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ai-traffic-tracking▌

kostja94/marketing-skills · updated Apr 8, 2026

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$npx skills add https://github.com/kostja94/marketing-skills --skill ai-traffic-tracking
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summary

Guides tracking of AI-driven search traffic in Google Analytics 4 and Google Search Console.

skill.md

Analytics: AI Traffic

Guides tracking of AI-driven search traffic in Google Analytics 4 and Google Search Console.

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.

Scope

  • AI search traffic: Track in GA4 and GSC; separate AI sources from organic referral
  • Google AI Overviews: AI summary box in Google search (formerly SGE)
  • AI-driven search: Traffic from ChatGPT, Perplexity, Gemini, Claude, Copilot, etc.

Why Track Separately

  • AI traffic is growing but GA4 often groups it as Referral, Organic, or Direct
  • AI visitors may have stronger intent and higher conversion
  • Separating AI Overviews from organic helps assess AI impact

GA4: AI-Driven Search

Option 1: Exploration Report (Recommended)

  1. Explore →Free form
  2. Dimensions: Session source (or Session source / medium)
  3. Metrics: Sessions, Engagement rate, Event count, etc.
  4. Filters: Add filter →Session source Matches regex →use regex below
  5. Configure table, save report

Regex (common AI sources):

chatgpt\.com|openai\.com|openai|perplexity\.ai|perplexity|doubao\.com|chat\.qwen\.ai|copilot\.microsoft\.com|copilot\.com|(business\.)?gemini\.google|chat\.deepseek\.com|deepseek\.com|poe\.com|anthropic\.com|claude\.ai|bard\.google\.com|edgeservices\.bing\.com

Option 2: Custom Channel Group

  1. Admin →Data Display →Channel Groups
  2. Copy default group, name e.g. "Default and AI Chatbots"
  3. Add channel "AI Chatbots": Source Matches regex (same regex)
  4. Important: Place "AI Chatbots" above "Referral" so it matches first
  5. Save and use in Traffic Acquisition

Option 3: Custom Report

  1. Reports →Library →Create Detail Report
  2. Use Traffic Acquisition template
  3. Add filter: Session source Matches regex (same regex)
  4. Save and add to menu

Common AI Source Domains

Platform GA4 Source examples
ChatGPT chatgpt.com, openai
Perplexity perplexity.ai, perplexity
Copilot copilot.com, copilot.microsoft.com
Gemini business.gemini.google, gemini.google
Claude claude.ai, anthropic.com
Bing Chat edgeservices.bing.com

Google AI Overviews

  • GA4 + URL fragment: Some AI Overview clicks add URL fragments; can use GTM (partial coverage)
  • GSC: For AI Overviews analysis in GSC (filter, limitations), see google-search-console

Checklist

  • AI sources identified in GA4 (Session Source)
  • AI traffic Exploration report created
  • Channel group updated with AI above Referral (if used)
  • Custom report added to Library (optional)
  • GTM + URL fragment for AI Overviews (optional)
  • GSC AI-oriented query filter (optional; see google-search-console)

Output Format

  • GA4 setup: Exploration, channel group, or custom report
  • Regex: Adapted to user's observed sources

Related Skills

  • generative-engine-optimization: GEO strategy; AI traffic tracking measures GEO impact
  • traffic-analysis: Traffic sources, attribution, UTM
  • analytics-tracking: GA4 events and conversions
  • google-search-console: GSC AI traffic analysis
  • robots-txt: AI crawler allow/block strategy
how to use ai-traffic-tracking

How to use ai-traffic-tracking on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • ›Cursor installed and configured on your development machine
  • ›Node.js version 16.0+ with npm package manager (verify with node --version)
  • ›Active project directory or workspace where you want to add ai-traffic-tracking
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/kostja94/marketing-skills --skill ai-traffic-tracking

The skills CLI fetches ai-traffic-tracking from GitHub repository kostja94/marketing-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/ai-traffic-tracking

Reload or restart Cursor to activate ai-traffic-tracking. Access the skill through slash commands (e.g., /ai-traffic-tracking) or your agent's skill management interface.

⚠

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

Additional Resources

›View source code on GitHub›Skills CLI documentation›Learn more about Cursor›What are agent skills?

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases▌

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

✓

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

✓

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

✓

Improve work quality by 30-40% with less effort

Implementation Guide▌

Prerequisites

  • ›Claude Desktop or compatible AI client with skill support
  • ›Clear understanding of task or problem to solve
  • ›Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • ⚠Expecting perfect results without iteration
  • ⚠Not providing enough context in prompts
  • ⚠Using skill for tasks outside its intended scope
  • ⚠Accepting outputs without review and validation

Best Practices▌

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • −Don't use without understanding skill limitations
  • −Don't skip validation of outputs
  • −Don't share sensitive information in prompts
  • −Don't expect skill to replace human judgment

💡 Pro Tips

  • ★Be specific about desired format and style
  • ★Ask for multiple options to choose from
  • ★Request explanations to understand reasoning
  • ★Combine AI efficiency with human expertise

When to Use This▌

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path▌

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.5★★★★★38 reviews
  • ★★★★★Ira Taylor· Dec 16, 2024

    ai-traffic-tracking reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • ★★★★★Ira Abebe· Nov 15, 2024

    ai-traffic-tracking fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • ★★★★★Layla Li· Nov 11, 2024

    Registry listing for ai-traffic-tracking matched our evaluation — installs cleanly and behaves as described in the markdown.

  • ★★★★★Meera Lopez· Nov 7, 2024

    ai-traffic-tracking is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • ★★★★★Meera Malhotra· Oct 26, 2024

    Useful defaults in ai-traffic-tracking — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • ★★★★★Sakura Chawla· Oct 6, 2024

    Registry listing for ai-traffic-tracking matched our evaluation — installs cleanly and behaves as described in the markdown.

  • ★★★★★Olivia Ndlovu· Oct 2, 2024

    ai-traffic-tracking fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • ★★★★★Sakshi Patil· Sep 25, 2024

    Keeps context tight: ai-traffic-tracking is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • ★★★★★Rahul Santra· Sep 21, 2024

    ai-traffic-tracking fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • ★★★★★Ama Haddad· Sep 17, 2024

    Useful defaults in ai-traffic-tracking — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

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