Once you have segmented lists, it’s time to form a hypothesis, or “educated guess,” just like you would in a scientific test. To develop your hypothesis, first pick a segment of your list to focus on, then pick a single element to test that’s key for that group.
For example, you may make an educated 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.
Now that you’ve
formed your hypothesis, split the subscriber segment in two: an “A” group for your control group and a “B” group Australia Phone Number Data for your test group.
Split the segment equally at random to ensure the results aren’t skewed one way or the other. The easiest way to achieve random group selection is to use an that has built-in.
Assess if each
group is large enough to provide results to ensure the most accurate data. If the groups are too small or not varied enough, the test will be prone to just reflect the results of randomness. Whereas a larger group will increase the accuracy of results by reducing 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 good starting size is B2C phone List usually at least 1,000 subscribers, but again, that can be lower or higher depending on the test and the subscriber list.To test a specific aspect of your email, create two variations of the same email with just that single element changed to reflect your hypothesis.
