---
created: 2026-03-12
source: Rivet
tags: [agent-archive, rivet]
---

# RateRight Analytics & Metrics Plan

## 1. Key Metrics Dashboard

### Conversion Metrics
- **Signup Conversion Rate**: (Landing page visitors → Registered users) × 100
  - Target: >15% industry standard
  - Track by traffic source and user type (contractor vs worker)
  - Monitor drop-off points in signup funnel

- **Time to First Job Post (Contractors)**
  - Definition: Days from registration to first job posting
  - Target: <7 days for active contractors
  - Segment by contractor industry/experience level

- **Time to First Application (Workers)**
  - Definition: Days from registration to first job application
  - Target: <3 days for active job seekers
  - Track by worker skills/qualifications

### Matching & Hiring Metrics
- **Match Rate**: (Jobs with matched workers ÷ Total jobs posted) × 100
  - Target: >80% within 48 hours
  - Track by job category and urgency level
  - Monitor match quality score

- **Hire Rate**: (Matches that result in hires ÷ Total matches) × 100
  - Target: >60% conversion from match to hire
  - Track reasons for non-hires
  - Monitor by contractor/worker ratings

- **Average Time to Fill a Job**: Hours from job posting to successful hire
  - Target: <48 hours for standard jobs
  - Track by job category and urgency
  - Monitor seasonal variations

### Payment & Retention Metrics
- **Payment Completion Rate**: (Successful payments ÷ Total payment attempts) × 100
  - Target: >95% success rate
  - Track by payment method
  - Monitor failed payment reasons

- **Repeat Hire Rate**: (Contractors hiring same worker multiple times ÷ Total hires) × 100
  - Target: >40% for quality matches
  - Track by industry and job type
  - Monitor worker performance correlation

- **Worker Retention (Monthly Active)**: (Workers active in last 30 days ÷ Total registered workers) × 100
  - Target: >60% monthly active rate
  - Track by registration cohort
  - Monitor churn reasons

- **Contractor Retention (Monthly Active)**: (Contractors posting jobs in last 30 days ÷ Total registered contractors) × 100
  - Target: >50% monthly active rate
  - Track by industry and company size
  - Monitor satisfaction correlation

### Satisfaction Metrics
- **Net Promoter Score (NPS)**: "How likely are you to recommend RateRight?" (0-10 scale)
  - Target: >50 (excellent)
  - Survey quarterly
  - Segment by user type and tenure

- **Customer Satisfaction (CSAT)**: Post-interaction satisfaction rating (1-5 stars)
  - Target: >4.5 average
  - Collect after job completion
  - Track by contractor and worker separately

## 2. Analytics Tools Recommendation

### Primary Analytics Stack (Free/Cheap Tier)
1. **PostHog** (Free up to 1M events/month)
   - Product analytics and event tracking
   - User journey analysis
   - Feature flags for A/B testing
   - Session recordings
   - Setup complexity: Medium
   - Cost: Free tier sufficient for MVP

2. **Google Analytics 4** (Always free)
   - Website traffic analysis
   - User acquisition tracking
   - Basic conversion tracking
   - Setup complexity: Low
   - Cost: Free

3. **Supabase Analytics** (Built-in with Supabase)
   - Database-level metrics
   - User authentication events
   - API performance monitoring
   - Setup complexity: Low (already using Supabase)
   - Cost: Included

### Secondary Options (Consider Later)
4. **Mixpanel** (Free up to 100K monthly users)
   - Advanced product analytics
   - Cohort analysis
   - Funnel optimization
   - Setup complexity: Medium
   - Cost: Free tier may be limiting

5. **Custom Dashboard** (Build in-house)
   - Real-time metrics display
   - Custom KPI tracking
   - Business intelligence
   - Setup complexity: High
   - Cost: Development time only

### Implementation Priority
1. Start with GA4 for basic traffic analysis (Day 1)
2. Add PostHog for product analytics (Week 1)
3. Leverage Supabase analytics for backend metrics (Ongoing)
4. Consider Mixpanel when hitting PostHog limits (Month 6+)
5. Build custom dashboard for executive reporting (Month 12+)

## 3. Event Tracking Plan

### User Acquisition Events
```javascript
// Landing page
analytics.track('landing_page_viewed', {
  page: 'home',
  traffic_source: 'google_ads',
  utm_campaign: 'summer_promotion'
});

// Signup flow
analytics.track('signup_started', {
  user_type: 'contractor', // or 'worker'
  method: 'email',
  page: 'signup_form'
});

analytics.track('signup_completed', {
  user_type: 'contractor',
  method: 'email',
  time_to_complete: 45, // seconds
  fields_completed: 8
});
```

### Job Posting Events (Contractors)
```javascript
// Job lifecycle
analytics.track('job_post_started', {
  contractor_id: 'user_123',
  job_category: 'construction',
  form_version: 'v2_simplified'
});

analytics.track('job_post_completed', {
  contractor_id: 'user_123',
  job_id: 'job_456',
  job_category: 'construction',
  urgency: 'urgent',
  time_to_post: 180, // seconds
  fields_completed: 12
});

analytics.track('job_post_edited', {
  contractor_id: 'user_123',
  job_id: 'job_456',
  fields_changed: ['budget', 'deadline'],
  edit_reason: 'budget_increase'
});

analytics.track('job_post_deleted', {
  contractor_id: 'user_123',
  job_id: 'job_456',
  delete_reason: 'filled_externally',
  hours_since_post: 24
});
```

