In the email marketing world, email marketing is still as effective as it was then and offers businesses direct access to a segmented group of people in their inboxes and has a high ROI. With millions of emails a day being sent to consumers, email campaigns should be optimised in order to stand out and draw more attention. This is where A/B testing (or split testing) comes in handy. For email campaigns, A/B testing involves evaluating two versions of an email in order to determine which is most likely to reach the intended audience and yield the best results.
The Power of A/B Testing:
Email marketers can greatly benefit from using A/B testing as a powerful tool because it allows them to act upon data. The test involves comparing two versions of an email so that you can get insights into how each element (subject lines, CTA, and pictures) will perform. When we understand which version drives more clicks and conversions, marketers can tweak their future email campaigns. Such optimization ensures higher engagement, better ROI and higher sales over the long-term.
Setting Up an A/B Test:
For email campaigns, it is easy to conduct an A/B test. Here are the steps:
Step 1: Define Aims
Your first step in any A/B testing session is to clarify your goals. Depending on the stage of your email campaign, you may have different objectives. Perhaps you want to improve open email numbers, click-through rates, conversions, or even get some insight into customer tastes. Having a clear goal will run all the way through the testing and enable you to evaluate what is most important to the business.
Example of Goals:
Open Rates: Decide what subject line is most appropriate for your intended recipients.
Click-through Rates: Alter the language of your CTA or the place in your email.
Conversions: experiment with different versions of images or descriptions to see which leads to more sales.
Step 2: Prepare Two Drafts of Your Email.
You’re then going to have to develop two variations in an email, changing just one variable between them. This separation will mean that you can assign performance changes to that change, and that change alone.
Possible Variables to Test:
Email Subject Line: Experimenting with tone, length, or personalization strategies.
Call-To-Action (CTA): Text, design, or placement of the button.
Images: This would include posting different versions of various images to see which image would grab more attention.
Content Design: Revisions to the layout or order of content in the email.
Remember: Test one variable at a time to make sure your outcome is meaningful.
Step 3: Split Your Audience
Once you have two emails ready to go, divide your list into two as equal groups as possible. Just make sure both populations are roughly the same demographics as one another, so that your test results don’t differ. Each is given a copy of your emails so you can see how each section responds to them.
What To Segment Your List By:
Random Sampling: Randomly pick out your subscribers.
Geo-Location: Divide your mailing list based on where they live (if you want to test that). It can be segmented by country, state/province, or city.
Degree of Interest: you could sort subscribers by degree of interest — extreme and moderate- but you’ll definitely need to be a bit more subdued.
You’ve sent your emails now you’re ready to take a look at the results to see which version did better in relation to the specified goal. Then check your email marketing platform’s analytics to monitor open rates, click-through rates, conversions, and other overall activity.
Key Metrics to Track:
Open Rates: Did one subject line just blow the doors off of your emails?
Click-Through Rates: Which email had the most CTA clicks?
Conversion Rates: Which turned prospects into customers more efficiently?
Set your A/B test to a time frame you can trust, but don’t test your website during major holidays etc when traffic or offers might bias your findings.
Tips for A/B Testing Emails:
The following are best practices for A/B testing email campaigns:
Just Try One Variable At A Time.
The best A/B test for email campaigns is to always test one variable at a time. If more than one factor was tested at a time, you might find it challenging to see which one had the largest influence on the results. For instance, if you run the subject line and the CTA button at the same time, and the one with the new CTA button performs better, then you don’t know whether it was the CTA button or the subject line.
Rather, try to test one variable at a time. That might be the subject line, the sender name, the CTA button, the email layout, or the copy. You can test one variable only and isolate its impact on outcomes and decide through data what’s best for your audience.
Use a Representative Sample
If you are running A/B tests for emails, you need to have a representative sample. This requires that the sample should be large enough to yield statistically significant findings. If you use a small sample, results won’t be robust, and you’ll end up making choices based on insufficient data.
In order to be representative, think about these things:
Scale: A bigger sample will yield more accurate results than a smaller one. A general guideline is to test at least 1,000 subscribers per variation.
Survey Data: Make sure that your sampling is representative of your target audience. If your subscribers are diverse, consider including subscribers of varying demographics in your sample.
Take as Much Time As You Can.
For A/B testing email campaigns, make sure you test long enough. It is not worth testing too long as it will skew the outcome and some factors such as the time of day or weekday can bias the test.
If you want to make sure your test is accurate, consider the following:
Test for at least 24 hours, but longer if possible. This will provide you with sufficient data to draw reasonable conclusions.
Night: Try at various times of the day to see if they perform differently.
Time of the week: Experiment with different days of the week to see if there are any differences.
Analyze the Results Carefully
When you’ve run your A/B test, you have to take a look at the results. That is, analysing the data from both variants and deciding which one was the winner. If you need to make the result statistically significant, use a statistical significance calculator.
As you evaluate the findings, consider these:
Open rate: Did one subject line fare better than the other?
Click-through rate: Did one CTA button/email design outperform the other?
Rate of conversion: Did one variant convert more than the other?
Conclusion:
Email campaigns can be A/B tested for marketers to use in order to better target their email marketing. Testing various components of an email enables marketers to learn what is working and what is not in order to make data-driven decisions and optimize email campaigns. Following best practices like testing a single variable, representative sample, testing long enough and looking at the outcomes, marketers can fully benefit from A/B testing and generate better outcomes for their business.
