How often have you sent email campaigns or promoted a product or service, but haven’t seen the desired results? In most cases, the target audience doesn’t even bother to take the initial steps.
In this day and age, where there are multiple businesses offering the same services, it can be hard to stand out. Customers need something more than just a product — they need a story, an engaging email, or a standout experience. This is why creating an effective marketing strategy and A/B testing your campaigns is essential for success.
A/B testing, also known as a split test, is a great way to determine which marketing strategy works best for your business. By testing multiple versions of a campaign against each other, you can see which one produces the best results.
Given the right approach and data-driven decisions, A/B testing can help you optimize marketing campaigns, email subject lines, and landing pages. It helps to identify which message resonates better with the target audience and how effective your approach is.
In this guide, we’ll show you how to A/B test your campaign for marketing success. From defining goals and metrics to studying the statistically significant results, learn everything there is about successful split testing. Let’s get started!
Quick Note
To A/B test your email campaign, you can use MailChimp. It helps you to test for various criteria. Another advantage of using MailChimp is multivariate campaigns. Get the details by reading our MailChimp review.
What is A/B Testing?

A/B testing is a method of comparing two versions of a marketing campaign to determine which one performs better. The goal is to identify the nuances that your audience would respond to better, be it email subject lines, ad copies, or website design and layout.
When conducting A/B tests, you create two separate versions of a single page (Version A and Version B). Both variations are then tested against each other to see which one provides the best results.
For example, if you want to test email subject lines, you can create two distinct versions of the email subject line. Then, send each email to a segmented list of your subscribers and measure which email got higher open rates.
This allows marketers to make data-driven decisions when creating email campaigns or promoting products and services.
By understanding the key differences between variants, marketers can optimize their campaigns for maximum success. It also helps them pinpoint what works and what doesn’t so they can focus their efforts on the right initiatives.
How Do You Plan a Split Test?
Planning an A/B test requires you to break down the components of your marketing campaign into different variables.
You can think of these as distinct elements that make up the email design and copy, such as email subject lines, body copy, colors, images, etc.
On the other hand, you need to determine what you want to test. Are you running an off-site test or an on-site test? Are you testing email subject lines or website design?
An off-site test involves email campaigns and other forms of promotions, while an on-site test focuses more on website design and layout.
Once you have a clear picture of the elements that need to be tested, it’s time to set up your test. This includes creating two distinct variations (Version A and Version B) and dividing the target audience into two groups.
For email marketing campaigns, this would involve creating two separate email subject lines for Version A and Version B, such as “Buy Now & Save 25%” vs. “Get 25% Off Today Only.”
In case, you are testing a landing page, you might want to test:
- Featured images
- Pop-ups
- Headlines
- The number of fields in a form
- Web copy
- Call to action text
- CTA location
Suppose people visited your landing page but did not sign up for your email list. Even after you provided all the information in a readable manner with catchy headlines, they still did not convert. This could mean that your CTA text or CTA placement is not up to par.
In this case, you might test:
- CTA location
- The exact text used
- CTA button color or surrounding space
All this matters because small changes can have a substantial impact. Changing the CTA location or CTA text could result in higher click-through rates, improved email open rates, or even more conversions.
It is all about how you connect with your audience.
The next step involves running the tests in parallel and collecting data on user engagement, email open rates, click-through rates, etc., over a period of time. Once the test is complete, analyze the collected data to identify which variant performed better in terms of achieving the desired goals.
Multivariate testing can also be used in tandem with split tests to further optimize marketing campaigns. With multivariate testing, marketers can test multiple variables at once and identify the combination of elements that work best.
Quick Note
Don’t forget to split test different pricing options. You can try trial pricing, odd-even pricing, or penetration pricing strategy to see which one performs best.
A/B Testing Checklist to Get Started
A/B testing can be a powerful tool to optimize email marketing campaigns, websites, and other promotional materials. However, it is important that marketers follow an A/B testing checklist before they get started.
As a marketer, you need to have a clear idea of the results you’re looking for. Is it email open rates, click-through rates, or sales? It is important to set SMART (specific, measurable, attainable, relevant, and time-bound) goals to measure the success of your tests.
