Shiny GIFs, flashy offers, perfectly crafted subject lines, and still? no response. There’s no one size fits all formula to creating a high-converting email again and again, and anyone who tells you otherwise is selling a myth.
Every brand’s email list is different, and while there are general best practices, what works for one audience won?t necessarily work for another.
No one knows your audience better than your audience itself.
So while a beautifully designed email packed with animations and bold visuals might look stunning to you, is it really the best for your subscribers? Your emails aren’t for you they’re for your customers. That’s why it’s essential to let the data guide you.
A/B testing helps you answer questions that no “best practices” guide can. Is soft selling your product better than using an urgent, hard-sell tone? Does your audience respond more to minimalistic emails or visually rich designs? Do your subscribers engage better with emails sent at 8 a.m. or 3 p.m. With A/B testing, you’re no longer guessing you’re making decisions based on data. According to a study by Litmus, businesses that A/B test every email see 37% higher ROI than those that never do the A/B test.
Most e-commerce brands stop at the basics when it comes to A/B testing. They search for what to A/B test, like subject line variations, emoji use, or whether to personalize with the recipient’s name. But they often overlook more strategic questions: How long should an A/B test run? When is the right time to A/B test? Should you test your entire email list or focus on a segment? In this blog, we’ll dive into the best A/B test ideas, provide a framework for running tests successfully, and highlight common mistakes to avoid so you can get the best possible results.
How to Run an A/B Test in 5 Simple Steps
1. Identify which test will bring you the biggest win
There are countless A/B tests you could run, but not all are created equal. When deciding what to test, focus on the ones with the biggest upside for your e-commerce store. Here are three factors to consider:
- Ease: How simple it is to implement and measure the test results.
- Potential Lift: The potential increase in revenue if the test succeeds.
- Impact on KPIs: How much the test could move the needle on your key performance indicators, like open rates, CTR, or conversions.
2. Note Down Your Hypothesis
Once you’ve identified the problem, create a clear hypothesis. This helps you stay focused and ensures you measure the right outcome.
Example:
We believe that using personalized subject lines will increase open rates compared to generic subject lines because our audience responds well to tailored messaging.
Writing down your hypothesis makes the test more intentional and keeps you focused on what you’re trying to learn. Plus, it’s always fun to see if you were right!
3. Test Your Hypothesis
This is the part where you actually run the test. You’ll create two versions of your email:
Version A: Your control, or the original version.
Version B: The one with the change you’re testing.
Split your audience in half, and send one version to each group. And let it run long enough to get a meaningful result.
4. Decide on Your KPI
Once you have your hypothesis, you need to decide on a single KPI to measure its success. Without a clear metric, it’s impossible to understand the impact of your test or make informed decisions.
Choose just one KPI to focus on. Typically, this will be either open rate or click rate, as revenue can also be influenced by factors on your website.
- Open Rate: Best for testing elements visible before the email is opened, like the sender name, subject line, or preheader text.
- Click Rate: Ideal for testing elements that come into play after the email is opened, such as the CTA, email layout, or design.
By selecting the right KPI, you can ensure your A/B test delivers actionable insights without unnecessary complexity.
5. Analyze the Results
Once your test is complete, it’s time to dive into the data. Which version performed better, and why? Stick to the metric you set out to measure, whether it’s open rate, CTR, or revenue.
Document the results, including what you tested, the audience, and the outcome. Use a simple spreadsheet or a dedicated testing tool to track your experiments over time. Here’s the template we use to record the AB tests we run for our e-commerce partners.
6. Test Again After a Few Months
A/B testing is an iterative process. What works today might not work tomorrow, especially as audience preferences and behaviors evolve. Plan to revisit key elements every few months to ensure your email campaigns stay optimized.
Why Test Again?
- Seasonal trends, market shifts, or new products can impact performance.
- Continuous testing allows you to refine strategies and build on past successes.
- New subscribers may have different preferences and continuous AB testing can help you realize what works best even as your list continues to grow.
If you want a step-by-step tutorial of how to AB test your email campaigns check out my free Youtube tutorial by clicking on this link.
AB Testing Best and Worst Practices?
1. Test Only One Variable at a Time
One of the most common mistakes in A/B testing is trying to test multiple elements simultaneously. If you’re changing your subject line, CTA, and design all at once, how do you know which change influenced the outcome? To get clear, actionable insights, stick to testing a single variable. For example, if you’re testing personalization in subject lines, you might compare “Your Exclusive Deal Awaits!” with “John, Your Exclusive Deal Awaits!” By isolating the variable, you can confidently determine whether personalization improves open rates.
