# PostHog Mobile Analytics Tracker

> Track screen views, in-app events, and user engagement across your mobile app with PostHog. Get full visibility into how users navigate and interact with your product.

Source: https://cotera.co/solutions/ops/posthog-mobile-analytics-tracker

---

- **Team:** Operations
- **Tools:** PostHog
- **Difficulty:** medium
- **Setup time:** 10 min
- **Time saved:** 2-3 hrs/week

## How it works
1. **Track Screen Views** — Record every screen transition with names, paths, and navigation context for session flow analysis
2. **Capture In-App Events** — Send events for taps, swipes, purchases, and feature usage with full device context
3. **Identify Mobile Users** — Associate devices with users and set properties like subscription tier, OS version, and app version
4. **Map Session Flows** — Visualize how users navigate through your app and identify the most common paths

## Example requests
- Track screen views for our fitness app: Home, Workout, Progress, and Profile screens for user_456 on iOS 17
- Capture in-app events for our e-commerce app: product_viewed, add_to_cart, and checkout_completed with product and price properties
- Set up mobile analytics for our meditation app: track session screens, capture meditation_started and meditation_completed events, identify the user with their subscription tier

## Prompt

```markdown
## Task

Use @PostHog/Track Screen View to record mobile screen views as users navigate through your app, @PostHog/Capture Event to capture in-app engagement events like taps, swipes, form submissions, and feature usage, and @PostHog/Identify User to identify mobile users with their properties. This builds a complete mobile analytics setup in PostHog that shows how users move through your app and which features drive engagement.

## Input

The user provides:
1. Screen names and paths to track (e.g., "Home Screen", "Profile Settings", "Checkout")
2. In-app events to capture (e.g., "button_tapped", "item_added_to_cart", "search_performed")
3. User identifier and properties (e.g., user ID, device type, app version)
4. Optional: engagement metrics to focus on (session length, feature adoption, retention signals)

**Example:** "Track mobile analytics for our fitness app: screen views for Home, Workout, Progress, and Profile screens. Capture workout_started, exercise_completed, and streak_achieved events. Identify the user with their subscription tier and device info."

## Context

### Screen View Tracking

1. Use @PostHog/Track Screen View for each screen the user visits
2. Include properties with each screen view:
   - Screen name (human-readable, e.g., "Workout Detail")
   - Screen path or route (e.g., "/workout/detail")
   - Previous screen (for navigation flow analysis)
   - App section or tab (e.g., "training", "social", "profile")
3. Track screens in the order users navigate to build session flow visibility
4. Note time spent context where available

### In-App Event Capture

1. Use @PostHog/Capture Event for meaningful user interactions:
   - Core actions: feature used, item created, content viewed
   - Engagement signals: share, save, favorite, comment
   - Commerce events: add to cart, purchase, subscription change
   - Error events: crash, timeout, failed action
2. Include contextual properties:
   - Screen where the action occurred
   - Content or feature identifier
   - User state (logged in, trial, premium)
   - Device context (OS version, app version, device model)
3. Use consistent naming: "object_action" format (e.g., "workout_started", "photo_uploaded")

### Mobile User Identification

1. Use @PostHog/Identify User to associate the device with a known user
2. Set mobile-specific properties:
   - Device type (iOS/Android), OS version, app version
   - Subscription tier, account type
   - Push notification status (enabled/disabled)
   - First app open date, total sessions
3. Update properties when they change (e.g., app update, plan change)

### Engagement Analysis

After tracking is set up:
- Summarize the screen flow recorded
- List all events captured with their properties
- Identify which screens and features show the most engagement
- Flag any gaps in tracking coverage

## Output

**Mobile Analytics Setup Summary:**

**User Identified:**
- Distinct ID: [user_id]
- Device: [device_type] / [os_version]
- App version: [version]
- Properties set: [list]

**Screen Views Tracked:**
| Screen | Path | Properties | Status |
|--------|------|-----------|--------|
| [Screen Name] | [/path] | [key props] | Tracked |

**In-App Events Captured:**
| Event | Screen Context | Properties | Status |
|-------|---------------|-----------|--------|
| [event_name] | [screen] | [key props] | Sent |

**Session Flow:**
[Screen 1] -> [Screen 2] -> [Screen 3] -> ...

**Coverage Summary:**
- Screens tracked: [count]
- Events captured: [count]
- User properties set: [count]
- Ready to analyze in PostHog mobile analytics
```

## Related reading
- [PostHog API Integration: Everything You Can Automate (With Examples)](https://cotera.co/articles/product-analytics-platform-comparison.md)