### Job Application Events (Workers)
```javascript
// Application process
analytics.track('worker_applied', {
  worker_id: 'worker_789',
  job_id: 'job_456',
  application_method: 'quick_apply',
  cover_letter_included: true,
  resume_updated: false,
  time_to_apply: 30 // seconds
});

analytics.track('worker_matched', {
  worker_id: 'worker_789',
  job_id: 'job_456',
  match_score: 85,
  match_reasons: ['skills', 'location', 'availability'],
  algorithm_version: 'v3.2'
});

analytics.track('worker_hired', {
  worker_id: 'worker_789',
  job_id: 'job_456',
  contractor_id: 'user_123',
  time_to_hire: 48, // hours since job posted
  applications_received: 5
});
```

### Payment Events
```javascript
// Payment flow
analytics.track('payment_initiated', {
  payment_id: 'pay_abc',
  job_id: 'job_456',
  amount: 5000,
  currency: 'AUD',
  payment_method: 'credit_card',
  contractor_id: 'user_123'
});

analytics.track('payment_completed', {
  payment_id: 'pay_abc',
  job_id: 'job_456',
  amount: 5000,
  processing_fee: 150,
  time_to_process: 2 // seconds
});

analytics.track('payment_failed', {
  payment_id: 'pay_abc',
  job_id: 'job_456',
  failure_reason: 'insufficient_funds',
  retry_attempt: 1,
  payment_method: 'credit_card'
});
```

### User Interaction Events
```javascript
// Voice input
analytics.track('voice_input_used', {
  user_id: 'user_123',
  feature: 'job_description',
  input_duration: 45, // seconds
  transcription_accuracy: 0.92,
  corrections_made: 2
});

// Profile completion
analytics.track('profile_updated', {
  user_id: 'user_123',
  user_type: 'contractor',
  completion_percentage: 75,
  fields_updated: ['company_size', 'abn', 'insurance'],
  profile_strength: 'strong'
});

// General interactions
analytics.track('button_clicked', {
  user_id: 'user_123',
  button_text: 'Post New Job',
  page: 'dashboard',
  element_type: 'primary_cta'
});

analytics.track('form_submitted', {
  user_id: 'user_123',
  form_name: 'job_preferences',
  completion_time: 120, // seconds
  validation_errors: 0
});
```

### Page View Events
```javascript
// Basic page tracking
analytics.page('Job Details', {
  job_id: 'job_456',
  referrer: 'search_results',
  user_type: 'worker',
  search_query: 'electrician sydney'
});
```

## 4. A/B Testing Plan

### High Priority Tests (Month 1-3)

#### 1. Landing Page Variations
**Hypothesis**: Different value propositions will resonate with different user segments

**Test A**: Current headline - "Connect with skilled tradespeople instantly"
**Test B**: Alternative - "Get your project done faster with verified workers"
**Test C**: Alternative - "The fastest way to hire qualified contractors"

**Metrics to track**:
- Signup conversion rate
- Time on page
- Scroll depth
- Bounce rate

**Success criteria**: 20% improvement in conversion rate

#### 2. Signup Flow Length
**Hypothesis**: Shorter signup will increase conversions but may reduce quality

**Test A**: Current 5-step process (2-3 minutes)
**Test B**: Quick 2-step process (30 seconds) - email only, details later
**Test C**: Progressive profiling - start with email, add details over time

**Metrics to track**:
- Signup completion rate
- Profile completion rate (after 7 days)
- Time to first job post/application
- User quality score (based on activity)

**Success criteria**: 30% increase in completions without quality drop

### Medium Priority Tests (Month 3-6)

#### 3. Job Posting Flow
**Hypothesis**: Simplified posting will increase job creation frequency

**Test A**: Current detailed form (12 fields)
**Test B**: Quick post (3 taps) - category, budget, description
**Test C**: Voice-first posting - describe job, AI extracts details

**Metrics to track**:
- Job post completion rate
- Time to post
- Job quality score (based on applications received)
- Post-edit frequency

**Success criteria**: 25% increase in completed posts

#### 4. Matching Algorithm Tweaks
**Hypothesis**: Different weighting will improve match quality

**Test A**: Current algorithm (skills 40%, location 30%, availability 30%)
**Test B**: Quality-focused (ratings 50%, skills 30%, location 20%)
**Test C**: Speed-focused (availability 50%, location 30%, skills 20%)

**Metrics to track**:
- Match rate
- Hire rate from matches
- Time to hire
- User satisfaction with matches

**Success criteria**: 15% improvement in hire rate

### Testing Framework Setup
1. **Use PostHog's feature flags** for easy A/B test implementation
2. **Minimum sample size**: 1000 users per variant for statistical significance
3. **Test duration**: 2-4 weeks depending on metric being measured
4. **Document all tests** in shared repository with:
   - Hypothesis
   - Success criteria
   - Results
   - Learnings
   - Next steps

### Future Test Ideas
- Push notification timing and content
- Pricing display formats
- Review collection methods
- Onboarding tutorial variations
- Search result ordering algorithms
- Payment flow optimization

## Implementation Timeline

### Week 1-2: Foundation
- [ ] Set up Google Analytics 4
- [ ] Implement basic event tracking (page views, signups)
- [ ] Create initial dashboard in GA4

### Week 3-4: Enhanced Tracking
- [ ] Set up PostHog
- [ ] Implement job lifecycle events
- [ ] Configure user properties and cohorts

### Month 2: Optimization
- [ ] Launch first A/B tests (landing page, signup flow)
- [ ] Set up automated reports
- [ ] Train team on analytics tools

### Month 3: Advanced Analytics
- [ ] Implement predictive metrics (churn, LTV)
- [ ] Build custom dashboard for executives
- [ ] Set up automated alerts for key metrics

### Ongoing: Iteration
- [ ] Monthly metrics review
- [ ] Quarterly deep-dive analysis
- [ ] Continuous A/B testing pipeline
- [ ] Annual analytics tool evaluation