Guide to A/B Email Testing Metrics

What do the best email marketers have in common?

The A/B test every element of their email campaigns and use that data to optimize future campaigns. Sending an email and opting that your subject line will resonate with your audience isn't a great strategy. Instead, developing a rigorous strategy of consistently testing subject lines (and other email elements) will help you to determine exactly what works.

A/B testing takes the guesswork out of email marketing. According to Finances Online, fewer than 50% of businesses utilize A/B testing tools. But the global market for A/B testing software is growing rapidly and is projected to reach $1.08 billion by 2025, growing at a compound annual rate of 12.1%.

In this article, we’ll explore the metrics that matter most in A/B testing for emails, how to set up effective tests, and actionable insights to integrate A/B results into your broader email strategy. By mastering these techniques, you’ll not only improve open rates, click-through rates, and conversions but also ensure every email you send is backed by solid data and strategy.

What is Email Marketing A/B Testing?

Email marketing A/B testing is the process of sending two versions of an email to a small segment of your audience to determine which performs better. By testing variables like subject lines, CTAs, and design elements, you can make data-driven decisions to optimize future campaigns.

The importance of A/B testing lies in its ability to uncover what resonates most with your audience, boosting email performance and ROI. For instance, testing subject lines might reveal that a casual tone generates more opens, while a concise CTA drives higher conversions.

You can test any element of your email. We've provided an extensive list of email testing ideas for you to look through, but in summary you can test elements like:

• Subject Line
• Preheader Text
• Call-to-Actions
• Sent Time
• Email Layout
• Personalization
• Visual Hierarchy
• Email Copy
• Sender Name
• Incentive Type

Key Metrics to Track in A/B Testing

Tracking the right metrics helps identify which email version resonates most with your audience. Here are the most critical metrics:

• Open Rates
• Click-Through Rates
• Conversion Rates
• Bounce Rate and Unsubscribe Rate
• Revenue per Email

Open Rates

Open rate measures the percentage of recipients who open your email. It’s a key indicator of how effectively your subject lines and sender names grab attention.

How It’s A/B Tested: To test open rates, create two versions of your email with variations in the subject line or sender name. For example, one version might use a casual subject line like "Hey, check this out!" while the other uses a formal tone such as "Your Monthly Update Inside." Then keep track of the percentage of people who have opened the email.

Ease of Testing: Open rate testing is straightforward and requires minimal changes, making it an excellent starting point for A/B testing beginners.

How to Interpret Results: A higher open rate indicates that your subject line or sender name resonates better with your audience. Low open rates may signal a need to revisit your sender reputation or rethink your approach to personalization.

Click-Through Rates

Click-through rates (CTRs) track the percentage of email recipients who click on a link within your email, reflecting how well your content and CTAs encourage engagement.

How It’s A/B Tested: Test different call-to-action (CTA) phrasing, button designs, or link placements. For instance, you might compare a button with the text "Learn More" against one that says "Get Started Now” and track how many recipients click on the links.

Ease of Testing: CTR tests require more setup than open rate tests, as they involve tweaking design or content elements, but they provide rich insights into user behavior.

How to Interpret Results: If one version has a significantly higher CTR, it indicates that the tested variable better captures your audience's interest. A lower CTR may suggest the need for clearer CTAs or more compelling value propositions.

Conversion Rates

Conversion rates measure the percentage of recipients who complete a desired action, such as making a purchase or signing up for a webinar.

How It’s A/B Tested: To test conversions, experiment with different offer types, landing page designs, or follow-up sequences. For example, you could test whether a limited-time discount converts more effectively than free shipping.

Ease of Testing: Conversion tests often involve more complex setups, including integrations with analytics tools, but they provide actionable insights into revenue generation.

How to Interpret Results: A higher conversion rate points to a successful alignment between your email content and your audience's needs. If conversion rates are low, consider revising your offer or ensuring a seamless user experience from email to landing page.

Bounce Rate and Unsubscribe Rate

Bounces rates measure the percentage of emails that couldn’t be delivered, while unsubscribe rates indicate how many recipients opted out of your mailing list.

How It’s A/B Tested: While bounce rate is less commonly A/B tested, unsubscribe rates can be influenced by testing email frequency, tone, or content relevance. For instance, compare a weekly newsletter to a bi-weekly one to assess subscriber preferences.

Ease of Testing: Testing unsubscribe rates is relatively simple and can often be implemented through existing email platforms. Bounce rate testing, however, typically requires troubleshooting your technical setup.

How to Interpret Results: A high bounce rate suggests issues with your email list quality or domain reputation. An increasing unsubscribe rate may indicate that your content isn’t meeting expectations or that you’re sending too frequently.

