Start using A/B split testing to increase your email open and click-through rates.
Here’s the issue with email marketing: We live in a world where the average email volume is 53.65 billion daily, and 85% of it is going to spam. As a marketer, it’s your job to cut through all the noise. But how?
How to Use A B Testing to Split Test Your Email Subjects & Copy
What is A B Testing?
A B split testing is a way that you can compare two versions of an email for the best performance. Marketers commonly use split testing to compare a change in one variable, such as subject lines or copy, to an original version by sending both to a sample of subscribers. The performance results of email A and B are observed, and the best version is sent to all subscribers.
Split testing is used to optimize email campaign responses including open rates, click-throughs, and, ultimately, conversions.
By analyzing the results of your split test, you can then optimize your email campaign’s effectiveness in open rates, click-throughs, and, ultimately, conversions.
What Is A/B/n Testing?
A/B/n testing is used to test multiple versions of a single element instead of two. You expose a percentage of your subscribers to different versions of your message to determine the best performing variation. Unlike A/B testing, you will usually have 3 or more versions of your message. The “n” in A/B/n refers to the number of variations you will test.
With Seynd’s automated A/B/n testing, you can set the “winner” (the best responding message) to automatically be sent, with no additional action being required on your part. You can also choose to simply evaluate the data or continue with more testing.
A/B/n testing takes the guess-work out of creating effective marketing messages, so you can focus your time in other areas.
What Is Multivariate Testing?
Multivariate testing tests multiple variables among two versions of an email to analyze the performance of different combinations. You can test not only the effect of changing one element but the combined effect of several.
The drawback of Multivariate tests is more room for human error. If you do not have a large enough sample size, (Yoast recommends at least 100 conversions per variation) you won’t get accurate results. Likewise, more variables being compared simultaneously can also affect the chances for error.
Multivariate testing is best for high traffic webpages. In the context of email, we recommend sticking to testing one variable at a time for best results.
Key Stats to Consider with an A B Test
1. Not Enough Marketers Split Test
According to the 2018 Email Marketing Industry Report, 53% of marketers never use split testing to test their emails (subject lines, copy, CTAs, and more). Meanwhile, 51% are not automating their emails, including their welcome campaigns.
That means that you, the smarter marketer, have the upper hand over companies who are not testing their emails. Split testing your subject lines and email body copy will ensure that your emails are always performing at their best.
2. Small Changes Matter
A general rule to split testing is to test one variable at a time. That’s because one small change can already make a big difference.
For example, Hubspot uses a b testing to compare clickthrough rates between using a generic company email sender name and a personal sender name. Hubspot’s test concludes that by using a personal sender name, clickthrough rates increased by 0.23%.
The variable test (B) gained 292 more clicks compared to their control test (A), resulting in 131 new leads.
What You Need to Know to Start Email A B Testing
Know Your Audience
You’ll want to create a campaign that appeals to your market. Ask yourself:
- Who are your buyers?
- What are your segments?
Creating a customer avatar is a great way to pinpoint the types of people that ideally buy what you sell. An intimate understanding of your buyers allows you to customize your email message for a better response.
Your company might have various customer avatars. Categorizing, or segmenting, your ideal buyers will help you to customize multiple email messages.
An initial good email is fundamental for efficient A B testing.
Know Your Key Performance Indicators
Decide what your goal is going to be for testing your subject lines and copy. Are you aiming for better open rates? Click-throughs? Or overall conversions? Your key performance indicator (KPI) will help you define what a successful email looks like after split testing.
- Open rates
- Click-through rates
- Conversions
Split Testing Email Subject Lines
Email subject lines are a great place to start split testing, especially if your goal is to increase open rates. Here are a few A B tests to consider to create the best performing email subject line:
- Longer vs Shorter Email Subject Line
- Simple vs Detailed
- Answer vs Question
- Urgent vs Nonurgent
- Emoji vs No Emojis
- Customer Name vs No Name
- Personal sender name vs Company Name
- Word Order
Split Testing Email Copy
Ever heard the saying “less is more”? A study by MIT professors in 2010 concluded that shorter emails increase the chances of higher responses (click-throughs, open-rates, and replies). You can test this for yourself using the split testing method!
Other A B tests to consider are:
- Formatting
- Image vs no image
- Call-to-actions
- Tone and style
How to Split Test With Seynd
Seynd is the only Web Push Notification service that provides A/B/n automated testing. You can use it to test your email subject lines and body text, as well as your web push notifications. Here’s how Seynd’s A/B/n tool can work to also split test your emails:
Begin by selecting the A B Testing
Next, add your test
Filter your subscribers by location and add the amount you’d like to use for testing.
Set the winning date and time. This will determine the date and time you want to stop testing and review your results.
Tip: When using A/B/n split testing for push notifications, you can select send automatically to auto-send your best-performing web push notification.
Choose the number of messages or tests you want. With A/B/n split testing, you can add more than two messages to test with.
Create various email subject lines or email body copy in the message boxes.
If you are testing different subject lines, be sure to keep your body copy the same for accurate results, and vice versa.
Now that you’ve got a great strategy for better-performing emails plus a great tool to do it, why not find out how else Seynd Web Push Notifications can enhance your email performance?