> ## Documentation Index
> Fetch the complete documentation index at: https://mintlify.com/mixpanel/docs/llms.txt
> Use this file to discover all available pages before exploring further.
# Cohorts
> Group users by demographic and behavior
# Cohorts: Group Users by Behavior
Cohorts are groups of users that share a set of properties or perform a similar sequence of events. Mixpanel lets you visually define cohorts, view the users in them, compare them in analysis, and share them across your organization.
## What are Cohorts?
Cohorts represent user segments based on who they are or what they do:
**Demographic Cohorts:**
* **US Users** - Users from the United States
* **Premium Subscribers** - Users with premium plans
* **Mobile Users** - Users on mobile devices
**Behavioral Cohorts:**
* **New Users** - Signed up in the past month
* **Power Users** - Used app on 5 of last 7 days
* **Dropped-Off Users** - Signed up but didn't return
* **High-Value Customers** - Spent over \$500 lifetime
## Use Cases
Cohorts enable powerful segmentation and targeting:
### Analysis and Insights
* Compare power users vs casual users
* Track new user growth over time
* Analyze retention by acquisition channel
* Identify high-value customer behaviors
### Marketing and Messaging
* Target campaigns to specific user segments
* Re-engage churned users
* Personalize messaging by user type
* Exclude existing customers from acquisition ads
### Product Development
* Test features with beta user cohort
* Measure feature adoption by segment
* Understand different user personas
* Prioritize based on segment size
## Creating Cohorts
There are three main ways to create cohorts:
### 1. From a Report
Click any data point in Insights, Funnels, or Retention:
1. Click a bar, point, or segment
2. Select **View Users**
3. Click **Save as Cohort**
4. Name your cohort
**Example:** In a funnel report, click users who dropped off at checkout to create a "Checkout Abandoners" cohort.
### 2. Using the Cohort Builder
The [Cohort Builder](https://mixpanel.com/report/users) lets you define precise conditions:
**Filter by Event Behavior:**
**Example:** Users who watched more than 10 videos in the last 7 days
**Filter by First-Time Actions:**
**Example:** Users who watched a video for the first time in the past 30 days
**Chain Multiple Conditions:**
**Example:** Power users who are also premium subscribers
You can access the Cohort Builder from any report by clicking **Create Custom > Cohort** in the query builder.
### 3. From a CSV File
Upload a list of user IDs to create a cohort:
**Use Cases:**
* Random sample selections
* External data sources
* Lists from other tools
* Custom user groups
**Steps:**
1. Create CSV with two columns:
* Column 1: `$distinct_id` values
* Column 2: Property value (e.g., "inCohort" = "yes")
2. Go to **Users** → **Add/Edit Profile** → **Import from CSV**
3. Map columns:
* Column 1: `$distinct_id`
* Column 2: Your property name
4. Create cohort using the new property
If a `$distinct_id` doesn't exist, Mixpanel will create a new user profile. CSV cohorts are static and won't update over time.
## Cohort Conditions
Build sophisticated cohorts with multiple condition types:
### Event-Based Conditions
**Basic Event Filters:**
* Users who did \[event] more than X times
* Users who did \[event] in last N days
* Users who did \[event] at least once ever
**Property Filters:**
* Users who did \[event] where \[property] = \[value]
* Users who did \[event] where \[property] > \[number]
**Sequence Filters:**
* Users who did \[event A] and then \[event B]
* Users who did \[event A] but not \[event B]
### Profile-Based Conditions
**User Properties:**
* Users where \[property] equals \[value]
* Users where \[property] is set
* Users where \[property] > \[number]
**Historical Properties:**
With historical properties, specify when the property had a value:
**Example:** Users who had "Plan" = "Trial" in the last 30 days
**User Property Behavior**: User properties store only the most recent value. Without historical properties, cohorts use the current value even if it changed over time.
### Combining Conditions
**AND Logic:**
* All conditions must be true
* Creates more specific segments
* Example: Premium users AND active in last 7 days
**OR Logic:**
* Any condition can be true
* Creates broader segments
* Example: Watched video OR purchased item
## Using Cohorts in Analysis
### Visualize Cohort Size Over Time
In Insights, select a cohort as a metric:
* See how cohort grows or shrinks
* Track power user population
* Monitor churn cohorts
* Measure acquisition success
**Example:** Track "Active Premium Users" cohort size daily
### Filter by Cohort
Apply cohorts as filters in any report:
* Focus analysis on specific user segment
* Exclude test users or employees
* Analyze beta users separately
* Compare before/after feature access
**Example:** Filter all reports to "New Users" (signed up in last 7 days)
### Compare Cohorts
Breakdown metrics by cohorts:
* Power Users vs Casual Users engagement
* Free vs Premium conversion rates
* iOS vs Android retention
* Geographic segment performance
**Example:** Compare retention for "Organic" vs "Paid" acquisition cohorts
**Multiple Cohort Breakdown**: When breaking down by cohorts, each event is evaluated independently. An event can contribute to multiple cohort buckets if the user belongs to multiple cohorts.
