# 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.

Source: https://cotera.co/solutions/ops/posthog-product-usage-tracker

---

- **Team:** Operations
- **Tools:** PostHog
- **Difficulty:** medium
- **Setup time:** 10 min
- **Time saved:** 3-4 hrs/week

## How it works
1. **Track Feature Usage** — Capture events for every feature interaction with adoption depth and frequency metadata
2. **Monitor Product Pages** — Record which sections of your product users visit most and where they spend time
3. **Segment by Behavior** — Automatically classify users as power users, active, at-risk, or churning based on usage patterns
4. **Surface Insights** — Get a usage score, milestone tracking, and actionable recommendations per user

## Example requests
- 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

## Prompt

```markdown
## Task

Use @PostHog/Capture Event to track feature usage events across your product (feature activations, workflows completed, integrations configured), @PostHog/Identify User to update user properties based on their behavior patterns (power user, at-risk, new, churning), and @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 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 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 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:**
- [milestone_1]: [description]
- [milestone_2]: [description]

**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]
```

## Related reading
- [PostHog vs Mixpanel: We Used Both for a Year. One Survived.](https://cotera.co/articles/posthog-feature-flags-guide.md)
- [PostHog Alternatives: 7 Options for Teams That Need Something Different](https://cotera.co/articles/posthog-vs-amplitude-comparison.md)