you might test different email subject lines for subscribers in different geographic regions, or you might test different product recommendations for subscribers who have previously made purchases versus those who haven't.
A common email A/B testing mistake is segmenting too broadly or too narrowly. Segments that are too broad may dilute the effectiveness of your tests. For example, segmenting all subscribers based solely on their geographic location, such as "United States" or "Europe" is often nowhere near detailed enough to produce useful test results. While leveraging geotargeting for your email segmentation can be valuable for certain types of campaigns, such as localized promotions or events, it may prove ineffective without any further differentiation. Go deeper. Segment these email subscribers based on groups like frequent purchasers, lapsed customers, or subscribers who have recently interacted with a particular product or in-app feature.
Conversely, segments that are too narrow may not provide enough data to draw meaningful conclusions, where the results are only applicable to a small subset of your audience. Suppose you're a travel app running an email A/B test to broad trip planning promotions based on users’ different travel interests and preferences. You decide to segment your email list based on users who have booked a flight to a specific destination within the past month, creating two segments: one for users who booked a flight to "Paris" and one for users who booked a flight to "Tokyo."
While this segmentation may seem relevant to target users for local itineraries or destination-specific content, it's too narrow and specific to yield useful results for the above A/B testing purpose. Segmenting solely based on recent flight bookings overlooks other relevant factors that impact user engagement and response to the email campaign, such as:
- Travel style preferences (adventure travel, luxury experiences, family trips, etc.)
- Age demographics (trip planning habits between Millennials and Boomers)
- Preferred travel season (Test promotions based on users' preferred travel seasons, such as summer vacationers versus winter holiday planners)
- Membership status (free vs. premium users)
- Broader Past Booking Behavior (Compare the response to promotions among users who have booked any trip in the last three months with those who haven't booked recently)
To mitigate these pitfalls, aim for a balance between breadth and specificity in your segments, and consider incorporating a mix of demographic, behavioral, and psychographic factors for a more holistic understanding of your audience.
How Big Should My Test Audience Be?
To ensure the effectiveness of an email A/B test, it's vital to select a target audience percentage with a sufficient number of users, preventing skewed results. Keep in mind that using multiple variants will require a larger percentage of the target audience to ensure adequate distribution of users across each variant.
While the temptation to expose 100% of your audience to your A/B test is understandable, it's important to note that doing so would leave no users in the segment to receive the "winning" variant after testing! Instead, consider setting your email A/B test audience to 25%. This allows for a significant enough sample size to detect meaningful differences between variants while still preserving a large enough audience to receive the "winning" variant once testing is complete.
In OneSignal’s email A/B testing tool, we start all your tests at this number by default to make things a little easier. Your variants will be split up evenly among the percentage you choose.
Confirm Mobile Responsiveness
Don’t make your users work harder than they need to when your email lands in their inbox — chances are that inbox is on their phone. Prior to kicking off your email A/B tests, thoroughly test your campaigns across different mobile devices, including smartphones and tablets, as well as various email clients and operating systems. This testing process helps identify any potential formatting issues or display inconsistencies that may arise on different devices.
Mobile-friendly emails are more likely to be opened and engaged with on mobile devices, enabling you to effectively connect with your users wherever they are in their day and capitalize on the world’s increasing reliance on mobile browsing and shopping. This expanded reach has been proven to increase brand visibility, customer acquisition, and revenue growth for mobile-first businesses.
Ready to dive into mobile responsiveness properly? Our guide to responsive email design covers everything you need to know!
Make the Most of Your Email A/B Testing Software
Email A/B testing looks vastly different, depending on the tools you’re using to do the job. Rather than settling for A/B testing software as an ancillary “add-on” or bonus feature to your current email marketing provider, seek out a testing suite built for optimizing click-through rates (CTR) and achieving custom outcomes with advanced functionality.
For example, OneSignal’s email A/B testing feature allows senders to create up to 10 different email variants, giving lifecycle and growth marketers the confidence needed to optimize email effectiveness and drive CTR.
Once you’re ready to review results, OneSignal gives you a detailed breakdown of your most crucial metrics, including open rate, unique opens, clicks, and CTR.
When you have a moment, we highly suggest checking out this guide on how to optimize email performance through A/B testing, which gets into all the details!
Iterate and Learn
A/B testing requires constant refinement of your campaigns for proper email marketing optimization. As you test, tweak, and test again, you’ll begin to notice patterns leading to improved engagement and conversion rates over time. By systematically testing and optimizing elements such as subject lines, CTAs, and content, you gain a much clearer understanding of your users’ preferences and can tailor email communications to match.