## How Cohorts are Computed
Cohorts are computed dynamically when you use them:
**Process:**
1. Run query to compute current cohort membership
2. Run analysis query filtering to those users
**Implications:**
* **Always Fresh** - Cohort membership updates with new data
* **Point-in-Time** - Uses current membership, not historical
* **Performance** - Large cohorts may slow queries
**New Data Timing**: Newly imported events timestamped more than 30 days ago may take up to 12 hours to appear in cohort analysis.
### Cohorts vs Funnels for Sequences
When analyzing event sequences, should you use cohorts or funnels?
**Use Cohorts When:**
* You want current users who did sequence
* Comparing user characteristics
* Using in other reports as a filter
**Use Funnels When:**
* You care about conversion window
* Measuring time to convert
* Tracking conversion rate trends
**Example:**
**Cohort:** Users who watched comedy video AND subscribed (ever)
* Shows users who did both
* No time relationship
* Static snapshot
**Funnel:** Watch comedy video → Subscribe (30-day window)
* Measures conversion rate
* Tracks time to convert
* Dynamic trending
## Managing Cohorts
Access all cohorts in [Lexicon](/docs/data-governance/lexicon) → **Cohorts**
### Sharing Cohorts
**Visibility Options:**
* **Private** - Only you can see it (default)
* **Specific People** - Share with selected teammates
* **Organization** - Everyone in project can use it
**Best Practices:**
* Share core cohorts organization-wide (New Users, Power Users)
* Add clear descriptions for shared cohorts
* Use consistent naming conventions
* Document cohort definitions
**Plan Limits**: Growth and Enterprise plans support unlimited saved cohorts. Free plans can create cohorts but cannot save them.
### Exporting Cohorts
**CSV Export:**
* Download user list from Cohort Builder
* Contains user IDs and basic properties
* Use for external analysis
**Cohort Sync:**
* Push to [native destinations](/docs/cohort-sync) (Segment, Braze, etc.)
* Use [webhooks](/docs/cohort-sync/webhooks) for custom destinations
* Automate marketing campaigns
* Sync with ad platforms
### Deleting Cohorts
In Lexicon → Cohorts:
1. Click "..." next to cohort
2. Select **Delete**
3. Confirm deletion
Deleting a cohort removes it from all reports and boards where it's used.
## Real-World Examples
### Example 1: Power Users
**Definition:**
* Users who used app on 5+ of last 7 days
* AND total sessions > 20
* AND Last seen within 7 days
**Use Cases:**
* Compare power user behavior vs average
* Test new features with engaged users
* Identify behaviors that drive engagement
### Example 2: Churned Users
**Definition:**
* Users who signed up
* AND did NOT use app in last 30 days
* AND last seen between 31-90 days ago
**Use Cases:**
* Re-engagement campaigns
* Win-back messaging
* Churn analysis
### Example 3: High-Value Customers
**Definition:**
* Users where Lifetime Revenue > \$500
* AND Purchase count > 5
* AND Last purchase within 90 days
**Use Cases:**
* VIP treatment programs
* Loyalty rewards
* Cross-sell campaigns
### Example 4: Activation Cohort
**Definition:**
* Users who signed up
* AND completed profile
* AND invited 1+ friends
* AND created first project
* Within 7 days of signup
**Use Cases:**
* Track activation rate trends
* Compare activated vs non-activated retention
* Optimize onboarding flow
### Example 5: Trial Conversion
**Definition:**
* Users where Current Plan = "Trial"
* AND Trial Start Date between -7 and 0 days
* AND did NOT convert to paid
**Use Cases:**
* Trial conversion campaigns
* Identify conversion blockers
* Compare trial behaviors
## Tips for Effective Cohort Usage
**Start with Key Segments**: Define core user segments that matter to your business (New, Active, Power, Churned, etc.)
**Use Descriptive Names**: Name cohorts clearly so anyone can understand what they represent ("iOS Users - Last 30 Days" vs "Cohort 1")
**Add Descriptions**: Explain the purpose and definition of shared cohorts to ensure consistent usage across your team.
**Review Regularly**: Audit cohorts monthly to remove unused ones and update definitions as your product evolves.
**Combine with Analysis**: Use cohorts to segment all your reports - insights become much more actionable when segmented.
**Track Cohort Size**: Create an Insights report showing cohort sizes over time to monitor segment health.
## Common Questions
**Q: Can I create cohorts for users who dropped off in a funnel?**
A: Yes! In a Funnels report, click the drop-off segment and select "View Users" → "Save as Cohort".
**Q: How do I find users who did Event A but NOT Event B?**
A: In the Cohort Builder:
* Add condition: Users who did Event A
* Add condition: Users who did NOT do Event B
* Combine with AND logic
**Q: Why is my cohort size changing?**
A: Cohorts are dynamic and recompute with current data. Use specific date ranges in conditions to create more stable cohorts.
**Q: Can I combine multiple cohorts?**
A: Yes! Create a new cohort with conditions:
* User in Cohort A AND User in Cohort B (intersection)
* User in Cohort A OR User in Cohort B (union)
**Q: How do I exclude a cohort from analysis?**
A: Add a filter: "User NOT in \[Cohort Name]"
## Next Steps
* Use cohorts in [Insights](/reports/insights) for segmented analysis
* Compare cohorts in [Funnels](/reports/funnels)
* Track cohort retention in [Retention](/reports/retention)
* Learn about [Cohort Sync](/docs/cohort-sync) for marketing automation