How to Test Sending Times

Testing the best sending times for your newsletter is a valuable way to learn more about the behaviors of your readers and the best times to reach them. We’ve already talked about techniques to utilize in creating a simple case study and those rules all apply here. In order to test sending times, try to keep everything else as constant as you can; don’t try sending new types of content at this time and keep your subject lines and calls to action consistent with your usual email marketing practices. 

Step One:  Examine Potential Windows
Consider your demographics. Who is opening your emails and where? This information is vital. If you are primarily sending to professionals engaging with your emails as a course of business, then you want to identify times during their work week when they will be apt to open, read, and respond to calls to action in emails. On the other hand, if you are sending emails that are being opened by individuals in their leisure time, your tactic will need to be different. Keep in mind that most emails are opened during the day on weekdays, although this is certainly subject to variability based on industry and unique subscriber lists. Unless you have a strong reason to suspect that yours is an exception, stick to the more common email-opening time slots.

Step Two:  Design and Execute the Test
If you’re a science geek like me, this part is quite exciting. Now, you don’t have to go brush up on the scientific method, just decide on a basic approach. Stick to one of two options: run an A/B test or design a longer-term test in which you send to the entire group.

Let’s back up. First pick a few (not more than four) times during the day/week that you’d like to test. Then determine your test method.

For an A/B Test you’ll need to divide your readership into two groups. Make sure that you are sending to an active readership when doing this. (You want to know that you have active engaged subscribers on both the A and the B side of the testing). Send to the A group at one of your test times and the B group at the other. Continue with each of the times you are testing for.

NOTE: if you pick more than two times, you will be doing an A/B/C or A/B/C/D test.

For a trial that uses your entire readership, simply lengthen the time span and schedule sends for each of your test times while sticking to your normal sending schedule. Sending more emails than usual could skew your data. To check for consistency, send a few times at each of the times you have selected.

Step Three:  Adjust As Necessary
If you experienced clear and measurable results, then adjust course and continue to actively observe your metrics to ensure that you continue to see the results you expect. If you didn’t see a difference, then you may choose to test at more unconventional times. Of course, this might also be a sign it’s time to give closer examination to other aspects of your approach such as subject line and call to action. 

Other potential factors that will require you to adjust course will be unexpected or confusing results. Say you start sending at 3pm in the afternoons on Thursday and see a fast increase in the number of opens, but the number of click-throughs decrease and fewer readers respond to the call-to-action. This lets you know that you’ve found a viewing time, but you’ve yet to hit on your subscribers’ action time. All isn’t lost here - you know exactly when to send if you want to prime readers for a future call to action… you just have to find out what time to send that email. All information that you gain is useful once you see how it applies to the bigger picture.

P.S.  If you want to get fancy….
Once you’ve conducted such a test, you have a wealth of information at your fingertips that, if you so choose, can be used to further research and segment subscriber behavior. For example, if you collect personal data such as gender, you could examine the behaviors of your male and female readers to determine if there were any significant differences in open rates between the two during the times you tested.