---
name: data-and-funnel-analytics
description: Analytics tracking, interpretation, funnel analysis, product metrics, and ROI measurement. Use when setting up GA4/GTM tracking, interpreting analytics data, analyzing conversion funnels, calculating ROI, or measuring product engagement. Triggers on "analytics," "GA4," "Google Analytics," "conversion tracking," "event tracking," "UTM parameters," "tag manager," "GTM," "tracking plan," "funnel analysis," "conversion rates," "user flow," "cohort analysis," "retention," "product metrics," "North Star metric," "ROI," "break-even," "payback period," "investment analysis," "validate my funnel," "why isn't my funnel converting," or "executive financial report." For A/B test setup, see ab-test-setup.
---

# Data & Funnel Analytics

End-to-end analytics: set up tracking, interpret data, analyze funnels, measure product engagement, validate conversion paths, and calculate ROI.

**Principle:** Track for decisions, not data — every event should inform an action.

---

## Analytics Tracking

### Event Naming Convention

Format: `object_action` in lowercase snake_case.

```
signup_completed | cta_hero_clicked | checkout_started | onboarding_step_completed
```

Rules: Specific over vague (`cta_hero_clicked` not `button_clicked`), past tense for completed actions, context in properties not event name.

### Tracking Plan

| Category | Event | Key Properties |
|----------|-------|---------------|
| **Marketing** | `page_view` | page_title, page_location, referrer |
| | `cta_clicked` | button_text, location, page |
| | `form_submitted` | form_type, page |
| | `signup_completed` | method, plan |
| **Product** | `onboarding_step_completed` | step_number, step_name |
| | `feature_used` | feature_name, context |
| | `trial_started` | plan, source |
| | `purchase_completed` | plan, value, currency |
| **E-commerce** | `product_viewed` | product_id, category, price |
| | `product_added_to_cart` | product_id, price, quantity |
| | `checkout_started` | cart_value, items_count |

### Standard Properties

- **User context:** user_id, user_type (free/paid/admin), plan_type
- **Attribution:** source, medium, campaign, content, term (UTM params)
- **Page:** page_title, page_location, content_group
- **PII hygiene:** Never send email, name, or phone as event properties. Use hashed user IDs only.

### GA4 Implementation

```javascript
// gtag.js custom event
gtag('event', 'signup_completed', {
  'method': 'email',
  'plan': 'free',
  'user_id': userId
});

// GTM dataLayer
dataLayer.push({
  'event': 'signup_completed',
  'method': 'email',
  'plan': 'free'
});
```

**Enhanced Measurement** (enable in GA4): page_view, scroll, outbound_click, site_search, video_engagement, file_download.

**Conversions:** Admin → Events → Toggle "Mark as conversion." Counting: once per session (form submit) or every time (purchase).

### UTM Parameters

Convention: `utm_source={channel}&utm_medium={cpc|email|organic|social}&utm_campaign={id}&utm_content={variant}&utm_term={keyword}`

- Apply to ALL paid and email links
- Never use on internal links (breaks session attribution)
- Lowercase, hyphens not spaces
- Document in a UTM tracking sheet

### Privacy & Compliance

- GDPR/CCPA: Implement consent management, block GA4 until consent granted
- GA4 data retention: 14 months max (Admin → Data Settings)
- IP anonymization enabled

---

## Analytics Interpretation

### GA4 Benchmarks

| Metric | Good | Warning | Poor | Action When Poor |
|--------|------|---------|------|------------------|
| Avg Time on Page | >3 min | 1–3 min | <1 min | Improve content depth |
| Bounce Rate | <40% | 40–70% | >70% | Add internal links, improve intro |
| Engagement Rate | >60% | 30–60% | <30% | Review content quality |
| Scroll Depth | >75% | 50–75% | <50% | Add visual breaks |
| Pages/Session | >2.5 | 1.5–2.5 | <1.5 | Improve internal linking |

### Google Search Console Benchmarks

| Metric | Good | Warning | Poor | Action When Poor |
|--------|------|---------|------|------------------|
| CTR | >5% | 2–5% | <2% | Improve title/meta description |
| Avg Position | 1–3 | 4–10 | >10 | Strengthen content, build links |
| Impressions | Growing | Stable | Declining | Refresh content |

### Traffic Quality Matrix

```
                    High Engagement
                          │
           ┌──────────────┼──────────────┐
           │  HIDDEN GEM  │   STAR       │
           │  Low traffic  │   High traffic│
           │  → Promote   │   → Maintain  │
Low ───────┼──────────────┼──────────────┼─── High
Traffic    │  UNDERPERFORM│   LEAKY      │   Traffic
           │  Low traffic  │   High traffic│
           │  → Rework    │   → Optimize  │
           └──────────────┼──────────────┘
                          │
                    Low Engagement
```

### Anomaly Detection

| Metric | Significant Change | Alert Level |
|--------|-------------------|-------------|
| Traffic | ±30% WoW | HIGH |
| CTR | ±1pp WoW | MEDIUM |
| Position | ±5 positions | HIGH |
| Bounce Rate | ±10pp WoW | MEDIUM |

---

## Product Analytics

### North Star Metric

The ONE metric that represents customer value:

| Company | North Star |
|---------|-----------|
| Slack | Weekly Active Users |
| Airbnb | Nights Booked |
| Spotify | Time Listening |
| Shopify | GMV |

Criteria: Represents customer value, correlates with revenue, measurable frequently, rallies the team.

