Cohorts

What are cohorts?

Cohorts enable you to easily create a list of users who have something in common, such as completing an action or having the same property.

Here are a few examples of the cohorts you can create:

Users who work at the same company.
Users who used your app in the last week.
Users who have churned from your product.
Users who signed up recently.
Users who viewed the signup page, but didn't convert.

You list of cohorts are accessible from the People page.

Where can you use cohorts?

You can use cohorts in many different ways, such as:

In trends, funnels, retention, user paths, stickiness, and lifecycle insights
As a filter on any product analytics dashboard
To target feature flags, experiments, and user surveys
To filter the session replay list and create playlists
Filter live events on the Activity page
Filter users on the People page

You can use cohorts to answer questions like:

"Are people at company X using our app frequently?"
"What percentage of the users who signed up last week are still using our app?"
"Which features are power users using?"

How are cohorts different from groups?

Cohorts are sometimes confused with groups, but they each serve different purposes:

Cohorts represent a specific set of users – e.g., a list of users who's email contains a certain string (like a company's domain).
Groups aggregate events based on entities, such as organizations or companies, but do not necessarily connect to a user. They enable you to analyze trends, insights, and dashboards at an entity-level, as opposed to a user-level.

Groups require additional code in your app to set up, while cohorts are created in PostHog and don't require additional code. This makes cohorts easier to use and quicker to get started.

If your only goal is to create a list of users with something in common, we recommend cohorts instead of groups.

How to create a cohort

There are two methods to create a new cohort:

Method 1: Create a new cohort directly from an insight

You can create cohorts using data from insights such as trends, funnels, user paths and lifecycles.

Go to insights and open any insight that's aggregated by users – i.e. unique users, weekly active user, etc. Click a data point on the visualization to view the persons represented in the underlying data.
In the modal popup, click 'Save as cohort' at the bottom.

The video below shows how to create a new cohort from a trend, although you can similarly create a cohort from a funnel, user path, or any other insight.

Method 2: Create a new cohort from the cohorts page

Navigate to the People page within the sidebar, then click on the Cohorts tab.
Click '+ New Cohort' on the top right.

Static and dynamic cohorts

You have two options when creating a cohort:

Static cohorts, lists of users that don't change over time (e.g. all the users who signed up to your app in January 2024) or you update manually.
Dynamic cohorts, which are automatically updated based on a specific condition – e.g. all users who have performed a specific event or action in your app.

Static cohorts

Static cohorts are created from insights, by uploading a CSV of users, or by duplicating a dynamic cohort.

The CSV file only requires a single column with the user's distinct ID. The very first row (the header) will be skipped during import.

To update the list, you can either upload another CSV to add more users, or use the interface to remove users.

Dynamic cohorts

Dynamic cohorts can be based on existing cohorts, and support the following criteria:

Behavioral

Event or action	Example
Completed event or action	Completed `user signed up` in the last 30 days
Did not complete event or action	Did not complete `user signed up` in the last 2 months
Completed event or action multiple times	Completed `watched video` 5 times in the last 2 weeks
Completed a sequence of events or actions	Completed `user signed up` in the last 5 days followed by `watched video` within 1 day of the initial event
Did not complete a sequence of events or actions	Did not complete `user signed up` in the last 5 days followed by `watched video` within 1 day of the initial event

You can select days, weeks, months or years time ranges here.

Can use a dynamic behavioral cohort as a feature flag target? No. To use a cohort based on their behaviors as a target for a feature flag, A/B test, or survey, you must duplicate the dynamic cohort to a static one and use it.

Person properties

Has or doesn't have a person property with the following operators:

Operator	Example
`equals` or `does not equal`	`Pineapple on pizza` property `does not equal` "true"
`contains` or `does not contain`	`email` property `does not contain` "gmail"
`matches regex` or `does not match regex`	`Country code` property `matches regex` "us
`greater than` or `greater than or equal to`	`Age` property is `greater than` "21"
`less than` or `less than or equal to`	`Age property is` less than or equal to` "21"
`is set` or `is not set`	`UTM Source` property `is not set`
`between` or `not between`	`Age` property is between "18" and "30"
`minimum` or `maximum` value	`Organization size` property `minimum` of "5"

Lifecycle

Criteria	Example
Completed and event for first time	Completed `shared insight` event for the first time in the "last 30 days"
Completed an event regularly	Completed `shared insight` at least "3 times per week" for at least "3 of the last 5 periods"
Stopped doing an event	Stopped doing `shared insight` event in the "last 5 days" but had done it in the "5 days prior"
Started doing event again	Started doing `shared insight` event in the "last 5 days" but had not done it in the "5 days prior"