With A/B Testing you can split traffic randomly into different groups and show each group variations of a message. This is done by creating multiple experiences, then assigning each a percentage of traffic.
What is an A/B Test?
A/B testing, in it's true definition, is a form of statistical hypothesis testing with two variants: test and control. Within Evergage, we use A/B testing to more broadly define any campaign that uses a randomized split in the traffic to test a hypothesis. There are several things you should understand before creating an A/B test:
- When creating an Evergage campaign, you can create multiple experiences which are shown to a set percentage of traffic as determined by your needs
- As a best practice for an unbiased, statistically sound test, create messages as variations of each other. For example, testing a popup against an inline message is not a true measure of effectiveness as both invoke different behaviors for the users and cannot be compared. A better example of an A/B test would be a campaign that tests which exit popup discount code is more effective
For a better understanding of how you can design a campaign such that the results are statistically sound and do not contain any biases, please contact your Customer Success representative for guidance.
Create an A/B Test
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