Run your test on a platform that can measure results . Now it’s finally time to hit play on your test. Make sure you send your email from an esp that has a strong analytics dashboard so you can easily measure and assess the results. Remember to isolate all variables except the one you’re testing. So if you’re testing send times. Don’t write different subject lines and send on different days of the week or different times of day. Include the same subject lines in both emails. And just change the time sent.
Analyze the data
Analyze the data Once you’ve run your test. It’s time to assess the outcomes and determine if your hypothesis was correct or not. When testing the hypothesis above. For example. Look at open rates for each country email list email segment to measure the impact of send time. Whichever group had the highest open rate would be the “winner.”If you’re using an esp that has built-in a/b testing. The platform should do most of the hard work for you. For example. In campaign monitor’s a/b test analytics dashboard. You can view graphs of your results and conversion values all at the same time.
The results in light of your overall email
In addition to analyzing the results as they pertain to the individual test. Assess the results in light of your overall email newsletter performance. This will allow you to gain further insights into CH Leads the potential impact it could have on other email segments. For example. If a personaliz subject line increas open rates with new customers. Consider running the same test with other list segments .Optimize bas on the results The data you gather and analyze will only go as far as you implement it. The key to long-term vitality is to implement the changes indicat by the test results as well as continuously iterate on them. Your audience’s nes change.