When iterating on email elements, focus on testing one variable at a time to isolate its impact on performance. For example, if you're testing subject lines, keep all other elements of the email constant across both variants to accurately measure the impact of the subject line variation.
Don't be afraid to think outside the box and experiment with innovative ideas in your email A/B testing. Test new approaches to content, design, or personalization to uncover novel strategies for engaging your audience. While it's important to learn from past tests, innovation and creativity often lead to breakthroughs in email marketing performance. Be willing to take calculated risks and learn from both successes and failures to drive ongoing improvement in your email campaigns.
Test interactive content like quizzes or polls and experiment with GIFs and trending memes — your recipients are desensitized and expecting generic marketing communications, even from brands they love. Surprise them with messaging that cuts through the noise and makes them laugh, think, or pause for just an extra moment (ideally all three!)
Monitor Timing and Frequency
Test the timing and frequency of your email sends to determine the optimal schedule for reaching your audience without overwhelming them or causing email fatigue.
Begin by testing basic timing variations, such as sending emails on different days of the week or at different times of day. Monitor open rates, click-through rates, and conversion rates to determine which timing options resonate best with your audience.
Experiment with different email frequencies, such as daily, weekly, or bi-weekly sends, to find the optimal balance between staying top-of-mind with your audience and avoiding redundancies or user irritation. Monitor unsubscribe rates and engagement metrics to gauge audience response to different frequency levels and adjust accordingly.
Unsubscribe rates getting out of control? We have a guide to managing email unsubscribes for just such an occasion!
Use Control Groups
An A/B test control group refers to a subset of your target audience that is not exposed to any experimental changes or variations being tested. Instead, the control group receives the standard or existing version of the product, service, or communication, serving as a baseline for comparison against the test variants. The same way you can’t tell how fast you’re going in an airplane until you pass a nearby cloud, you won’t be able to accurately assess your A/B experiments without a static control group!
Using control groups in email A/B tests provides a reliable baseline for comparison, enabling you to accurately measure the effectiveness of your test variants. By comparing the performance of test variants against the control group, you can gain valuable insights into the true impact of changes on key metrics such as engagement, conversion rates, and revenue.
Additionally, control groups help mitigate biases and external factors that may influence test results, ensuring that decisions are based on solid data and leading to more informed optimization strategies.
Analyze Results Holistically and Integrate Across Channels
It’s worth noting, these email communication best practices have far-reaching effects, beyond the inbox. The best way to generate a consistent and cohesive customer experience is by aligning your various mobile channels with each other.
Multichannel Attribution
Implement a multichannel attribution model to track and analyze customer interactions across email, push, in-app messaging, and SMS. By understanding how customers move between channels and interact with different touchpoints along the user journey, you can identify opportunities to optimize messaging strategies and maximize engagement across your entire mobile ecosystem.
Suppose you conducted an email A/B test to compare two subject lines for a promotional campaign. Variant A emphasized a time-sensitive offer, while Variant B highlighted a specific product category. After analyzing the results, you found that Variant A had a higher open rate and click-through rate compared to Variant B.
Now, to inform your push notification strategy, you can leverage the insights from the email A/B test. Since Variant A performed better and emphasized a time-sensitive offer, you can craft push notifications that complement this urgency. For example, you can send push notifications targeting users who didn't open Variant A email, reminding them of the limited-time offer and encouraging them to take action.
Cross-Channel Insights
Use insights from other mobile channels to inform your email A/B testing strategies. Analyze performance metrics such as open rates, click-through rates, conversion rates, and user behavior patterns from push notifications, in-app messages, and SMS campaigns to identify trends and preferences among your audience. These insights can help you tailor email content, subject lines, and timing to better resonate with your customers and drive higher engagement.
Testing Synergies
Explore opportunities to test synergies between email and other mobile channels. For example, you can conduct A/B tests to compare the effectiveness of coordinated email and push notification campaigns versus standalone email or push efforts. Test variations in messaging timing, frequency, and content to identify the most effective combinations for driving engagement and conversions across channels.
This user referral sequence for the sports betting app Betmate uses OneSignal’s Journeys builder to leverage the strengths of both push and email for a unified (and personalized) mobile engagement strategy.
To see more multichannel use cases in action, we highly recommend checking out Betmate’s full story to see how they achieved a 600% increase in MAU (monthly active users)!
Email A/B Testing For a Mobile-First World
With OneSignal’s email A/B testing platform, finding the winning variant has become less of a chore and more of a score. With the ability to test up to 10 variants at once and view detailed analytics of each test, you gain invaluable insights into your most impactful engagement drivers to optimize email performance.
And you’re in luck! Email A/B testing is available to try right now on our comprehensive free plan!
Get Started for Free
