Newsletter Ab Testing How To Achieve Higher Opening 038 Click Rates
Management Summary
A/B testing
With A/B testing (AB testing or A/B split testing), your email marketing tool is used to determine the better of two or more newsletter or mailing versions. A/B tests offer countless opportunities to optimize your newsletter and continually learn from the results of the tests for future mailings.
The most important A/B tests include:
- Subject testing
- Content testing
- Testing the shipping time, etc.
If the sending group is large enough (at least 1,000 recipients per group), it is recommended to send one each newsletterA/B testingto carry out. Through ongoing testing, you’ll ultimately learn what works and what doesn’t for your recipient group.
A/B testing: How it works
Professional email marketing toolsoffer the possibility to carry out automatic A/B or split tests. TheSize of the test group, theParameter for goal achievementand theShipping timeare determined by the sender, everything else is automatic. All you have to do after that is wait for the result of your test and draw conclusions from it.
Here is an example: You want to test 2 versions of a subject against each other and set in the email marketing tool that 25% of the recipients should receive the 1st version and 25% the 2nd version. Since the quality of the subject provides information about the level of the opening rate, the opening rate is defined for the test as a parameter for achieving the goal. As soon as the tool has calculated a significant result (unfortunately not all tools can do this) or after a time defined by you, the better of the two versions will automatically be sent to the remaining recipients (50%). In the case of subject testing, the better version is the one that achieved a higher open rate.
The benefits of A/B testing
- More performance with the same effort.
- With each significant test result, conclusions can be drawn about the preferences of the newsletter recipients.
- The results of a test provide assistance in designing future newsletters. What performed well will continue to be tested – what has performed poorly will be avoided in the future.
- Without testing, you might have sent the “worse” version to all recipients. Going back to the example above, the test allowed you to send at least 75% of the recipients the better version.
A case study: A/B content testing
At aContent testingTwo or more newsletters or emails are compared that are each otherdiffer from each other in content– this can be done by others, for exampleImages, wording, formatting, etc.be. The following case study from e-dialog deals with a simple content test for a hotel. Can’t tell the difference between the two newsletters in the pictures at first glance? This example requires you to take a closer look. It was testedUnderlining the text links– once underlined, once not underlined.
Since the click rate represents a performance indicator for the content of a newsletter, this was set as a criterion for achieving the goal. With this measure, the A/B content test was able to achieve a 100% increase in the click rate in the variantwith underlined text linkseffect. Ie this version moved the recipients to do so100% more frequent access to the linksthan in the newsletter without underlined links.
How do you proceed? Are you already testing or are you still shipping randomly and what experiences have you had with A/B testing?
You are now full of enthusiasm, want to get started right away, but don’t know how – then we would be happy to help you increase the opening and click rates of your newsletter with the help of the right tests!
