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