cotera

PostHog Product Usage Tracker

Track feature adoption, identify power users, and catch churn signals before they become cancellations. Build a complete product usage intelligence layer in PostHog.

Feature adoptionUser segmentationChurn preventionProduct intelligence

The Challenge

You know some users love your product and others churn after a week, but you cannot tell the difference until it is too late. Feature usage data sits in PostHog as raw events with no structure, so you cannot answer basic questions like which features correlate with retention or which users are power users versus at-risk. Manually tagging users based on behavior is impossible at scale, and without behavior-based segments, your product and customer success teams are flying blind.

What This Prompt Does

Track Feature Usage

Capture events for every feature interaction with adoption depth and frequency metadata

Monitor Product Pages

Record which sections of your product users visit most and where they spend time

Segment by Behavior

Automatically classify users as power users, active, at-risk, or churning based on usage patterns

Surface Insights

Get a usage score, milestone tracking, and actionable recommendations per user

The Prompt

The Prompt

Task

Use @PostHog/Capture EventName it "PostHog/Capture Event" and call it with @PostHog/Capture Event to track feature usage events across your product (feature activations, workflows completed, integrations configured), @PostHog/Identify UserName it "PostHog/Identify User" and call it with @PostHog/Identify User to update user properties based on their behavior patterns (power user, at-risk, new, churning), and @PostHog/Track Page ViewName it "PostHog/Track Page View" and call it with @PostHog/Track Page View to record which product pages and sections users visit most. This builds a product usage intelligence layer in PostHog that reveals who your power users are, which features drive retention, and where users get stuck.

Input

The user provides:

  1. Feature usage events to track (e.g., "report_generated", "integration_connected", "team_member_invited")
  2. Product pages or sections to monitor (e.g., "/dashboard", "/settings/integrations", "/reports")
  3. User identifier and current properties
  4. Behavior-based segments to assign (e.g., power user = 10+ features used, churning = no activity in 7 days)

Example: "Track product usage for user_789 on our project management tool: they viewed the dashboard, created a project, invited 3 team members, and connected the Slack integration. Update their user segment to power_user."

Context

Feature Usage Tracking

  1. Use @PostHog/Capture EventName it "PostHog/Capture Event" and call it with @PostHog/Capture Event for each feature interaction:
    • Feature activations: "feature_activated" with feature name, first use flag
    • Workflow completions: "workflow_completed" with workflow name, duration, steps
    • Configuration changes: "setting_changed" with setting name, old value, new value
    • Integration events: "integration_connected", "integration_used" with provider name
  2. Include contextual properties:
    • Feature name and category
    • Whether this is the first time the user used this feature
    • Time since last usage of this feature
    • Usage count (if tracking frequency)
  3. Track milestone events:
    • "first_project_created", "tenth_report_generated"
    • "all_integrations_configured", "team_fully_onboarded"
    • "usage_milestone_reached" with milestone details

Product Page Monitoring

  1. Use @PostHog/Track Page ViewName it "PostHog/Track Page View" and call it with @PostHog/Track Page View for key product pages
  2. Focus on pages that indicate engagement:
    • Dashboard views (daily active usage signal)
    • Settings pages (configuration depth)
    • Feature-specific pages (adoption signals)
    • Help/docs pages (confusion signals)
  3. Include properties:
    • Page section and subsection
    • Time on page (if available)
    • Navigation source (sidebar, search, notification)

Behavior-Based User Segmentation

  1. Use @PostHog/Identify UserName it "PostHog/Identify User" and call it with @PostHog/Identify User to update segment properties based on observed behavior:
    • Power user: High feature adoption, frequent sessions, uses advanced features
    • Active user: Regular usage of core features
    • At-risk: Declining usage, fewer features used over time
    • New user: Recently signed up, still in onboarding
    • Churning: No activity for extended period
  2. Set quantitative properties:
    • features_used_count: number of distinct features used
    • last_active_date: timestamp of most recent activity
    • session_count_30d: sessions in the last 30 days
    • onboarding_completion: percentage of onboarding steps done
  3. Set qualitative properties:
    • user_segment: power_user, active, at_risk, new, churning
    • product_fit: based on which features they use
    • expansion_candidate: true/false based on usage patterns

Usage Intelligence

After tracking all events:

  • Summarize which features the user engaged with
  • Calculate a usage score based on breadth and depth of feature adoption
  • Identify the user's behavioral segment
  • Flag any usage patterns that indicate churn risk or expansion opportunity

Output

Product Usage Tracking Summary:

User Profile:

  • Distinct ID: [user_id]
  • Segment: [power_user/active/at_risk/new/churning]
  • Features used: [count] of [total available]
  • Usage score: [calculated score]

Feature Usage Events: | Event | Feature | Properties | First Use? | Status | |-------|---------|-----------|------------|--------| | [event] | [feature] | [key props] | [yes/no] | Sent |

Product Pages Viewed: | Page | Section | Properties | Status | |------|---------|-----------|--------| | [page] | [section] | [key props] | Tracked |

Milestones Reached:

User Properties Updated: | Property | Value | Reason | |----------|-------|--------| | user_segment | [segment] | [behavior evidence] | | features_used_count | [count] | [features list] | | last_active_date | [date] | [most recent event] |

Behavioral Insights:

  • [1-2 sentence summary of usage patterns and segment assignment]
  • Recommended next action: [retention play, expansion opportunity, or onboarding nudge]

Example Usage

Try asking:

  • →"Track product usage for user_789: they created a project, invited 3 team members, connected Slack, and generated 2 reports. Classify their segment."
  • →"Set up feature tracking for our analytics tool: capture dashboard_viewed, report_created, filter_applied, and export_downloaded events for user alex@company.com"
  • →"Track onboarding completion for new user trial_user_42: they visited /dashboard, /settings, and /integrations, and completed 3 of 5 onboarding steps"