You also need to plan out the test in advance. Identify which email design elements you want to test. Remember to keep track of the results after each email is sent so that you can make informed decisions when it comes time to review them.
Finally, don’t forget to account for sample size and confidence intervals when interpreting results. Don’t jump the gun on declaring a winner before collecting enough data points. Your conclusions should be based on meaningful data – not anecdotal evidence.
Here is a quick overview of what should be included in the A/B testing checklist:
- Identify your goal: Set clear objectives for your test so you know what success looks like.
- Determine the elements to be tested: Break down the different components that need to be tested such as email subject lines, body copy, images, etc.
- Create two distinct versions (Version A and Version B): Design two variations of the same page or email and divide the target audience into two groups.
- Choose a testing tool to help you run your test: Choose software or tool to help you run the split tests efficiently and accurately.
- Run the test in parallel and collect data: Track email open rates, click-through rates, conversions, etc., over a period of time.
- Analyze collected data: Compare results from both versions to determine which variant is more successful in achieving the desired goal.
- Rinse and repeat: Make changes to the email or page based on what you learn, then rinse and repeat with different elements.
A/B testing is an essential component of any marketing strategy because it helps maximize email performance and ROI. Follow this A/B Testing Checklist for success! With the right approach, marketers can easily optimize email campaigns for maximum effectiveness.
How to Set up Your A/B Test Email Campaign for Accurate Results
Emails are one of the most effective channels for marketing campaigns, and email A/B testing is a critical tool to ensure they are performing their best.
When setting up your email campaign, there are several important steps you should take to ensure accurate results.
- First, craft two variations of email subject lines that appeal to different segments of your audience. You may want to test something like “Your Chance To Win” versus “Don’t Miss Out On This Opportunity” as well as other similar variations.
- Next, create two versions of the email body copy with distinct content and visuals for each version. When preparing these versions, consider the email format (plain text or HTML), layout, design elements like fonts and colors, and email length.
- Once you have the two email versions ready to go, the third factor to consider is the timing window. Consider the scenarios – you received an email and click-opened it within 5 minutes of receiving it or received a newsletter that you opened after 2 hours, or perhaps the subject line and the headline were so boring and spammy that you didn’t even bother opening the email at all. All of this factors into the importance of having a timing window. That is, email recipients should receive each email version within the same window and be given enough time to review it before closing or deleting it.
- Now that you have a handle on the timing window, you need to focus on delivery time. Suppose you’re testing 2 subject lines on 30% of your subscribers, with 15% in each group, you want the winning newsletter to arrive at people’s inboxes by 10 AM and test the open rate for a two-hour duration. Therefore, you will need to start your split test at 8 A.M. if you want the winning variant to be sent out 2 hours later, at 10 A.M.
- Finally, you need to test one variable at a time. Suppose you sent two emails simultaneously with the content and sender’s name being identical. However, you made sure to use two different subject lines. A few hours after sending the emails, you will notice that variant B experienced a much better open rate. In this case, you can assume that the email subject line played a key role in improving email performance. Therefore, you need to test one thing at a time. This will give you a clear understanding of how email performance is being impacted by each element you are testing.
What Email Variable Can you Put to the Test?
When it comes to email A/B testing, the sky’s the limit. You can test several email variables such as:
- Subject line
- Email design
- Personalization (using the sender’s name or subscriber’s name)
- Sender’s Designation
- Email Layout
- Images
- CTAs
- Preview text
- Links and buttons
- Different testimonials
- Headline text
- Closing text
- Copywriting (length, word order, tone)
- Any other aspects
Please note that you should always test one element at a time. This way, you’ll know for sure which email variable impacted email performance the most.
Prioritizing A/B Test Ideas
It’s important to prioritize A/B test ideas in order to ensure maximum email effectiveness. Here are some things you can do:
- Leverage email performance data from previous campaigns to determine email variables that have the most influence on email performance.
- Set goals and objectives for email campaigns, such as increasing click-through rate or improving email open rate. This will help you focus your testing efforts and prioritize email elements based on their potential impact on the outcome of email campaigns.
