Why does one email easily attract the attention of the audience, while another one gathers dust unread? How to avoid failures and create a truly effective newsletter with high open and click rates? The answer is simple - A/B testing.

Let's talk about experiments in email marketing that will help you get the most out of your campaigns.

Definition of A/B testing

For many marketers, A/B testing still seems like a complicated process. However, in reality, its essence is quite simple.

Imagine that you want to find out which email subject line will be more effective: “50% discount just for you!” or “Don’t miss out on the deal — 50% discount on all products!”.

To do this, you divide your audience of subscribers into two equal groups and send the first group a message with the first subject line, and the second group — with the second. Then, carefully track the statistics of opens, clicks, and unsubscribes using email analytics.

The version of the email that demonstrates the best results becomes the winner and is sent to the rest of the subscribers in your database. That’s the whole secret!

Email Elements to Test

You can make the process of A/B testing in email marketing more complex and test not only the subject line, but also other elements such as text, images, and call-to-action buttons. The main thing to remember is to test only one element at a time so that you know exactly what influenced the result. This allows you to optimize the content and design of your email campaigns, increasing their effectiveness and audience engagement.

Let's start with the visual part of the email - fonts and design. Have you ever wondered why some emails look like boring memos, while others look like works of art? It's all about the right choice of font, size, color palette, and other design tricks. You can compare a letter in a strict business style and a more creative version using illustrations. Most experienced email marketing specialists are convinced that the second option will arouse more interest among subscribers.

Don't forget about the length of the email text. Short messages sometimes work better than long and wordy ones. Experimenting with the amount of content will help you figure out the optimal format, so that your subscribers won't scroll through your emails, but will read them with pleasure.

The next point is the number and location of calls to action (CTA). How often do you offer subscribers to perform a target action: go to the site, place an order, or subscribe to the newsletter? One "Buy" button at the end of the email or several calls at different stages of the text? Run a test and find out what works better.

Another interesting topic for experiments is visual elements. Photos, illustrations, GIF animations - what catches the eye more? It is important to find the golden mean between "too boring" and "too much glitter".

And another important aspect is the time and day of the newsletter. Tuesday at 10 am or Saturday at midnight? It's hard to predict when your subscribers will be most active and receptive to your offers. A/B testing can help you figure out the optimal window for sending.

Example of an effective email

A/B Testing Guide

Now let's dive into the sea of email marketing experiments. Our email marketing agency uses the following guide to properly conduct A/B testing:

1

The first step is to determine what exactly you want to test. This could be a compelling subject line, a bright CTA button, or the placement of images. The main thing is that your “test unit” is clearly defined and not spread throughout the entire email. Otherwise, you risk getting a set of incomprehensible data, rather than valuable insights;

2

Step two: formulate a working hypothesis. Imagine that you are testing two options for the subject line: “50% discount just for you!” and “Urgent! Buy at the best price.” Your hypothesis might sound like this: “A subject line that indicates urgency and benefit will attract more attention from subscribers than a simple discount offer — the open rate of such letters will be 2 times higher”;

3

Now it is important to choose the right audience for the experiment. Divide the base into two equal random groups - control and test. This will minimize the influence of external factors and obtain reliable results;

4

The most interesting part is launching the mailing. Send the first version of the letter to the test group, the second one to the control group. Track the statistics: openings, clicks on links, unsubscribes and other KPIs that are important for business;

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The final step is to analyze the results and confirm or refute your initial hypothesis. If the subject line with urgency and benefit really showed the best results, then your guess was correct. Now you can safely send this version to your entire subscriber base. But if the control group outperformed the test group, you will have to reconsider your assumptions and think about new experiments.

Errors in A/B Testing of Email Campaigns

The killer of A/B tests is the lack of a clear hypothesis.

Seriously, how are you going to get meaningful results if you don’t understand what exactly you want to test? It’s like going to the store without a shopping list - at best, you’ll buy something you don’t need, at worst, you’ll go home empty-handed. The first step is to formulate a hypothesis that you want to confirm or deny. For example, “Using emoji in the subject line will increase open rates by 15%.”

Perhaps the most common mistake is changing the testing parameters.

You’ve launched an A/B test comparing two versions of the email subject line. But then you decide to add another experimental group with a test for the sending time. Bam! Your results have just turned into a pumpkin. It’s now almost impossible to objectively compare and draw conclusions. Conclusion: choose the metrics and testing parameters in advance and strictly follow them.

The next mistake is incorrectly calculating the sample size.

Imagine you decided to compare two versions of an email, but only selected 50 people for the test group. Yes, the results may be interesting, but will they be statistically significant? Unlikely. So before launching a test, analyze the size of the base, determine the minimum threshold for representativeness, and distribute the audience accordingly.

Another common mistake that cannot be ignored is testing several elements at once.

You want reliable results, not a mess from an axe, right? If you change the subject line, sender, CTA, and design at the same time, how will you understand what exactly influenced the final result? It is better to focus on one element at a time. Then you will be able to understand what worked and what did not, and continue optimizing.

Features of Mailing Services and Online Tools

So, we have figured out the intricacies of successful A/B testing of email newsletters. But the question arises - how exactly to conduct experiments in email marketing? Use services and online tools for mailings.

The advantages of this approach are obvious: automation of processes, visual analytics of your email marketing, convenient distribution of the audience. Many such platforms usually have built-in tools for calculating the required sample size and determining the statistical significance of the results. They allow you to conduct two main types of experiments:

1.A test without waiting for the final part.
You select the element you want to test, set the distribution of test groups (for example, 50/50) and select metrics for analysis. The service automatically divides the base, sends them different versions of the mailing and determines the winner based on a comparison of the statistical indicators of each group.

2.A/B test with waiting for the final part.
Here you independently set the proportions of the test groups and configure how the letters will be sent. For example, you can send a second message only to the group that showed the best results initially. This is a more complex testing option with detailed settings, which allows you to deeply analyze the behavior of your audience and optimize email campaigns.

Why is it important to conduct A/B testing of email newsletters? This is a sure and perhaps the only way to get to know your subscribers and understand what they like. Without this knowledge, you risk shooting blindly into the dark, wasting time and money. But with the help of well-organized experiments, you can constantly optimize newsletters and achieve high efficiency.