Analytics
When the user wants to set up, improve, or audit analytics tracking and measurement.
Install
npx skills add coreyhaines31/marketingskills --skill analytics -g -a claude-code -y- Repository
- coreyhaines31/marketingskills57.8k
- Category
- Testing
- Updated
- 5d ago
- License
- MIT
- Context cost
- Mediumabout 3,000 tokens
- Runs scripts
- No, instructions only
What it does
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.
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:
- Business Context - What decisions will this data inform? What are key conversions?
- Current State - What tracking exists? What tools are in use?
- 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.
