2024-02-15 4:06 pm
2024-04-25 5:23 am
2024-04-25 5:23 am

A/B Testing for Emails: Steps to Execute It for 2024

By reading this article, discover how to execute A/B testing for emails in 2024. We’ll be going over everything you need to know, from what A/B testing is to a step-by-step guide to executing effective A/B testing.

So, what exactly is A/B testing, and how do you carry out A/B testing for your email marketing campaign?

In this article, we’ll be taking a look at: 

  • What A/B testing emails are
  • A sample Google Sheet for A/B email testing
  • Your 12-step plan for effective A/B testing for email
  • Five things you should include as variables in your email A/B testing
  • The 15 potential pitfalls and mistakes to avoid
  • Frequently asked questions.

Let’s go ahead and jump right into it.

What Is A/B Testing Emails?

what is a/b testing emails?

A/B testing is a split testing method email marketers use to determine the best possible email subject lines and content for their marketing campaign.

Practically, this means dividing your virtual recipients into two separate groups, who receive one of two versions of your email in their email clients, with a few things tweaked.

This could be:

  • The subject line length or headline altogether
  • The way that characters look (eg, font size)
  • Choice of words
  • Use of or lack of emojis
  • Differing imagery, GIFs, and background colors
  • Brand name (or company name) placement
  • Display of the sender name.

Not only will the email itself be different, but the preview text will also be different for your two groups of readers.

Drawing from our experience, if you have a hypothesis about how one version of an email may outperform another in your metrics and analytics (eg, with improved opens, click-through rates, or engagement rates), A/B testing is the perfect way to test and study your theories, especially against a control group.

While you can A/B test from your email client, using a CRM platform (ie, Hubspot) that manages this for you will allow you to significantly automate the process through their in-platform menu options. This can save you a great deal of time.

The Concept and Importance of A/B Testing in Email Marketing

The concept of A/B testing is that you can have measurable behavior statistics for feedback and research into which group engaged with the email and its products or offers more. 

It’s an excellent, focused approach (of many potential strategies) for cold email marketers to employ, as it tells you at the moment what had the most attraction and interest within your subscribers’ or customers’ inboxes.

What you alter in each set of emails depends entirely on what you want to test. Perhaps you want to test, as examples:

  • Which font performs better
  • What got more clicks and improved your click rate
  • Which messages and newsletters held people’s attention over a particular duration or period better
  • Whether including call-to-actions (CTAs) resulted in increased sales percentages. 

Whatever the case may be, A/B testing is a great way to measure the success of the emails on consumers within your marketing campaign and apply relevant changes to your future emails to optimize success. 

Why A/B Testing Is Crucial for Email Campaigns

When working on an email campaign, you want to constantly grow and evolve. Changing certain aspects of the emails you send out can greatly increase your open rates and boost your sales. 

A/B testing is one of the easiest and most effective ways to determine what changes you need to implement regarding your email marketing campaign to increase purchases and your revenue. 

While it may seem like a dull task, doing regular A/B testing on your email list allows you to test ideas and options for elements of your email and will provide you with valuable insights into best practices — a crucial aspect of successful email campaigns.

If you’re using a CRM client to do your A/B testing for you, you can even set it to select which elements or objects to change in your emails for optimization.

Sample A/B Testing for Emails - Google Sheet

sample a/b testing for emails

Want to see a visual example of what A/B testing for emails can look like? Look no further — we’ve got a Google Docs online spreadsheet as one of our downloadable tools that you can utilize for your own A/B email testing! 

Simply click here to access our sample of A/B testing for emails, then follow the instructions at the top of the page to make a copy to your platforms. 

Instructions and details are included at the top of the spreadsheet, so you can input the numbers, track the results of your own A/B email testing for your marketing campaigns, and implement optimization. 

Steps to Execute Effective A/B Testing for Email

steps to execute effective a/b testing for email

Are you planning on doing some A/B email testing for your campaign? Then we have some good news — we’ve got the best tips and tricks for executing effective A/B testing!

