MCPInstall

data-and-funnel-analytics

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.

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Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/manojbajaj95/claude-gtm-plugin --skill data-and-funnel-analytics
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads data-and-funnel-analytics automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

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

CategoryEventKey Properties
Marketingpage_viewpage_title, page_location, referrer
cta_clickedbutton_text, location, page
form_submittedform_type, page
signup_completedmethod, plan
Productonboarding_step_completedstep_number, step_name
feature_usedfeature_name, context
trial_startedplan, source
purchase_completedplan, value, currency
E-commerceproduct_viewedproduct_id, category, price
product_added_to_cartproduct_id, price, quantity
checkout_startedcart_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

MetricGoodWarningPoorAction When Poor
Avg Time on Page>3 min1–3 min<1 minImprove 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>2.51.5–2.5<1.5Improve internal linking

Google Search Console Benchmarks

MetricGoodWarningPoorAction When Poor
CTR>5%2–5%<2%Improve title/meta description
Avg Position1–34–10>10Strengthen content, build links
ImpressionsGrowingStableDecliningRefresh 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

MetricSignificant ChangeAlert Level
Traffic±30% WoWHIGH
CTR±1pp WoWMEDIUM
Position±5 positionsHIGH
Bounce Rate±10pp WoWMEDIUM

Product Analytics

North Star Metric

The ONE metric that represents customer value:

CompanyNorth Star
SlackWeekly Active Users
AirbnbNights Booked
SpotifyTime Listening
ShopifyGMV

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

Key Metrics by Stage

StageMetrics
AcquisitionTraffic sources, CPC, visitor → signup rate
ActivationSignup → first core action, time to value, onboarding completion
RetentionDAU/MAU (stickiness), D1/D7/D30 retention, churn rate
RevenueMRR/ARR, ARPU, LTV, LTV:CAC ratio
ReferralViral coefficient, referral signups, NPS

Retention Benchmarks

TimeframeGoodBad
D160–80%<40%
D740–60%<10%
D3030–50%<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

FunnelSteps
E-commercePromotion → Search → Product View → Add to Cart → Purchase
SaaS SignupLanding Page → Sign Up → Email Verify → Onboarding Complete
ContentArticle 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

DimensionWeightWhat It Measures
Hook Strength2xStops the scroll, grabs attention
Story Connection1.5xCreates emotional connection and belief
Offer Clarity2xClear, compelling, irresistible
Value Ladder Fit1xFits the ascension path
Traffic Match1.5xMatched to traffic temperature
Conversion Path1xNext step obvious and frictionless

Rating Scale

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

Traffic Temperature

TemperatureThey KnowAppropriate Funnel
ColdNothing about youLead funnel, value-first content
WarmProblem + your solutionTripwire, webinar, challenge
HotReady to buySales 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:

CaseAssumptionsRevenueProfitROIAssessment
WorstPessimisticRisk level
RealisticExpectedTarget
BestOptimisticUpside

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

CategoryTools
Event TrackingMixpanel, Amplitude, PostHog (open-source)
Session RecordingFullStory, LogRocket, Hotjar
A/B TestingOptimizely, VWO
Web AnalyticsGA4, Google Search Console
Tag ManagementGoogle 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

FAQ

What does the data-and-funnel-analytics skill do?

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.

How do I install data-and-funnel-analytics?

Run npx skills add https://github.com/manojbajaj95/claude-gtm-plugin --skill data-and-funnel-analytics in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/data-and-funnel-analytics/ (personal) or .claude/skills/data-and-funnel-analytics/ (project).

Which AI agents can use data-and-funnel-analytics?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is data-and-funnel-analytics safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains data-and-funnel-analytics?

It is published by manojbajaj95 in manojbajaj95/claude-gtm-plugin. It has 421 recorded installs.

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