- Talk to sales reps or customer service teams about common grievances customers may have about emails so that you can identify areas where improvement is needed.
- Analyze email metrics, such as opens, clicks, unsubscribed, and delivery rate to determine email variables that need improvement.
Apart from these, there are some prioritization frameworks that you can use. They include:
- PXL: Prioritize email tests based on the potential impact, cost of implementation, and amount of learning/innovation needed.
- ICE: Prioritize email tests based on the Impact, Confidence, and Ease of implementation.
- RICE: Prioritize email tests based on Reach, Impact, Confidence, and Effort.
- PIE: Prioritize email tests based on Potential Impact, Importance, and Ease of implementation.
By prioritizing email A/B testing ideas, you can ensure that each email campaign is optimized to its fullest potential. This will help you maximize email performance and reach your marketing objectives in a much quicker time frame.
How to Perfectly Conduct A/B Testing?
Once you have identified email variables and set email objectives, it’s time to start A/B testing. Here are a few tips to consider:
Use Collaboration Tools

Collaboration tools such as Idea Management Software can help you brainstorm email tests and create email test plans. Ideas can come from anywhere – from email experts to customer feedback. This allows your team to collaborate more effectively and come up with email tests that will generate the best results.
Choose Appropriate Sample Size
The sample size you select for email A/B testing will have a huge impact on the outcome of email campaigns. It’s important to choose an appropriate sample size so that email performance is not skewed by any factor.
Typically, an email list of 1000 subscribers can be split into two groups of 500 each – one group as the control group while the other group as the treatment group.
Make Use of the Marketing Software
Marketing software can help you automate email A/B testing. This will save you time and effort by automating test setup, email delivery, reporting, optimization, and email personalization. At SaaS Genius, we have reviewed some of the best marketing software, from SEO tools to email marketing software, marketing automation tools, and more.
Include Confidence Intervals
Confidence intervals are important when conducting email A/B tests as they provide a measure of certainty on the outcome of email campaigns. This allows email marketers to identify statistically significant results in order to make data-driven decisions for email optimization.
For example, email marketers can use 95% confidence intervals to identify email variables that are significantly impacting email performance.
Analyze Results Quickly
It’s important to analyze email performance quickly in order to make optimal use of the data from any given email campaign. By analyzing email performance quickly, you can determine which email variable had the most influence on email performance and improve future emails accordingly.
CRM Integration
Integrating email marketing with a customer relationship management (CRM) system can help email marketers personalize emails and track email performance more accurately. This allows email marketers to tailor email campaigns according to each individual customer’s preferences and behaviors.
By following these tips, you can ensure that your email A/B testing efforts are successful and yield the best results for your email campaigns.
Reading A/B Testing Results
Once email testing is complete and data has been collected, it’s time to analyze email performance. Here are a few tips for reading email A/B test results:
Check Your Goal Metric
The goal metric is the email variable that you are testing. It’s important to check this email variable first and see if it performs better in one email version than the other. This will help email marketers identify which email variables have an impact on email performance.
Check Email Response Rates
Email response rates indicate how many people opened, clicked, or interacted with your emails. These email metrics can help email marketers determine which email versions were more successful in engaging customers and encourage them to take action.
Segment Your Audiences for Further Insights
After email performance is measured, email marketers can segment email audiences by demographics, interests, and behaviors. This will help email marketers identify which email variables work better for different customer segments.
Check Email Report Summaries
Email report summaries provide a quick overview of email performance and enable email marketers to determine which email versions performed the best. These reports enable email marketers to compare different email parameters such as open rate, click-through rate (CTR), unsubscribe rate, etc., and make data-driven decisions for email optimization.
Conclusion
Email A/B testing is an effective email marketing strategy for optimizing email campaigns and improving marketing performance. By following the tips outlined in this guide, email marketers can use email A/B testing to make data-driven decisions that are tailored to individual customer preferences and behavior.
Additionally, email marketers should be sure to read email test results in order to gain further insights into customer behavior and optimize future emails accordingly.