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Zhongwei Li
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skills/analytics-plan/SKILL.md
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skills/analytics-plan/SKILL.md
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---
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description: Define analytics tracking plan for features and initiatives
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disable-model-invocation: false
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---
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# Analytics Plan
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Create comprehensive analytics tracking plans to measure feature success.
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## When to Use
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- Before implementing a new feature (define what to track)
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- When launching an experiment
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- When setting up product analytics
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- When defining success metrics
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## Used By
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- Data Analyst (primary owner)
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- Growth Marketer (growth metrics)
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- Product Manager (success metrics)
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- Full-Stack Engineer (implementation)
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---
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## Analytics Plan Template
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```markdown
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# Analytics Plan: [Feature/Initiative Name]
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**Author**: [Name]
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**Date**: [Date]
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**Status**: Draft | Approved | Implemented
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---
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## Overview
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### Feature Description
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[Brief description of the feature]
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### Business Questions
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What decisions will this data inform?
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1. [Question 1]
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2. [Question 2]
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3. [Question 3]
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### Success Criteria
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How will we know if this feature is successful?
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- **Primary Metric**: [Metric] - Target: [X]
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- **Secondary Metric**: [Metric] - Target: [X]
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- **Guardrail Metric**: [Metric] - Should not decrease by [X%]
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---
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## Event Tracking
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### Core Events
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| Event Name | Trigger | Properties | Priority |
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|------------|---------|------------|----------|
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| `[event_name]` | [When fired] | [Key properties] | P1 |
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| `[event_name]` | [When fired] | [Key properties] | P1 |
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| `[event_name]` | [When fired] | [Key properties] | P2 |
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### Event Specifications
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#### `feature_viewed`
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**Trigger**: When user views the feature for the first time in session
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**Properties**:
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| Property | Type | Required | Description |
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|----------|------|----------|-------------|
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| `source` | string | Yes | Where user came from |
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| `variant` | string | No | A/B test variant |
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| `user_tier` | string | Yes | Free/Pro/Enterprise |
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**Example**:
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```json
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{
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"event": "feature_viewed",
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"properties": {
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"source": "navigation",
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"variant": "control",
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"user_tier": "pro"
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}
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}
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```
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#### `feature_action_completed`
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**Trigger**: When user completes the primary action
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**Properties**:
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| Property | Type | Required | Description |
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|----------|------|----------|-------------|
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| `action_type` | string | Yes | Type of action |
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| `time_to_complete` | number | Yes | Seconds from start |
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| `success` | boolean | Yes | Action succeeded |
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---
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## Funnel Definition
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### Primary Funnel: [Feature Adoption]
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```
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Step 1: feature_viewed
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↓ [Target: 80%]
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Step 2: feature_started
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↓ [Target: 60%]
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Step 3: feature_completed
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↓ [Target: 40%]
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Step 4: feature_repeated (within 7 days)
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```
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### Funnel Analysis Questions
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- Where is the biggest drop-off?
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- How does drop-off vary by user segment?
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- What's the time between steps?
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---
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## User Properties
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| Property | Type | Description | When Updated |
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|----------|------|-------------|--------------|
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| `has_used_feature` | boolean | User has ever used feature | On first use |
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| `feature_usage_count` | number | Times user used feature | On each use |
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| `first_feature_use` | timestamp | When first used | On first use |
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| `last_feature_use` | timestamp | Most recent use | On each use |
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---
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## Segments
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### Key Segments to Analyze
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| Segment | Definition | Why Important |
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|---------|------------|---------------|
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| New Users | account_age < 7 days | Adoption patterns |
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| Power Users | feature_usage > 10/week | Success indicators |
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| At-Risk | no_activity > 14 days | Retention insights |
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| By Plan | plan_type = [free/pro/enterprise] | Monetization |
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---
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## Dashboard Requirements
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### Overview Dashboard
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**Purpose**: Daily monitoring of feature health
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**Metrics to Include**:
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- Daily Active Users (DAU)
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- Feature adoption rate
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- Primary action completion rate
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- Error rate
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**Filters**:
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- Date range
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- User segment
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- Platform
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### Deep Dive Dashboard
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**Purpose**: Understanding patterns and opportunities
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**Charts to Include**:
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- Funnel visualization
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- Cohort retention
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- Time-based trends
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- Segment comparison
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---
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## Experiment Plan (if applicable)
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### Hypothesis
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[Change] will lead to [X% improvement] in [metric] because [reason].