Set Clear Objectives

Before starting your A/B email testing, you must have clear goals, targets, and outcomes. That way, the answers you receive will support your utilization and enhancement of your marketing emails.

What exactly are you wanting to achieve with this testing? Is it:

  • Higher open rates from prospects?
  • Better conversion rates?
  • Improved user interface designs?
  • Increased visitors from all over the internet to your website?

Our findings show that you should set clear objectives that you are aiming to achieve for advancement by carrying out your digital A/B testing job. This will help you stay on track during the testing process. 

Select One Variable to Test

Trying to test too many variables with A/B testing will not work. 

If you change several variables between your emails with no controls and notice one email group performing much better than the other, how will you manage and determine which variable theory caused this successful performance? 

Instead, select just one (or perhaps two, at a push) variable to test and stick to it. 

This will give you a much clearer instance of what is working and what is not regarding your email campaigns. 

Segment Your Audience

The next step in A/B testing emails is segmenting your email list. 

While segmenting your email list is usually done by specific categories — such as age, demographic, or locations and places — this changes slightly when it comes to A/B testing. 

Since you seek genuine results for which email performs better across the board and has more transformation, you will likely want to divide your email list randomly to ensure the testing is accurate.

Don’t have a large enough list to get enough sample size for your A/B testing? You may want to consider using a prospecting service by purchasing your own email lists without waiting for them to grow organically.

Design Your Variants

After segregating your email list, you want to design your variants and features. 

What exactly will you change in your two emails and why? Will you alter the subject line or change the font size and style for better readability

The variants you choose to alter can be anything that you desire. Just make sure you are choosing something with a high possibility, probability, or opportunity to impact the success of your email campaign. 

Based on our observations, while it is important to not choose too many variables, choosing something insignificant is equally ineffective. 

For example, carrying out A/B testing to determine whether an email with items such as “kind regards” performs better than one that ends with “best wishes” isn’t a good use of your time. 

Determine Sample Size

Another step that you will need to take before sending out emails for A/B testing is determining your sample size for your collectives. 

How many recipients will there be in each testing group? Having only a few various recipients in each group is unlikely to yield valuable results, but having plenty in abundance can give you far too much data to sort through.

Determine how many recipients you want to include in your A/B testing, and then split them into two even teams to get the most accurate results. 

Send Out Your Test

Finally, it is time to send out your test. 

Send your emails to your two test groups’ email client interfaces — just ensure that you have accurately applied the relevant changes you want to test! 

It is also important to ensure you are sending these emails simultaneously; otherwise, this may interfere with the results. Unless you are testing what time during the day is best to send your marketing emails. 

Monitor the Results

Once you have sent out your test emails, carefully monitor and observe, evaluate, and carry out examinations on the results. 

Document any relevant information that you discover for assistance after sending these emails (perhaps even taking screenshots), such as deliverability, open rates, and conversions. 

Documenting and monitoring the results as they occur as an aid will ensure that you have all of the relevant information needed when it is time to analyze the data and your usage of it. 

Analyze the Data

Once the testing results have rolled in, it is time to analyze and validate the data you have collected. Take a close look at the performance of your emails and which one seemed to perform better. 

In application, did the recipients respond better to version A or B of the email? Are there clear differences in the responses to these emails? Were any hypotheses that you had about the testing proved correct?

You’ll likely have lots of data to look through, so employ good analytics skills and discard any irrelevant or incomplete data first, then look at the remaining data. This remainder — or leftover — data will give you your true results over the others.

Determine Statistical Significance

After analyzing your data, you must determine the statistical significance of your results. 

Did one email perform significantly better than the other? Or were the responses to both versions of the email relatively similar?

If the response to one of the emails is statistically significant regarding successful performance, it is likely a good idea to model the rest of the emails in your marketing campaign after this version. 