Revenue per Email

Revenue per email calculates the average income generated per email sent, providing a clear picture of campaign profitability.

How It’s A/B Tested: Experiment with different promotional offers, product showcases, or email formats. For example, test whether a flash sale email generates more revenue than a product spotlight email.

Ease of Testing: Revenue testing requires integration with e-commerce or CRM tracking tools but offers high ROI on insights gained.

How to Interpret Results: Higher revenue per email indicates that your tested approach resonates strongly with buyers. Lower results may suggest the need for more personalized offers or better audience segmentation.

By focusing on these metrics, you can gather the data you’ll need to refine your email marketing strategy.

Setting Up Effective A/B Tests

A/B testing is just like going into the lab and preparing an experiment. The more scientific and disciplined you are with your approach to A/B testing, the better your results will be. A common challenge in A/B testing is testing too many things at once and not being able to isolate variables.

Did the subject line improve engagement or was it the new layout we tested? It's tempting to test everything but this strategy isn't effective if you want to build up a centre of excellence and really answer the core question of how to improve your email marketing.

Here's a simple step-by-step process for setting up A/B tests:

1. Define your objectives and hypothesis
2. Identify Variables to Test
3. Determine Sample Size
4. Measure Results

Define your objectives and hypothesis

You want to clearly outline what you hope to achieve with your test. Are you looking to test using emojis in your email subject line? What do you expect the outcome to be? By being clear with your objective and hypothesis you can focus your test to ensure you maximize your learnings.

Identify Variables to Test

You will want to isolate variables and focus on one variable at a time. Pick something like a subject line, CTA, or design element to test. If you try to test too many variables it can be impossible to understand which variable had the desired effect.

Determine Sample Size

You've probably heard of the term, "statistical significance." Without enough people in your test, it'll be impossible to get a definitive result. You need to select a sample size that is large enough to get a meaningful result.

Measure Results

After you send the A/B test, you need to monitor the results. The metrics we detailed above are a great indicator of success. What you're really looking for here is big differences between the "A" and "B" versions of your test.

Real-World Applications and Success Stories

A/B testing has proven to be a transformative strategy in email marketing, enabling businesses to make data-driven decisions that enhance engagement and conversion rates. Here are some illustrative examples:

1. HubSpot's Text Alignment Experiment

HubSpot conducted an A/B test to determine the impact of text alignment on email engagement. They compared emails with centered text against those with left-aligned text. The results indicated that left-aligned text led to fewer clicks, with less than 25% of the left-aligned emails outperforming the centered text variant.

2. Neurogan's Segmented Promotions

By auditing their email marketing strategy and implementing product-specific offers, Neurogan tested various deals to identify the most effective promotions for each segment. This approach resulted in higher revenue from promotions and increased click rates with a new workflow achieving an average open rate of 37% and a click rate of 3.85%.

3. WallMonkeys' Homepage Optimization

WallMonkeys, a company specializing in wall decals, aimed to optimize its homepage for better user engagement. Utilizing Crazy Egg's heatmaps and A/B testing tools, they experimented with different homepage designs. The insights gained from these tests enabled WallMonkeys to make informed design decisions that enhanced user interaction and conversions.

Integrating A/B Testing Insights into Strategy

A/B testing isn’t a one-off experiment; it’s an ongoing process. To effectively integrate your findings, align the results with your broader marketing goals, such as increasing engagement or driving conversions.

Leverage the insights gained from A/B testing to enhance personalization and segmentation efforts, creating campaigns that are more targeted and relevant to specific audience segments. Treat each test as part of a larger cycle of iterative improvement, where learnings from previous campaigns are used to optimize future efforts.

By embedding A/B testing insights into your strategy, you can make data-driven decisions that continually enhance your campaigns, ensuring sustained growth and success over the long term.

No-Code Email Tools and A/B Testing

Your mind is likely already buzzing with ideas on how to incorporate A/B testing into your email strategy. One last element to consider is how you build emails. No-code email builders help shift the burden of email design from developers to marketers. With a tool like Knak, marketing teams can get involved in the design process – incorporating learnings from A/B tests into email tests and even designing their own tests.

The flexibility and scalability of no-code tools help to speed up the A/B testing process. As we've seen, you want to isolate single variables – so developing a body of knowledge can take time, especially if your tests are bogged down in a design queue. No-code tools give you the ability to design and publish tests quickly, all while ensuring adherence to brand guidelines.

Ready to take your email marketing to the next level? Explore how Knak’s platform makes A/B testing simple, efficient, and effective.