Track team metrics including usage stats, per-user activity, and active user counts from the dashboard
Team admins can track metrics for their team from the dashboard.
A new and upgraded metrics page is currently in development, including an API for programmatic data retrieval and will be available soon.
The metrics dashboard shows usage statistics for your team over the last 30 days:
Total Usage
View aggregate metrics across your entire team, including total tabs and premium requests used. For teams less than 30 days old, metrics reflect actual usage since team creation, including activity from team members’ individual accounts prior to joining.
Per Active User
See average usage metrics per active user, including tabs accepted, lines of code, and premium requests.
User Activity
Track both weekly and monthly active user counts.
FAQ
Analytics Report Headers
When you export analytics data from the dashboard, the report includes detailed metrics about user behavior and feature usage. Here’s what each header means:
User Information
The date when the analytics data was recorded (e.g., 2024-01-15T04:30:00.000Z)
Unique identifier for each user in the system
User’s email address associated with their account
Indicates if the user was active on this date
AI-Generated Code Metrics
Total lines of code suggested by the AI chat feature
Total lines of code suggested for deletion by the AI chat
AI-suggested lines that the user accepted and added to their code
AI-suggested deletions that the user accepted
Feature Usage Metrics
Times a user applied AI-generated changes from chat
Times a user accepted AI suggestions
Times a user rejected AI suggestions
Times AI suggestion tabs were displayed to the user
AI suggestion tabs that were accepted by the user
Request Type Metrics
Requests made through the composer/edit feature (Cmd+K inline edits)
Chat requests where users asked questions to the AI
Requests made to AI agents (specialized AI assistants)
Times the Cmd+K (or Ctrl+K) command palette was used
Subscription and API Metrics
AI requests covered under the user’s subscription plan
Requests made using API keys for programmatic access
Requests that count toward usage-based billing
Additional Features
Times the bug detection/fixing AI feature was used
Configuration Information
The AI model that the user used most frequently (e.g., GPT-4, Claude)
File extension most commonly used when applying AI suggestions (e.g., .ts, .py, .java)
File extension most commonly used with tab completion features
Version of the Cursor editor being used
Calculated Metrics
The report also includes processed data that helps understand AI code contribution:
- Total Lines Added/Deleted: Raw count of all code changes
- Accepted Lines Added/Deleted: Lines that originated from AI suggestions and were accepted
- Composer Requests: Requests made through the inline composer feature
- Chat Requests: Requests made through the chat interface
All numeric values default to 0 if not present, boolean values default to false, and string values default to empty strings. Metrics are aggregated at the daily level per user.