This article covers some frequently asked questions about Behavioral Cohorts.
How do I group users with a certain property value that was recently introduced?
To create a cohort of these users, you can use the most recently feature. This will find users who had a certain property value on their most recent active event in the time frame given.
For example, here Amplitude is querying for users who most recently had "Germany" as the value for the
country user property in the last 30 days:
Why does the .CSV file keep failing when creating a cohort?
The .CSV file may only contain user IDs or Amplitude IDs, but not both in the same file. Also, the .CSV cannot contain any other information. (Read more about uploading CSVs as cohorts.) Your .CSV should contain no blank space or other text. If the file is not in the correct format, Amplitude will show an error message and refuse to upload the cohort.
A properly-formatted .CSV file looks like this:
Why is the cohort definition non-modifiable?
While it is possible to create cohorts from certain charts, particularly funnel and retention charts, it is not possible to modify the events from within these cohorts. In this example, the steps are present, but not modifiable. In order to change them, return to the source of the chart, change the steps there, and recreate a new cohort.
Why doesn't this cohort support population over time?
Cohort population is only supported for dynamic cohorts, i.e., cohorts that can be recomputed according to specified criteria. It is not supported for static cohorts. Examples of static cohorts include those imported from a .CSV file or created using Microscope within charts.
How do I create a cohort of users who fired an event a specific number of times in the last 30 days?
The count feature in cohorts allows you to segment these users. The following cohort definition will segment users who fired
Play Song or Video ten times or more in the last 30 days.
How can I identify users who lack user properties or did not perform events?
You can 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.
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 not clause, 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 not clause.
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
= 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.
Read on for more information about cohorts in Amplitude.