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 β 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('event', 'signup_completed', {
'method': 'email',
'plan': 'free',
'user_id': userId
});
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 β Events β 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 β Data Settings)
- IP anonymization enabled
Analytics Interpretation
GA4 Benchmarks
| Metric |
Good |
Warning |
Poor |
Action When Poor |
| Avg Time on Page |
>3 min |
1β3 min |
<1 min |
Improve content depth |
| Bounce Rate |
<40% |
40β70% |
>70% |
Add internal links, improve intro |
| Engagement Rate |
>60% |
30β60% |
<30% |
Review content quality |
| Scroll Depth |
>75% |
50β75% |
<50% |
Add visual breaks |
| Pages/Session |
>2.5 |
1.5β2.5 |
<1.5 |
Improve internal linking |
Google Search Console Benchmarks
| Metric |
Good |
Warning |
Poor |
Action When Poor |
| CTR |
>5% |
2β5% |
<2% |
Improve title/meta description |
| Avg Position |
1β3 |
4β10 |
>10 |
Strengthen content, build links |
| Impressions |
Growing |
Stable |
Declining |
Refresh content |
Traffic Quality Matrix
High Engagement
β
ββββββββββββββββΌβββββββββββββββ
β HIDDEN GEM β STAR β
β Low traffic β High trafficβ
β β Promote β β Maintain β
Low ββββββββΌβββββββββββββββΌβββββββββββββββΌβββ High
Traffic β UNDERPERFORMβ LEAKY β Traffic
β Low traffic β High trafficβ
β β Rework β β Optimize β
ββββββββββββββββΌβββββββββββββββ
β
Low Engagement
Anomaly Detection
| Metric |
Significant Change |
Alert Level |
| Traffic |
Β±30% WoW |
HIGH |
| CTR |
Β±1pp WoW |
MEDIUM |
| Position |
Β±5 positions |
HIGH |
| Bounce Rate |
Β±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 β signup rate |
| Activation |
Signup β 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 |
60β80% |
<40% |
| D7 |
40β60% |
<10% |
| D30 |
30β50% |
<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 β Search β Product View β Add to Cart β Purchase |
| SaaS Signup |
Landing Page β Sign Up β Email Verify β Onboarding Complete |
| Content |
Article View β Comment β Share β Subscribe |
Analysis Patterns
- Bottleneck identification β Steps with highest drop-off rates
- Segment comparison β Conversion across user groups
- Temporal analysis β Conversion over time
- A/B testing β Compare funnel variations
See examples/ for Python implementations with Plotly visualizations.
Funnel Validation (DotCom Secrets)
Score existing funnels against Russell Brunson's framework: Hook β Story β 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 |
| 85β100 |
Conversion Machine β Ready to scale |
| 70β84 |
Strong Funnel β Fix weak points, then scale |
| 55β69 |
Leaky Funnel β Fix before scaling traffic |
| 40β54 |
Broken Funnel β Rebuild key components |
| 0β39 |
Non-Functional β 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) Γ 100%
- β
INVEST: ROI > 100% (realistic case)
- β οΈ REVIEW: ROI 50β100%
- β REJECT: ROI < 50%
Break-Even: Investment / Monthly Net Profit
- β
INVEST: Break-even < 50% of realistic target
- β REJECT: Break-even > 70%
Payback Period: Investment / Monthly Net Profit
- β
INVEST: < 12 months
- β οΈ REVIEW: 12β24 months
- β 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 β₯ 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
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 β 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 β A/B test measurement and setup
- seo-and-aeo-strategy β Measuring SEO/AEO performance
- conversion-rate-optimization β Optimizing conversion after funnel analysis
- executive-dashboard-generator β Building dashboards from analytics data