### Key Metrics by Stage

| Stage | Metrics |
|-------|---------|
| **Acquisition** | Traffic sources, CPC, visitor → signup rate |
| **Activation** | Signup → first core action, time to value, onboarding completion |
| **Retention** | DAU/MAU (stickiness), D1/D7/D30 retention, churn rate |
| **Revenue** | MRR/ARR, ARPU, LTV, LTV:CAC ratio |
| **Referral** | Viral coefficient, referral signups, NPS |

### Retention Benchmarks

| Timeframe | Good | Bad |
|-----------|------|-----|
| D1 | 60–80% | <40% |
| D7 | 40–60% | <10% |
| D30 | 30–50% | <2% |

Good = flattening curve. Bad = steep drop-off.

### Dashboard Design

- **Executive:** North Star Metric (big number), revenue (MRR/ARR), key trends
- **Product:** Active users, feature usage, retention cohorts, funnels
- **Marketing:** Traffic sources, conversion rates, CPA, ROI by channel

---

## Funnel Analysis

### Core Workflow

1. Load and merge user journey data
2. Define funnel steps and calculate step-by-step conversion rates
3. Segment by user attributes (device, cohort, plan)
4. Visualize bottlenecks
5. Generate optimization recommendations

### Common Funnel Types

| Funnel | Steps |
|--------|-------|
| **E-commerce** | Promotion → Search → Product View → Add to Cart → Purchase |
| **SaaS Signup** | Landing Page → Sign Up → Email Verify → Onboarding Complete |
| **Content** | Article View → Comment → Share → Subscribe |

### Analysis Patterns

- **Bottleneck identification** — Steps with highest drop-off rates
- **Segment comparison** — Conversion across user groups
- **Temporal analysis** — Conversion over time
- **A/B testing** — Compare funnel variations

See `examples/` for Python implementations with Plotly visualizations.

---

## Funnel Validation (DotCom Secrets)

Score existing funnels against Russell Brunson's framework: **Hook → Story → Offer**.

### Scoring Dimensions

| Dimension | Weight | What It Measures |
|-----------|--------|------------------|
| Hook Strength | 2x | Stops the scroll, grabs attention |
| Story Connection | 1.5x | Creates emotional connection and belief |
| Offer Clarity | 2x | Clear, compelling, irresistible |
| Value Ladder Fit | 1x | Fits the ascension path |
| Traffic Match | 1.5x | Matched to traffic temperature |
| Conversion Path | 1x | Next step obvious and frictionless |

### Rating Scale

| Score | Verdict |
|-------|---------|
| 85–100 | Conversion Machine — Ready to scale |
| 70–84 | Strong Funnel — Fix weak points, then scale |
| 55–69 | Leaky Funnel — Fix before scaling traffic |
| 40–54 | Broken Funnel — Rebuild key components |
| 0–39 | Non-Functional — Start over |

### Traffic Temperature

| Temperature | They Know | Appropriate Funnel |
|-------------|-----------|-------------------|
| Cold | Nothing about you | Lead funnel, value-first content |
| Warm | Problem + your solution | Tripwire, webinar, challenge |
| Hot | Ready to buy | Sales page, order form, call booking |

For complete scoring criteria and examples, see [references/full-guide.md](references/full-guide.md).

---

## ROI Analysis

### Core Metrics

**ROI:** `(Net Profit / Total Investment) × 100%`
- ✅ INVEST: ROI > 100% (realistic case)
- ⚠️ REVIEW: ROI 50–100%
- ❌ REJECT: ROI < 50%

**Break-Even:** `Investment / Monthly Net Profit`
- ✅ INVEST: Break-even < 50% of realistic target
- ❌ REJECT: Break-even > 70%

**Payback Period:** `Investment / Monthly Net Profit`
- ✅ INVEST: < 12 months
- ⚠️ REVIEW: 12–24 months
- ❌ REJECT: > 24 months

### 3-Scenario Analysis

Always model Best / Realistic / Worst:

| Case | Assumptions | Revenue | Profit | ROI | Assessment |
|------|------------|---------|--------|-----|------------|
| **Worst** | Pessimistic | | | | Risk level |
| **Realistic** | Expected | | | | Target |
| **Best** | Optimistic | | | | Upside |

**Decision rule:** If worst-case ROI ≥ 0%, investment is low-risk.

### Executive Summary Template

```
[Investment] achieves [ROI%] ROI at [conversion/growth rate].
Break-even occurs at [threshold], with payback in [months].
Investment is [recommended/not recommended] because [reason].
```

For detailed formulas (NPV, LTV, CAC, sensitivity analysis), see [references/roi-reference.md](references/roi-reference.md).

---

## Validation & QA

### Before Launch
- [ ] Events fire in GA4 DebugView
- [ ] Properties have expected values
- [ ] No duplicate events
- [ ] Conversions marked correctly
- [ ] UTM parameters captured on landing

### Ongoing
- **Weekly:** Check for sudden drops in key events (>20% change = investigate)
- **Monthly:** Audit for new pages/features without tracking
- **Quarterly:** Full tracking plan review — remove stale events, add missing ones

---

## Tools

| Category | Tools |
|----------|-------|
| **Event Tracking** | Mixpanel, Amplitude, PostHog (open-source) |
| **Session Recording** | FullStory, LogRocket, Hotjar |
| **A/B Testing** | Optimizely, VWO |
| **Web Analytics** | GA4, Google Search Console |
| **Tag Management** | Google Tag Manager |

---

## Related Skills

- **ab-test-setup** — A/B test measurement and setup
- **seo-and-aeo-strategy** — Measuring SEO/AEO performance
- **conversion-rate-optimization** — Optimizing conversion after funnel analysis
- **executive-dashboard-generator** — Building dashboards from analytics data