Implement Learnings

As per our expertise, if you find significant differences in the responses to your emails, you can adjust, refine, and implement these changes in your future emails. This will greatly increase the success of your email marketing campaign. 

For example, let’s say that version B of your email contained an embedded button that the recipients could click to visit your website. 

If website traffic and sales via this button have increased significantly, it is likely a good idea to add this feature to your future emails. 

Iterate and Optimize

The best part about A/B testing is that you can repeat these tests as many times as you want to constantly grow and optimize your marketing campaign. 

As a general rule, you should periodically implement relevant changes to your testing to gather further data that will help you improve your emails and click-through ratios. 

Create multiple iterations of your A/B testing emails until you find the content, layout, and best email practices for you.

Document and Share Findings

This part is crucial — document your findings. 

Once you have finished your A/B testing, ensure that you are keeping the data you have gathered somewhere secure. 

You may want to report your findings publicly, with other workers in your team or field, or simply store them in a private document somewhere. 

Variables to A/B Test in Your Emails

Variables to a/b test in your emails

Struggling to come up with some variables to the A/B test in your emails? Don’t worry — we’re here to help!

Testing Subject Lines for Maximum Impact

Using A/B email testing to try out new subject lines is a great way to gauge their effectiveness. 

Measuring the difference in open rates between two emails with vastly different subject lines will point you in the right direction and help you determine which subject lines appeal most to your target audience. 

Personalization: Length, Tone, and Content Variations

Another aspect of your emails to consider during A/B testing is personalizing your content, which is preferred by potential customers. 

The length, tone, and specific content included in your email are extremely important for your email marketing campaign. 

Visuals: Using Images, Layout, and Email Design

Visuals such as images, layout, and design are aspects of your email that can have a strong impact on the way that the message is received by your audience and generates more responses than plain text. 

Using A/B testing to try out new layouts, email structures, and embedding images is a great way to gauge what does and doesn’t work in your email marketing campaign. 

Calls to Action: Button vs. Text, Copy, and Placement

Your email's call to action section is one of the most important areas and therefore is something that you may want to A/B test. 

Experimenting with call-to-action buttons, test links, and placements will help you understand what leads to the most website traffic and sales. 

Send Time: Optimizing Delivery for Best Engagement

What is the best time to send emails for your marketing campaign? This will often differ slightly depending on your specific audience.

For example, in some regions, sending emails in the morning results in more engagement than at night. However, an email sent on a Tuesday afternoon likely has a higher open rate than and leads to more clicks than one sent on a Friday afternoon.

A/B testing to see what time of day and day of the week outperforms others is a good way to get an accurate read on the optimal email delivery times for the best engagement. 

Potential Pitfalls and Mistakes to Avoid

potential pitfalls and mistakes to avoid

Now you know what to do regarding A/B testing for emails — but what about what not to do?

Testing Too Many Variables Simultaneously

One common mistake in A/B testing that can completely throw off your results is using too many variables simultaneously. 

Over time, we found that using fewer variables is more effective than too many as if you change too many aspects and see significant results, you won’t be able to tell which variable caused them!

Ignoring Statistical Significance

Once you have collected data from your A/B testing, it is important to analyze this and watch for statistically significant changes, such as if one converts higher. 

This will indicate what email performs better and what variables should be changed. 

Sample Size Too Small

When carrying out any testing, you will want a decent sample size. This is to ensure that your results are accurate and will help you understand what most of your audience thinks is more appealing than other approaches in your email marketing campaigns.

Not Accounting for External Factors

Many external factors may influence the results of your A/B testing. 

Are you sending the emails on a public holiday? Is there anything significant happening that will draw people away from their computers? 

Be sure to consider external factors that may impact your A/B testing. 

Not Running Tests Simultaneously

You want to do this simultaneously when sending out your two sets of emails. This will ensure that the time you send your emails does not influence the results. 

The only exception is if the variable you are testing is which time of day you should send your emails. 

