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Analytics Tracking

Community
kostja94
analytics-tracking

When the user wants to set up, audit, or optimize analytics tracking (GA4, events, conversions). Also use when the user mentions "Google Analytics," "GA4," "event tracking," "conversions," "attribution model," "gtag," "data layer," "GA4 setup," "conversion tracking," "event setup," "User ID tracking," or "CTA attribution." For traffic insights, use traffic-analysis.

Overview

Publisherkostja94
Repositorymarketing-skills
Skill nameanalytics-tracking
Stars
979
Forks
137
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by kostja94 on GitHub. Read the source before you install it.

Installation

Install the Analytics Tracking 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/kostja94/marketing-skills.git /tmp/marketing-skills
mkdir -p .claude/skills
cp -r /tmp/marketing-skills/skills/analytics/tracking .claude/skills/analytics-tracking
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Analytics Tracking 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 Tracking 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 Tracking 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

Guides analytics implementation: GA4 setup, event tracking, conversions, and data quality. Applies to web and app tracking across marketing channels.

When invoking: On first use, if helpful, open with 1-2 sentences on what this skill covers and why it matters, then provide the main output. On subsequent use or when the user asks to skip, go directly to the main output.

User ID

  • Purpose: Cross-device, cross-session user identification
  • Implementation: Set user_id when user is identified (e.g., login); send to GA4
  • Benefit: Accurate attribution across sessions; better audience building

CTA Attribution (Article ROI)

Track CTA clicks on key articles to measure content ROI:

ActionPurpose
Event per CTAe.g., cta_click with content_url, content_type
ConversionMark as conversion in GA4 for attribution
UseCompare high vs low performers; optimize CTA placement and copy

See seo-monitoring for article database and benchmark context.

Infrastructure Requirements

ComponentPurpose
Data warehouseCentralized data; BI reporting
Event trackingUser behavior; funnel mapping
AttributionAd pixels; attribution model; impression-to-sale tracking

Optimization flow: Clean UTM + conversion events → attribution reports → optimize channel mix.

Scope

  • GA4: Web data stream, gtag.js, configuration
  • User ID: Cross-device, cross-session identification
  • CTA attribution: Per-article conversion tracking for content ROI
  • Events: Recommended and custom events
  • Conversions: Key events, parameters
  • Quality: Naming, testing, validation

GA4 Setup

Prerequisites

  • Google Analytics property and web data stream
  • Google tag (gtag.js) on all pages
  • Measurement ID (e.g., G-XXXXXXXXXX)

Enhanced Measurement

Enable in Admin > Data Streams > Enhanced Measurement for automatic tracking of:

  • Page views, scrolls, outbound clicks
  • Site search, file downloads
  • Video engagement (YouTube)

Event Tracking

Event Types

TypeDescription
Automatically collectedpage_view, first_visit, session_start
Enhanced measurementscroll, click, file_download, etc.
Recommendedpurchase, sign_up, search, etc.
CustomBusiness-specific actions

Naming Conventions

  • Length: <=40 characters (GA4 hard limit; longer names are not logged)
  • Format: snake_case, lowercase
  • Verb first: download_pdf, submit_form, video_play
  • Context: pricing_page_scroll vs generic scroll

gtag.js Syntax

javascript
gtag('event', '<event_name>', {
  <parameter_name>: <value>,
  // e.g. value: 99.99, currency: 'USD'
});

Place below the Google tag snippet. Events fire on page load or user action (e.g., button click).

Recommended Events

EventUseKey Parameters
purchaseE-commercevalue, currency, items
sign_upRegistrationmethod
loginLoginmethod
searchSite searchsearch_term
view_itemProduct viewitems
add_to_cartAdd to cartitems

Custom Events

  • Focus on 15-25 meaningful events aligned with KPIs
  • Add parameters for context (e.g., content_type, item_id)
  • Avoid tracking everything; prioritize quality over quantity

Conversions (Key Events)

  • Mark important events as conversions in GA4 Admin
  • Use for attribution, audiences, and reporting
  • Typical: purchase, sign_up, lead, contact

Attribution & Conversion Optimization

Attribution models determine how conversion credit is assigned across touchpoints. Use attribution data to optimize ads and growth channels.

ModelUse
Data-driven (GA4 default)ML assigns credit by actual contribution; best for multi-touch journeys
Last-click100% to final touchpoint; simple but undervalues awareness/consideration

Optimization flow: Clean UTM (source, medium, campaign) + conversion events → GA4 attribution reports → compare channels by attributed conversions → reallocate budget to ads/channels that drive results. Inconsistent UTM fragments data; multi-touch attribution requires reliable touchpoint data.

Reference: UTM.io – UTMs for Marketing Attribution, GA4 – Get started with attribution

Testing & Validation

ToolUse
RealtimeSee events as they fire
DebugViewDetailed event/parameter inspection; requires debug mode
GA4 Debug modegtag('config', 'G-XXX', { 'debug_mode': true }); or GTM preview
  • Test before launch; verify parameters and naming
  • Check for duplicate events, missing values

Output Format

  • Event list (name, trigger, parameters)
  • Implementation notes (gtag or GTM)
  • Conversion mapping
  • Testing checklist

Related Skills

  • traffic-analysis: UTM, source attribution; attribution for channel optimization
  • ai-traffic-tracking: AI traffic in GA4
  • google-search-console: GSC analysis (correlate with GA4)
  • seo-monitoring: Article database, benchmark, full SEO monitoring framework

Frequently asked questions

What does the Analytics Tracking AI skill do?

When the user wants to set up, audit, or optimize analytics tracking (GA4, events, conversions). Also use when the user mentions "Google Analytics," "GA4," "event tracking," "conversions," "attribution model," "gtag," "data layer," "GA4 setup," "conversion tracking," "event setup," "User ID tracking," or "CTA attribution." For traffic insights, use traffic-analysis.

Why use Analytics Tracking on TypingMind?

Because you install it once and use it with any model. Analytics Tracking 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 Tracking in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/kostja94/marketing-skills/tree/main/skills/analytics/tracking. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Analytics Tracking?

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 Tracking?

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

Is the Analytics Tracking AI skill free?

Yes. It is published on GitHub by kostja94 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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