Schaun Wheeler
August 26, 2022
2 MIN READ
Data Science

How many different timing preferences could users really have?

You just can’t manage all the different timing patterns by hand. And you don't have to.

We wrote recently about the importance of getting the timing of a message right. This short post uses data from one of our customers' actual messages to show what we mean by that. 

They say a picture is worth a thousand words. This one is worth hundreds of thousands of active users:

To conduct this analysis, we mined the history of our “personalization scores”. 

Personalization scores are how Aampe records user preferences, so for every possible change you could make to a message—whether sending on a different day, or at a different time, or with different content—every user in the system gets a score that estimates that specific user’s probability of responding positively to that choice. 

The chart above shows the top 40 patterns of “strong” preference (users who scored in the top third of the personalization score index for one or more message timing slots), and the bigger the dot, the more users showed that preference. 

  • The very top row was a relatively large number of users who only like to get messages on Tuesdays—but not late night on Tuesday
  • The next row is a big group of users who only want messages on Sundays. 
  • The row after that is a group that wants messages on Tuesdays, but not in the evening—not even early evening. 
  • The next row after that is a group of users who are good with pretty much any time we want to send them something.

You can see there are a bunch of groups who are good with almost all times, but who really don’t respond during a few key windows, and there’s another group that’s only ok with Monday mornings, and another that’s only ok with lunchtime on Wednesdays.

Also note the note at the bottom of the plot: There are 482 other timing preference patterns that we didn’t try to show, because it was too much to fit into one picture. 

Those 482 other preference groups, however, represent a full third of the user base.

In other words, there are hundreds, sometimes thousands, of preference patterns you need to take into account if you want to send each user a message at a time when they’re likely to act on it (and if you want to not send a user a message at a time that annoys them). 

You just can’t manage all of these different timing patterns by hand. 

Thankfully, you don’t have to.

Email hello@aampe.com, and give Aampe a test drive today.