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," "conversion tracking," "event trackin
Install
The skill file stays in the publisher's repository.
Paste the copied command in a terminal. It installs this SKILL.md into that agent.
npx skills add coreyhaines31/marketingskills --skill analytics -a cursor -y
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," "conversion tracking," "event tracking," "UTM parameters," "tag manager," "GTM," "analytics implementation," "tracking plan," "how do I measure this," "track conversions," "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 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.
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," "conversion tracking," "event tracking," "UTM parameters," "tag manager," "GTM," "analytics implementation," "tracking plan," "how do I measure this," "track conversions," "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 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: 2.2.0
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 exists (or , or the legacy 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.
.agents/product-marketing.md
.claude/product-marketing.md
product-marketing-context.md
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.
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.
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.
Lowercase everything. GA4 treats LinkedIn and linkedin as two sources, and the split never merges back.
Hyphens between words. No spaces, underscores, or +. Pick one separator for the whole company; this skill uses hyphens.
One spelling per source.linkedin, never also li or linkedin.com. Keep the allowed values in a shared sheet and build links from it.
No personal data. Never put emails, names, phone numbers, or user IDs in a UTM. They land in analytics reports and in referrer logs, and Google's terms prohibit sending PII to GA4.
Specific but short:blog-footer-cta, not cta1.
Test the final URL. Shorteners and redirects can drop or double parameters. Click the live link and check the landing URL before the campaign ships.
UTM Patterns by Partner Type
Partner links break most often because each deal gets named on the spot. Fix the pattern per partner type once: utm_medium names the kind of deal, utm_source names who sent the traffic.
Partner type
utm_source
utm_medium
utm_campaign
utm_content
Newsletter
{partner} (one per partner, across all their publications)
newsletter
{partner}-{publication}-{yyyy}-{mm}
{placement}-{yyyy-mm-dd}
Creator (YouTube, LinkedIn, TikTok)
{platform}
creator
{creator}
{post-date} or the video ID
Podcast
{podcast}
podcast
{podcast}-{yyyy}-{mm}
{spot}-{yyyy-mm-dd} (pre-roll, mid-roll)
Affiliate
{partner}
affiliate
{partner}-affiliate
placement, if they have several
Community
{community}
community
{community}-{program}
the channel or post, if known
Use creator as the medium for paid creator deals, not social (which mixes them with your organic posts) or video (which mixes them with paid video ads). The platform goes in utm_source.
One link per placement. A newsletter that runs you on two dates gets two links, so each date's clicks stay separate. The monthly utm_campaign rolls them up.
Add a custom channel group in GA4. GA4's default grouping sends mediums like newsletter, creator, podcast, and community to Unassigned (only affiliate and email map to a default channel). Create a channel group with a rule per medium so partner traffic shows up as its own channels.
Podcast and video links often aren't clickable, so pair the UTM link with a promo code or vanity URL. See influencer-marketing for the rest of partner measurement.
The partner-type pattern is adapted from Wispr Flow's link-creator skill (MIT), published in the skills.marketing library.
Traffic From AI Assistants
You can't tag links that ChatGPT, Claude, Perplexity, Gemini, or Copilot put in their answers. Some of those visits arrive with a referrer (chatgpt.com, perplexity.ai) or an assistant-added utm_source; many arrive as direct, or come later through a branded search.
Add a GA4 channel group rule that matches known assistant referrers and sources into an "AI assistants" channel, and update the list as new assistants appear.
Treat that channel as the floor. Assistant-driven visits that show up as direct or branded search can be most of the effect, and they won't carry the referrer.
For measuring the full effect (exposure, delayed visits, and longer attribution windows), see ai-seo. For reconciling it with other sources, see attribution.
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
# [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
What tools are you using (GA4, Mixpanel, etc.)?
What key actions do you want to track?
What decisions will this data inform?
Who implements - dev team or marketing?
Are there privacy/consent requirements?
What's already tracked?
Tool Integrations
For implementation, see the tools registry. Key analytics tools: