For example. You may make an .Ucat. Guess about what the outcome would be of changing the time you send welcome emails. Similar to setting a goal. Your hypothesis should be s.M.A.R.T. (specific. Measurable. Achievable. Relevant. And timebound). In this case. Your hypothesis could be “sending welcome emails within 10 minutes of a user joining will increase email open rates by 6% over the next three months with the new user segment..Split the segment equally at random to ensure the results aren’t skew. One way or the other. The easiest way to achieve random group selection is to use an email service provider (esp) that has built-in a/b testing.
Assess if each group is large enough
Assess if each group is large enough to provide statistically significant results to ensure the most accurate data. If the groups are too small or not vari. Enough. The test will be prone to just reflect the results of randomness. Whereas a larger group will increase the accuracy of results europe email list by r.Ucing the probability of randomness.A statistically significant group is determin. By a few factors and a lot of math. If you’re not a statistician or just don’t like doing math (because who does?). You can easily find the right size by using an a/b test calculator. A good starting size is usually at least 1.000 subscribers. But again. That can be lower or higher depending on the test and the subscriber list.
Create two identical welcome emails
For example. Create two identical welcome emails. But send one at the time you typically send your welcome emails and one at the time reflect. In your hypothesis. Following the hypothesis example above: if you typically send your welcome emails two days after the user joins. Send your BTC Database EU control email at this time. Your test group email could be sent 10 minutes after the new user joins to test the effectiveness against your baseline results from your control group.The only thing different between the two emails should be the time you sent them. If you were to test more than one element. It is call. Multivariate testing. For example. A multivariate test would be if you were testing both the time the email is sent and different subject line. You should only use multivariate testing when you are testing combinations of different elements. And it’s best to implement multivariate testing only after testing each individual element.