LLM Traffic Detector 🤖

Gain full visibility into traffic originating from Large Language Models (LLMs) such as ChatGPT, Google Gemini, Perplexity AI, Microsoft Copilot, and Claude.

This Google Tag Manager (GTM) template allows you to detect, segment, and control LLM-influenced traffic within your analytics and performance marketing ecosystem.

🚀 Why LLM Traffic Detector?

As AI models increasingly browse the live web, your GA4 data and attribution models can become skewed by non-human interactions. This tool empowers you to:

• Filter AI Traffic: Keep your conversion rates and engagement metrics clean.
• GA4 Segmentation: Create dedicated audiences or segments for LLM sessions.
• Advanced Attribution: Ensure your marketing spend is evaluated against real human behavior.
• Server-Side Ready: Fully compatible with Server-side GTM (sGTM), especially when using TAGGRS.

✨ Key Features

• ✅ Smart Detection: Identifies bots and crawlers from major AI providers via User-Agent analysis.
• ✅ Boolean Logic: Outputs a simple true (AI traffic) or false (Human traffic).
• ✅ Lightweight: Designed for performance with zero dependencies.
• ✅ Seamless Integration: Works as a standard GTM variable for use in any tag or trigger.

🛠 Configuration & Installation

1. Add the Template

• From Gallery (Recommended): In GTM, go to Templates → Search Gallery. Search for "LLM Traffic Detector" and click Add to Workspace.
• Manual: Download the LLM Traffic Detector.template file from this repository and import it under the Templates section.

2. Create the Variable

1. Navigate to Variables → New → User-Defined Variables.
2. Select LLM Traffic Detector as the variable type.
3. Name it (e.g., {{LLM Traffic Detector}}) and Save.

3. Implementation

• In Triggers: Use a condition like {{LLM Traffic Detector}} equals false to ensure a tag only fires for human visitors.
• In Tags: Pass the variable into GA4 as a User Property or Event Parameter (e.g., is_llm_traffic) to enable session-level segmentation.

🧪 Testing & Publishing

1. Enter GTM Preview mode.
2. Spoof an LLM User-Agent using browser DevTools (e.g., set your Network conditions to Mozilla/5.0... GPTBot).
3. Verify that the variable output shows true.
4. Once verified, Publish your container.

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📊 Example Use Cases

Trigger: Human Traffic Only

Setting	Value
Event Type	Custom Event / Page View
Trigger condition	{{LLM Traffic Detector}} equals false

TAGGRS Integration

Pass the boolean value to your server-side container to enable advanced attribution filtering and prevent AI "noise" from reaching your marketing pixels.

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🏗 Requirements

• Google Tag Manager container (Client-side or Server-side).
• For sGTM: A TAGGRS setup is recommended for enhanced tracking accuracy and server-side processing.

🤝 Contributing

Contributions are welcome! If you encounter a new AI bot that isn't being detected yet, please open an Issue or submit a Pull Request.

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

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Maintained by TAGGRS