To segment your subscriber list, divide your email list into smaller lists according to key characteristics, such as demographic, business type, purchase behavior, or location. Segments will allow you to see what has the most impact on each brand audience as well as provide more targeted email marketing in the future. Ideally, your email marketing platform should have a segmentation tool that will make it easy to do. Here’s how it works on Campaign Monitor’s platform.
Form a hypothesis
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 Brazil Phone Number Data 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.”
Split each segment into an “A” and “B” test group
Now that you’ve formed your hypothesis, split the subscriber segment in two: an “A” group for your control group and a “B” group 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 email service provider (ESP) that has built-in A/B testing.
Create “A” and “B” test assets
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. Assess if Betting Email List each group is large enough to provide statistically significant 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.
