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Analytics

CommunityPopular
coreyhaines31
analytics

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.

Overview

Publishercoreyhaines31
Repositorymarketingskills
Skill nameanalytics
Stars
50.7K
Forks
7.7K
Bundled files
4
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 4 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by coreyhaines31 on GitHub. Read the source before you install it.

Installation

Install the Analytics AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/coreyhaines31/marketingskills.git /tmp/marketingskills
mkdir -p .claude/skills
cp -r /tmp/marketingskills/skills/analytics .claude/skills/analytics
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Analytics in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Analytics on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Analytics is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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

Tracking Plan Framework

Structure

Event Name | Category | Properties | Trigger | Notes
---------- | -------- | ---------- | ------- | -----

Event Types

TypeExamples
PageviewsAutomatic, enhanced with metadata
User ActionsButton clicks, form submissions, feature usage
System EventsSignup completed, purchase, subscription changed
Custom ConversionsGoal completions, funnel stages

For comprehensive event lists: See 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

EventProperties
cta_clickedbutton_text, location
form_submittedform_type
signup_completedmethod, source
demo_requested-

Product/App

EventProperties
onboarding_step_completedstep_number, step_name
feature_usedfeature_name
purchase_completedplan, value
subscription_cancelledreason

For full event library by business type: See references/event-library.md


Event Properties

Standard Properties

CategoryProperties
Pagepage_title, page_location, page_referrer
Useruser_id, user_type, account_id, plan_type
Campaignsource, medium, campaign, content, term
Productproduct_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


Google Tag Manager

Container Structure

ComponentPurpose
TagsCode that executes (GA4, pixels)
TriggersWhen tags fire (page view, click)
VariablesDynamic 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


UTM Parameter Strategy

Standard Parameters

ParameterPurposeExample
utm_sourceTraffic sourcegoogle, newsletter
utm_mediumMarketing mediumcpc, email, social
utm_campaignCampaign namespring_sale
utm_contentDifferentiate versionshero_cta
utm_termPaid search keywordsrunning+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

ToolUse For
GA4 DebugViewReal-time event monitoring
GTM Preview ModeTest triggers before publish
Browser ExtensionsTag 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

IssueCheck
Events not firingTrigger config, GTM loaded
Wrong valuesVariable path, data layer structure
Duplicate eventsMultiple 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. Key analytics tools:

ToolBest ForMCPGuide
GA4Web analytics, Google ecosystemga4.md
MixpanelProduct analytics, event tracking-mixpanel.md
AmplitudeProduct analytics, cohort analysis-amplitude.md
PostHogOpen-source analytics, session replay-posthog.md
SegmentCustomer data platform, routing-segment.md

Related Skills

  • ab-testing: For experiment tracking
  • attribution: For attribution models, multi-touch/MMM/incrementality, and reconciling conflicting numbers across tools (once tracking is live)
  • seo-audit: For organic traffic analysis
  • cro: For conversion optimization (uses this data)
  • revops: For pipeline metrics, CRM tracking, and revenue attribution

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Analytics AI skill do?

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 r...

Why use Analytics on TypingMind?

Because you install it once and use it with any model. Analytics is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Analytics in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/coreyhaines31/marketingskills/tree/main/skills/analytics. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Analytics?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Analytics?

As many as you like. As long as a model supports skills, you can use Analytics with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Analytics AI skill free?

Yes. It is published on GitHub by coreyhaines31 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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