How can I track traffic from ChatGPT and Perplexity using Google Analytics?

You can see traffic from LLMs (ChatGPT, Perplexity, Claude, Gemini, etc.) in Google Analytics 4 (GA4), but it’s a bit hidden because most LLM referrals don’t show up as a clean “LLM” channel. Here’s how to surface it clearly.


1. Where LLM traffic usually appears in GA4

LLM traffic can show up as:

  • Referral traffic (most common)
  • Organic Search (especially Google Gemini / SGE)
  • Direct (when referrer is stripped)

So you’ll need to look beyond default channel groupings.


2. Quick win: View LLM referrals directly

Step-by-step

  1. Go to Reports → Acquisition → Traffic acquisition
  2. Change the primary dimension to Session source / medium
  3. Use the search box or filter for known LLM sources:

Common ones to look for:

chat.openai.com
openai.com
perplexity.ai
claude.ai
anthropic.com
bard.google.com
gemini.google.com
copilot.microsoft.com
bing.com (Copilot traffic often hides here)
you.com
phind.com

📌 Most will appear as:

chat.openai.com / referral
perplexity.ai / referral

3. Create an Exploration for deeper analysis (recommended)

This is the cleanest way to track LLM traffic over time.

Steps

  1. Go to Explore → Blank
  2. Add dimensions:
    • Session source
    • Session medium
    • Landing page
  3. Add metrics:
    • Sessions
    • Engaged sessions
    • Conversions (if set)
  4. Add a Filter:
    • Include → Session source → contains →openai | chat | perplexity | claude | anthropic | gemini | copilot | you.com | phind

Now you’ll see:

  • Which pages LLMs send traffic to
  • Engagement quality vs search/social
  • Conversion performance

4. Identify “hidden” LLM traffic inside Organic Search

Some AI answers (especially Google SGE / Gemini) still count as organic search.

To isolate this:

  1. Go to Search Console → Performance
  2. Look for:
    • Very long, conversational queries
    • Question-based searches that align with AI-style prompts
  3. Compare landing pages that spike without traditional SEO changes

📌 This isn’t perfect, but it helps identify AI-assisted discovery.


5. Optional: Create a custom “LLM” channel group

If you want LLM traffic visible in standard reports:

  1. Go to Admin → Data settings → Channel groups
  2. Create a new channel called LLM
  3. Rules:
    • Session source contains:chat.openai.com perplexity.ai claude.ai anthropic.com gemini.google.com copilot.microsoft.com you.com phind.com

This lets LLM traffic show up alongside Organic, Paid, Social, etc.


6. Why LLM traffic is often underreported

  • Some LLMs strip referrer data
  • In-app browsers often show as Direct
  • Copilot traffic frequently appears as bing.com
  • AI summaries may not generate a click at all (zero-click exposure)

7. Bonus: Best practices to improve LLM-attributed traffic

To get more measurable traffic from LLMs:

  • Add clear citations and authoritative language
  • Use FAQ-style content
  • Publish original data or definitions
  • Make sure pages are crawlable and fast
  • Add schema (FAQ, HowTo, Article)

TL;DR

  • Look under Referral → Session source
  • Build an Exploration with LLM source filters
  • Create a custom LLM channel group
  • Expect some traffic to hide under Direct or Organic