Analyze the supplied order journeys for a marketing lead. Meta, Paid Search, and Email each had $600 of spend. Deduplicate exact duplicate order_id rows before calculating, retain negative net revenue from refunds, and do not assign a Direct-only order to a marketing channel. Define first-touch as the first non-Direct touch and last-touch as the last non-Direct touch. Deliver: (1) a reconciliation under each model showing unique-order net revenue, the paid-channel subtotal, Organic attributed revenue, and unattributed Direct-only revenue; (2) a table for Meta, Paid Search, and Email with attributed net revenue and ROAS under both first-touch and last-touch; (3) the winning paid channel under each model; (4) a budget recommendation that distinguishes conclusions robust to the attribution choice from conclusions that depend on it; and (5) explicit assumptions plus the one data limitation that would most change the decision and how resolving it could change the recommendation. Show the arithmetic needed to audit the result, and do not treat attribution as proof of causation.
---
## Supplied source: order-journeys.csv
order_id,net_revenue_usd,touch_1,touch_2,touch_3
O-001,120,Meta,Email,Direct
O-002,80,Meta,Paid Search,
O-003,150,Paid Search,Email,
O-004,100,Organic,Meta,
O-005,200,Meta,Email,
O-006,90,Paid Search,Direct,
O-007,130,Email,Paid Search,
O-008,110,Organic,Email,
O-009,170,Meta,Paid Search,Email
O-009,170,Meta,Paid Search,Email
O-010,140,Paid Search,Meta,
O-011,160,Email,Meta,
O-012,100,Direct,,
O-013,-120,Meta,Email,
---
## Skill guidance you should follow
---
name: analytics
description: "Set up or audit tracking — GA4, GTM, Mixpanel, Segment; tracking plans, event naming, UTM conventions, conversion and attribution debugging. Rate metrics divide matching closed windows — never full-period spend by partial-period results."
metadata:
version: 2.2.0
---
# Analytics Tracking
You are an expert in analytics implementation and measurement. Your goal is to help set up tracking that provides actionable insights for marketing and product decisions.
## Initial Assessment
**Check for product marketing context first:**
If `.agents/product-marketing.md` exists (or `.claude/product-marketing.md`, or the legacy `product-marketing-context.md` filename, in older setups), read it before asking questions. Use that context and only ask for information not already covered or specific to this task.
**Apply the project's brand:**
If `BRAND.md` exists, read it before asking questions and apply it to everything you produce — its voice, messaging, and audience for anything written, and its colors, typography, and logo for anything visual. Never ask for a brand fact it already answers. If it lacks something you need, name the missing fact instead of inventing one or quietly falling back to a generic default.
Before implementing tracking, understand:
1. **Business Context** - What decisions will this data inform? What are key conversions?
2. **Current State** - What tracking exists? What tools are in use?
3. **Technical Context** - What's the tech stack? Any privacy/compliance requirements?
---
## Core Principles
### 1. Track for Decisions, Not Data
- Every event should inform a decision
- Avoid vanity metrics
- Quality > quantity of events
### 2. Start with the Questions
- What do you need to know?
- What actions will you take based on this data?
- Work backwards to what you need to track
### 3. Name Things Consistently
- Naming conventions matter
- Establish patterns before implementing
- Document everything
### 4. Maintain Data Quality
- Validate implementation
- Monitor for issues
- Clean data > more data
### 5. Compute, Don't Eyeball
- Derive every total, rate, and delta from row-level data with a script or
spreadsheet — never by scanning rows and summing mentally. One silently
dropped row corrupts every figure downstream of it.
- Cross-check each headline figure a second, independent way (a
reconciliation total, a recomputation from a different grouping) before
reporting it, and chase any mismatch to the exact row.
- When a claim is about one segment — a single campaign, ad set, channel, or
week — report that segment's own numbers. Never fold it into a neighboring
group and let the group's total speak for it.
### 6. Match Observation Windows
- A rate or efficiency metric divides a numerator and denominator that cover
the same closed observation window. Never divide a full period's spend by a
partial period's conversions or revenue — restate both over the weeks that
actually have data, and say which weeks those are.
- Cohort rates use only cohorts whose observation window has ended. A trial
or signup still inside its window is pending, not failed — exclude it from
the denominator and label it as pending rather than counting it against
the rate.
### 7. Recommend Against the Stated Goal
- Analysis ends in a recommendation, and the recommendation must be argued
from the goal the brief states — the launch target, audience, revenue, or
positioning objective — not only from what is operationally easiest.
Name which stated goal each option serves and what it trades away.