That said, it’s okay to test multiple variations of the same element. For instance, you could test up to four different subject lines in a single email campaign to find the most effective tone or style. Just be careful not to overcomplicate things testing too many variations at once can dilute your results and make analysis more challenging.
2. Run Your A/B Test for the Right Duration
A/B testing is essentially a statistical experiment, and the accuracy of your results depends on the size of the audience being tested. If your sample size is too small, the results may not reflect the behavior of your entire audience, leading to misleading conclusions.
Imagine this: You run an A/B test on a new email subject line. On the first day, 10 people open the email, and all 10 click through. It looks like a huge success! But over the next week, as the email reaches 2,000 more recipients, the open and click-through rates plummet. If you had ended the test on day one, you’d have thought the subject line was a winner, even though the larger sample tells a completely different story.
This is why statistical significance is so important. It ensures that the results of your test are not due to random chance. A result is considered statistically significant when it’s highly likely that the difference between variations is real and can be replicated.
What Does Statistical Significance Look Like?
Platforms like Klaviyo categorize your test results to make this easier to understand:
Source: Klaviyo Helpdesk
- Statistically significant: A clear winner emerges with strong evidence to back it up. You can confidently apply these insights to future campaigns.
- Promising: One variation is performing better than the others, but there’s not enough data yet. Consider running additional tests.
- Not statistically significant: One version slightly outperforms another, but the margin is too small to draw reliable conclusions.
- Inconclusive: The data isn’t clear enough to determine a winner. In this case, you may need a larger audience or longer test duration.
To achieve statistically significant results, aim for a 95% confidence level, which means there’s only a 5% chance the results are due to randomness. This usually requires testing until each variation gets at least 100 conversions, but the exact timeline depends on your audience size and the metric you’re measuring.
For example, if you’re testing open rates, you may see results quickly since people tend to open emails within the first 24-48 hours. But if your goal is to measure placed orders, you’ll need to allow more time for recipients to make a purchase decision. Align your test duration with the behavior tied to your chosen metric for the most accurate insights.
3. Don’t A/B Test During Q4 or Holiday Seasons
The holiday season is a critical time for execution, not experimentation. Q4, with its heightened traffic and urgency, tends to skew data, making it a poor period for running tests. The behaviors you see during Black Friday or Cyber Monday often don’t reflect your audience’s usual habits, so any insights you gather may not apply to the rest of the year.
Instead, reserve your A/B testing for quieter months when audience behavior is more stable. Use those learnings to fine-tune your strategy so you’re ready to apply proven tactics during peak periods. For example, you might test subject lines or CTA wording in February or March and use the winning versions in your holiday campaigns.
4. Focus on Low-Effort, High-Impact Elements First
When you’re new to A/B testing or working with a tight timeline, start with quick wins. Testing low-effort elements like subject lines, CTA text, or emoji usage can provide meaningful insights without requiring extensive setup. For instance, testing “Shop Now” versus “Claim Your Offer” in a CTA is far simpler than redesigning an entire email layout and the results can still significantly impact your click-through rate.
Once you’ve gathered data on these simpler elements, move on to higher-effort tests, like experimenting with email formats, layouts, or visuals. These tests often require more time and resources but can lead to larger shifts in performance. The key is to build on your learnings incrementally, starting small and scaling your efforts as you go.
5. Don’t Edit a Live Test
It’s tempting to tweak a variation mid-test if it’s underperforming, but this undermines the integrity of your results. Editing a live test introduces a new variable, making it impossible to attribute outcomes to the original change you were testing.
If you notice a significant issue like a broken link or a typo end the test, fix the error, and restart. Otherwise, let the test run its full course, even if one variation seems like an early winner. The most reliable insights come from seeing the test through to completion.
10 AB Test Ideas To Boost Your Email Campaigns?
Over the past six years, we’ve sent over 500M emails and run hundreds of A/B tests annually. Based on this extensive experience, these are the most impactful A/B tests we’ve identified and typically implement for new email marketing clients because they consistently deliver results.
1. Smart Send Time Test
Timing is everything when it comes to email campaigns, and Klaviyo’s Smart Send Time feature can help you uncover when your audience is most likely to engage. Instead of guessing or relying on generic benchmarks, Smart Send Time uses data to identify the optimal hour for each recipient.