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### Test Setup
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- **Control**: [Current experience]
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- **Variant**: [New experience]
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- **Allocation**: [50/50 or other]
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- **Duration**: [X weeks]
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- **Sample Size Needed**: [X users per variant]
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### Success Metrics
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| Metric | Baseline | MDE | Direction |
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|--------|----------|-----|-----------|
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| Primary: [metric] | [X%] | [Y%] | Increase |
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| Secondary: [metric] | [X] | [Y] | Increase |
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| Guardrail: [metric] | [X%] | [Y%] | No decrease |
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### Analysis Plan
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- Primary analysis at [X] days
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- Segment analysis by [dimensions]
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- Document learnings regardless of outcome
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---
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## Implementation Checklist
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### Before Development
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- [ ] Analytics plan reviewed by data/product
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- [ ] Event names follow naming convention
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- [ ] Success metrics approved
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### During Development
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- [ ] Events implemented with correct properties
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- [ ] Events fire at correct times
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- [ ] Properties populated correctly
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### Before Launch
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- [ ] Events tested in staging
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- [ ] Dashboard created
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- [ ] Baseline metrics captured
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- [ ] Alert thresholds set
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### After Launch
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- [ ] Verify data flowing correctly
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- [ ] Check for data quality issues
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- [ ] Monitor metrics daily for first week
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---
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## Data Quality Checks
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| Check | Query/Method | Expected |
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|-------|--------------|----------|
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| Events firing | Count by day | > 0 after launch |
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| Required properties | Null check | No nulls |
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| Property values | Distinct values | Expected options |
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| User join rate | user_id present | 100% |
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```
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---
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## Event Naming Convention
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### Format
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```
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[object]_[action]
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```
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### Objects (nouns)
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- `page` - Page views
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- `button` - Button interactions
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- `form` - Form interactions
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- `feature` - Feature usage
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- `subscription` - Subscription events
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- `user` - User lifecycle
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### Actions (past tense verbs)
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- `viewed` - Something was seen
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- `clicked` - Something was clicked
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- `submitted` - Form was submitted
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- `started` - Process began
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- `completed` - Process finished
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- `failed` - Something went wrong
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### Examples
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```
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page_viewed
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button_clicked
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form_submitted
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feature_started
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feature_completed
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subscription_upgraded
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user_signed_up
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```
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---
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## Property Guidelines
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### Always Include
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- `timestamp` - When event occurred
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- `user_id` - Logged-in user identifier
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- `session_id` - Session identifier
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- `platform` - web/ios/android
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- `page` - Current page/screen
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### Contextual Properties
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- `source` - What triggered the action
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- `variant` - A/B test variant
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- `value` - Numeric value if applicable
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- `error_type` - For error events
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### Naming Rules
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- Use `snake_case`
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- Be descriptive but concise
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- Use consistent naming across events
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- Document allowed values for enums
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---
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## Metrics Definitions
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### Common Metrics
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**Daily Active Users (DAU)**
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```
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Count of unique users with any event in past 24 hours
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```
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**Activation Rate**
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```
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(Users who completed key action) / (Users who signed up) × 100
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```
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**Retention Rate (Day N)**
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```
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(Users active on day N) / (Users who signed up N days ago) × 100
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```
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**Feature Adoption**
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```
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(Users who used feature) / (Total users) × 100
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```
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**Conversion Rate**
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```
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(Users who completed goal) / (Users who started flow) × 100
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```
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---
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## Quick Reference
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### Before Feature Launch
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1. Define success metrics
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2. Create event tracking plan
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3. Implement events
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4. Test in staging
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5. Set up dashboard
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6. Capture baseline
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### After Feature Launch
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1. Verify data quality
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2. Monitor daily
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3. Analyze after 1 week
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4. Deep dive after 1 month
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5. Document learnings
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