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

// 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

Load and merge user journey data
Define funnel steps and calculate step-by-step conversion rates
Segment by user attributes (device, cohort, plan)
Visualize bottlenecks
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.

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.

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