Klaviyo’s exploratory phase distributes emails across a 24-hour period to analyze engagement patterns. Once the best time is identified, a focused phase narrows down the window further, allowing you to refine your timing. Ultimately, this feature automates email scheduling so your campaigns always land in inboxes at the most effective time.
To set up a Smart Send Time test in Klaviyo, your email list should have at least 12,000 recipients to generate statistically significant results. This minimum list size is required to ensure Klaviyo has enough data to analyze engagement patterns effectively during the exploratory phase of the test.
If your list is smaller, consider running a manual A/B test to compare send times at different intervals. While it won’t offer the same level of automation as Smart Send Time, it can still provide valuable insights into your audience’s behavior.
2. Short Copy vs. Long Copy
Test whether your audience prefers concise, to-the-point messaging or detailed, story-driven content. Short copy often works for promotions, while long copy may perform better for storytelling or high-ticket items.
3. Test Subject Lines on Your Top 3 Flows
Email flows like your welcome series, abandoned cart, and post-purchase emails are critical drivers of revenue but they’re often overlooked when it comes to A/B testing. Experiment with subject lines on the first three emails in these flows. For example, test personalized subject lines like “Welcome to Boxxy, Rachel” against generic subject lines like “Welcome to Boxxy” These flows are highly automated, so optimizing them can have long-term compounding effects on revenue.
4. Email Popups: “10% Off” vs. “Get an Exclusive Discount”
Compare direct offers like “10% off” with curiosity-driven ones like “Get an exclusive discount” to see which captures more sign-ups. Test whether your audience prefers clarity or intrigue.
5. HTML vs. Plain Text Emails
This classic test helps you determine whether your audience prefers visually rich designs or personal, conversational messages. HTML emails are great for showcasing products, while plain text emails often feel more authentic especially for trust-building messages or founder-led updates. This is worth testing if your email strategy involves sending a lot of story driven emails from the CEO.
6. 20/80 Image-to-Text Ratio vs. 80/20
The balance of visuals and text in your emails can significantly impact engagement. Test a 20/80 ratio (more text-heavy) against 80/20 (image-focused) to determine which resonates better. For brands in fashion or home decor, images often perform well, while text-heavy emails might be better suited for B2B or educational content.
7. Best Sellers vs. No Best Sellers in the PS Section
Adding your best-selling products to the PS section of your email can nudge customers to explore more. Test whether highlighting your best-sellers in a subtle, non-intrusive way increases clicks and conversions. For some audiences, a reminder of what?s trending might spark interest, while for others, a constant reminder of your bestsellers could be annoying. Run this test on your content and trust based emails to see how your subscribers respond.?
8. CTA Button vs. Text Link
The placement and format of your call-to-action can significantly impact click-through rates. Test whether a bold CTA button drives more clicks than a subtle text link. Keep the button design consistent across your emails don’t change the size, color, or style for each variation, as this introduces multiple variables and muddles your results.
9. Emails With or Without Prices
Test whether including product prices in your emails drives more clicks and conversions. Prices can help set expectations, but omitting them might encourage curiosity and clicks to your website.
10. Product Images vs. Lifestyle Images
Visuals play a crucial role in engagement, but the type of imagery you use can make a difference. Test emails with standalone product images against lifestyle shots that show the product in use. For example, a simple image of a dog sweater might work well for detail-oriented shoppers, while a cozy shot of a dog wearing the sweater in a winter setting could evoke emotional engagement and drive clicks.
Wrapping Up
A/B testing isn’t a one-and-done exercise it’s an ongoing process that helps you stay ahead in an ever-changing digital landscape. At its core, A/B testing is about listening to your audience and letting data guide your decisions.
At Budai Media, we don’t just run A/B tests and call it a day. We continuously analyze the results, apply what we’ve learned, and adjust your email campaigns to make them even better. Whether it’s refining your subject lines, experimenting with CTAs, or optimizing email flows, every test is a stepping stone to more effective marketing. If you’re ready to take things to the next level, we’d love to help. We’ve worked with over 200 brands, creating growth strategies that bring real results, and we’re looking for a few more brands to join us.
If your store is bringing in over $100k a month and you’re curious to see how we could boost your growth, book a strategy call with me to get a free audit of your entire e-commerce set-up including Google Ads, email marketing, and more along with a custom blueprint to help you grow.