---
## Tracking Plan Framework
### Structure
```
Event Name | Category | Properties | Trigger | Notes
---------- | -------- | ---------- | ------- | -----
```
### Event Types
| Type | Examples |
|------|----------|
| Pageviews | Automatic, enhanced with metadata |
| User Actions | Button clicks, form submissions, feature usage |
| System Events | Signup completed, purchase, subscription changed |
| Custom Conversions | Goal completions, funnel stages |
**For comprehensive event lists**: See [references/event-library.md](references/event-library.md)
---
## Event Naming Conventions
### Recommended Format: Object-Action
```
signup_completed
button_clicked
form_submitted
article_read
checkout_payment_completed
```
### Best Practices
- Lowercase with underscores
- Be specific: `cta_hero_clicked` vs. `button_clicked`
- Include context in properties, not event name
- Avoid spaces and special characters
- Document decisions
---
## Essential Events
### Marketing Site
| Event | Properties |
|-------|------------|
| cta_clicked | button_text, location |
| form_submitted | form_type |
| signup_completed | method, source |
| demo_requested | - |
### Product/App
| Event | Properties |
|-------|------------|
| onboarding_step_completed | step_number, step_name |
| feature_used | feature_name |
| purchase_completed | plan, value |
| subscription_cancelled | reason |
**For full event library by business type**: See [references/event-library.md](references/event-library.md)
---
## Event Properties
### Standard Properties
| Category | Properties |
|----------|------------|
| Page | page_title, page_location, page_referrer |
| User | user_id, user_type, account_id, plan_type |
| Campaign | source, medium, campaign, content, term |
| Product | product_id, product_name, category, price |
### Best Practices
- Use consistent property names
- Include relevant context
- Don't duplicate automatic properties
- Avoid PII in properties
---
## GA4 Implementation
### Quick Setup
1. Create GA4 property and data stream
2. Install gtag.js or GTM
3. Enable enhanced measurement
4. Configure custom events
5. Mark conversions in Admin
### Custom Event Example
```javascript
gtag('event', 'signup_completed', {
'method': 'email',
'plan': 'free'
});
```
**For detailed GA4 implementation**: See [references/ga4-implementation.md](references/ga4-implementation.md)
---
## Google Tag Manager
### Container Structure
| Component | Purpose |
|-----------|---------|
| Tags | Code that executes (GA4, pixels) |
| Triggers | When tags fire (page view, click) |
| Variables | Dynamic values (click text, data layer) |
### Data Layer Pattern
```javascript
dataLayer.push({
'event': 'form_submitted',
'form_name': 'contact',
'form_location': 'footer'
});
```
**For detailed GTM implementation**: See [references/gtm-implementation.md](references/gtm-implementation.md)
---
## UTM Parameter Strategy
### Standard Parameters
| Parameter | Purpose | Example |
|-----------|---------|---------|
| utm_source | Traffic source | google, newsletter |
| utm_medium | Marketing medium | cpc, email, social |
| utm_campaign | Campaign name | spring_sale |
| utm_content | Differentiate versions | hero_cta |
| utm_term | Paid search keywords | running+shoes |
### Naming Conventions
- Lowercase everything
- Use underscores or hyphens consistently
- Be specific but concise: `blog_footer_cta`, not `cta1`
- Document all UTMs in a spreadsheet
---
## Debugging and Validation
### Testing Tools
| Tool | Use For |
|------|---------|
| GA4 DebugView | Real-time event monitoring |
| GTM Preview Mode | Test triggers before publish |
| Browser Extensions | Tag Assistant, dataLayer Inspector |
### Validation Checklist
- [ ] Events firing on correct triggers
- [ ] Property values populating correctly
- [ ] No duplicate events
- [ ] Works across browsers and mobile
- [ ] Conversions recorded correctly
- [ ] No PII leaking
### Common Issues
| Issue | Check |
|-------|-------|
| Events not firing | Trigger config, GTM loaded |
| Wrong values | Variable path, data layer structure |
| Duplicate events | Multiple containers, trigger firing twice |
---
## Privacy and Compliance
### Considerations
- Cookie consent required in EU/UK/CA
- No PII in analytics properties
- Data retention settings
- User deletion capabilities
### Implementation
- Use consent mode (wait for consent)
- IP anonymization
- Only collect what you need
- Integrate with consent management platform
---
## Output Format
### Tracking Plan Document
```markdown
# [Site/Product] Tracking Plan
## Overview
- Tools: GA4, GTM
- Last updated: [Date]
## Events
| Event Name | Description | Properties | Trigger |
|------------|-------------|------------|---------|
| signup_completed | User completes signup | method, plan | Success page |
## Custom Dimensions
| Name | Scope | Parameter |
|------|-------|-----------|
| user_type | User | user_type |
## Conversions
| Conversion | Event | Counting |
|------------|-------|----------|
| Signup | signup_completed | Once per session |
```
---
## Task-Specific Questions
1. What tools are you using (GA4, Mixpanel, etc.)?
2. What key actions do you want to track?
3. What decisions will this data inform?
4. Who implements - dev team or marketing?
5. Are there privacy/consent requirements?
6. What's already tracked?
---
## Tool Integrations
For implementation, see the [tools registry](../../tools/REGISTRY.md). Key analytics tools:
| Tool | Best For | MCP | Guide |
|------|----------|:---:|-------|
| **GA4** | Web analytics, Google ecosystem | ✓ | [ga4.md](../../tools/integrations/ga4.md) |
| **Mixpanel** | Product analytics, event tracking | - | [mixpanel.md](../../tools/integrations/mixpanel.md) |
| **Amplitude** | Product analytics, cohort analysis | - | [amplitude.md](../../tools/integrations/amplitude.md) |
| **PostHog** | Open-source analytics, session replay | - | [posthog.md](../../tools/integrations/posthog.md) |
| **Segment** | Customer data platform, routing | - | [segment.md](../../tools/integrations/segment.md) |
---
## Related Skills
- **ab-testing**: For experiment tracking
- **seo-audit**: For organic traffic analysis
- **cro**: For conversion optimization (uses this data)
- **revops**: For pipeline metrics, CRM tracking, and revenue attribution