AnalyticsSAFE

Marketing skills for Claude Code and AI agents. CRO, copywriting, SEO, analytics, and growth engineering.

The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.

---
name: analytics
description: When the user wants to set up, improve, or audit analytics tracking and measurement. Also use when the user mentions "set up tracking," "GA4," "Google Analytics," "event tracking," "UTM parameters," "tag manager," "GTM," "analytics implementation," "tracking plan," "how do I measure this," "Mixpanel," "Segment," "are my events firing," or "analytics isn't working." Use this whenever someone asks how to know if something is working or wants to measure marketing results. For getting conversions into ad platforms (pixels, conversion tags, CAPI, server-side) and verifying they arrived, see conversion-tracking. For choosing attribution models, comparing multi-touch/MMM/incrementality, or reconciling conflicting numbers across tools, see attribution. For A/B test measurement, see ab-testing. Rate metrics divide matching closed windows — never full-period spend by partial-period results.
metadata:
  version: 2.2.1
---

# 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.

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
- Keep provider-defined names when using automatic or recommended events (e.g. GA4 `click`, `view_search_results`, `purchase`). Map internal business names explicitly; naming a custom event does not make the provider collect it automatically.

---

## 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 duplic

SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.

What the source does

Filesystem

none-observed

Network

none-observed

Shell

none-observed

Dependencies

pinned

Secrets in source

none-found

Findings (1)

CLAUDE.md

Gates applied: no_behavioural_pass.

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