When it comes to testing opens or open rates, there are a limited number of variables to consider that affect those metrics. Variables such as message content or images won't influence open rates because those are not displayed until after the email is loaded.
Variables that can affect open rates:
- From name and sender
- Subject line
- Preheader text
As you can see, these are the only items visible once an email reaches your user's inbox:
All of the steps below will first require you to create an A/B experiment when you're editing an existing campaign.
For the purposes of this article, we used a triggered campaign, but the same steps apply for any type of campaign.
Selecting a test type
On the experiment setup page, you can select the type of information you want to experiment with, and how you want to split sends between variations (randomly splitting variations for your entire list, or experimenting with variations for a percentage of your sends before choosing a winner that will be used for all remaining sends). For more information about the setting up an experiment, see Experiments Overview.
From name and sender tests
When the experiment is created, you'll see that there is a control and a first variation. At this time, the only difference between the two is name and template ID. In our example we selected Opens as the variable we are trying to maximize.
As long as you are content with your original campaign, there is no need to edit the control.
If you would like to see how the from name and sender affect the open rate, then it's best to only change the From Name field.
After you've made your edit, be sure to save your experiment and then you will be taken to a final review page.
Once you save you will be taken to the Review & Launch page which will give you the option to launch the campaign right away or schedule for a later date.
NOTE
The campaign that the experiment is created from must also be launched in order for the experiment to run.
When the campaign is running, if any large differences in open rates take place, you'll be able to determine with more confidence that the from name was the reason why.
Subject line tests
When the experiment is created, you'll see that there is a control and a first variation. At this time, the only difference between the two is name and template ID.
If you'd like to see how the subject line affects the open rate, then it's best to only change the Subject Line field.
Things to considering testing are:
- Longer subject line
- Shorter subject line
- Call to action
- Noteworthy new service/product/features about your brand
- Including a detail specific to that user (for example, their first name or their city)
- Emojis
Once you save you will be taken to the Review & Launch page, which will give you the option to launch the campaign right away or schedule for a later date.
NOTE
The campaign that the experiment is created from must also be launched in order for the experiment to run.
If any large differences in open rates take place, you'll be able to determine with more confidence that the subject line was the reason why.
Preheader text tests
When the experiment is created, you'll see that there is a control and a first variation. At this time, the only difference between the two is name and template ID.
If you'd like to see how the preheader text affects the open rate, then it's best to only change the Preheader Text field.
Keep in mind that different width/resolution screens will display a different amount of text, or may not show the preheader text at all.
Since this field is often displayed in a smaller font or a lighter color, sometimes the most successful preheader text values include one or two key words, or a quick and recognizable phrase.
Once you save you will be taken to the Review & Launch page which will give you the option to launch the campaign right away or schedule for a later date.
NOTE
The campaign that the experiment is created from must also be launched in order for the experiment to run.
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