Late last year, Mailchimp rolled out our Send Time Optimization feature. Built on the Email Genome Project, which powers many of our other email marketing products, Send Time Optimization does just what you’d think: It suggests to users when they should send their campaigns.
"So," you might be thinking, "when is the optimal time to send?" Well, it depends on who you are and who you’re sending to: Since the Email Genome Project stores email address engagement data for billions of addresses at the individual level, these send time recommendations are personalized per user based on the subscribers on their list.
But that doesn’t mean we can’t tackle the question at a high level anyway. In this post, we’ll look at aggregate patterns from the send time optimization system and then investigate some drivers behind why different lists often have different optimal send times.
A note on how to read the graphs in this post: For this analysis we calculated the best time to send to individual addresses in their local time zones. "Best time to send" is a calculation—a function both of engagement and volume. The graphs then track the percentage of email addresses out of the population that have a particular time as their optimum. For example, 1% of email addresses might have 3am as their optimum, while 6% have 9am. Across the time horizon of a graph, these percentages will sum to 100%, because everyone has some time that’s optimal. (Also, these names can get unwieldy, so for this post I’m calling them STO and EGP. Cool?)