Stopping Tests Too Early

If you stop your A/B test too early, you may miss out on significant data from your recipient segment. 

Cutting your test short too quickly increases the likelihood of your results not reflecting your audience accurately, as you do not have enough data to find statistically relevant results. 

Not Re-testing

As demonstrated by our track record, the entire purpose of A/B testing is to help you improve certain aspects of the emails in your marketing campaign. 

If your first A/B test for your email content pointed towards a certain variable needing to be changed, change that variable and re-test it rather than moving onto a variable for email length. This will confirm whether or not this is a beneficial change. 

Overgeneralizing Results

If you notice a certain result in your A/B tests — eg, increased response time — do not automatically assume this applies to all other aspects of your email campaign. 

As another example, you may discover that a large call-to-action button in a specific button color embedded in your email was the most effective way to increase website traffic and sales. 

Do not instantly go and replace all of the links on your business website with large colored buttons — these results are specific to the testing scenario. 

Ignoring Small Gains

So, you’ve noticed that you received three more sales per week using an embedded call-to-action button. That’s not a lot, so why bother going to the effort of adding this button to your emails? 

The truth is you aren’t going to see huge gains all of the time. The small gains will gradually build up, leading to further success. A mere 3 extra sales from your testing group of 50 people would be 6 more sales in a group of 100. 

That is 12 more sales after 2 weeks and 18 more after 3 weeks. As time passes and your customer base increases, these sales will only continue to grow. 

Changing Test Parameters Midway

If you have decided on the parameters of your A/B test (eg, personalization level or image placement), stick to them. Changing test parameters midway can greatly impact your results and cause all your data to be inaccurate. 

Forgetting Mobile Users

In this day and age, more and more people are checking their emails exclusively on their smartphones. Don’t forget to consider mobile users when it comes to your A/B testing. 

Ensure that the format and structure of your emails are readable on mobile phones and that all your embedded links and images are mobile-friendly, or your unsubscribe rate will increase. 

Failing to Document Results

As demonstrated by our hands-on approach, it is vital that you document your results when A/B testing. The data you gather from these tests is incredibly useful, so you want to ensure that you are keeping track of it and storing it safely. 

Over-Reliance on A/B Testing

While A/B testing is a great tool in your back pocket, if you can’t make any decisions without it, it is time to take a step back. 

A/B testing can be time-consuming and can be used for every little thing. Trust your instincts and judgment, and reserve A/B testing for significant changes. 

Not Prioritizing Tests

As harmful as it can be to become overly reliant on A/B testing, it can be equally harmful to not prioritize them. 

A/B testing is extremely useful for a successful email marketing campaign and should be conducted regularly.


How often should I conduct A/B testing for my emails?

How often you conduct A/B testing for your emails depends entirely on your goals and schedule. You should try to A/B test your emails at least once a month but no more than once a week. 

What’s the minimum sample size for effective A/B testing?

Regarding A/B testing, the larger the sample, the better. While around 100 people are considered effective, if you can get your sample size into the thousands, you will receive much more accurate results. 

How do I Know if my A/B testing results are reliable?

You can tell that your A/B testing results are reliable when they are statistically significant. This means that the results are unlikely to have occurred by chance but accurately reflect your audience.

Key Takeaways

When it comes to email marketing campaigns, one of the most effective measures that you can take to ensure your campaign is successful is executing A/B email testing. 

This type of testing compares two versions of the same email and measures which performs better when sent to your target audience. 

A/B testing allows you to make relevant changes and improvements to your emails to bring about a range of benefits, such as increased open rates, website traffic, delivery rate, sales, and decreased bounce rate.

Ready to get your A/B testing down to an art and level up your email marketing campaigns? That’s where BookYourData comes in!

With a trusted reputation and thousands of clients globally, it’s the number one choice for small, innovative startups and industry giants to grow their lists since 2015.

Sign up for free with BookYourData today and receive 10 free and guaranteed leads to get you started, no credit card details are necessary.



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