Behavioral cohorts allow you to create a custom definition of a group of users based on not only the events they have performed, but also events which they did not perform. This article will explain how you can set this up.
NOTE: Queries that include Count = 0 or Count < 1 will not be processed, and they will return zero users.
To identify users who did perform a particular event or who lack a particular property, follow one of the processes described below.
Identify users who were on product in the last 30 days but did not complete Event A
Amplitude is an event-based analytics platform, and a behavioral cohort can only identify users who have triggered at least one event in Amplitude during your selected timeframe.
But what if you want to understand users who did not trigger a key event in your platform over the last 30 days? In this example, AmpliTunes is the product, and Favorite Song or Video is the key event we are interested in. To create this cohort, we can use the did notclause, which exists as an option when you add a second event to your cohort.
This will exclude users who have triggered Favorite Song or Video at least once in the last 30 days. This will in turn help identify users who have not triggered this event.
Identify users who lack a particular user property in the last 30 days
Another common scenario is identifying all the active users who did not become a paying user at any point in time during the last 30 days. To do this, you'll once again use the did notclause.
Instead of identifying users who have Paying = false at any time in the last 30 days, you'll need to identify users who did not have Paying
= true during that same timeframe. This is because you only want users who did not pay during the entire 30 day timeframe.
If a user was not a paying user at the start of the month but became a paying user by end of this month, querying for users who have Paying = false at any time in the last 30 days will identify them.