Data And Funnel Analytics

Data & Funnel Analytics

Workspace Context

Read bootstrap context before asking questions: strategy/brand.md for brand, audience, offer, channels, tools, constraints, and metrics; about/me.md for personal voice; content/ideas.md and content/calendar.md for content planning. Use legacy product-marketing context files only as fallback. Save generated drafts to content/<platform>/drafts/YYYY-MM-DD_short-topic-slug.md, and route durable learnings back to strategy/brand.md, about/me.md, or content/ideas.md.

Operating Contract

This skill is self-contained for its frontmatter scope: use its local instructions, references, scripts, and assets as the playbook; ask only for missing task-specific inputs; hand off to adjacent skills instead of expanding scope; and return an actionable artifact, decision, plan, draft, or diagnostic.

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

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

Google Search Console Benchmarks

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

Product Analytics

North Star Metric

The ONE metric that represents customer value:

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

Key Metrics by Stage

Retention Benchmarks

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

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

Rating Scale