Trace ChatGPT Web Queries: Step-by-Step Guide

When ChatGPT uses web browsing to answer questions, it runs real search queries behind the scenes. Tracing these queries reveals exactly what it's looking for—and why certain businesses get recommended while others don't.

This step-by-step guide shows you how to capture and analyse ChatGPT's search behaviour, from simple methods anyone can use to advanced techniques for developers.

Quick Method: Ask ChatGPT (2 minutes)

The fastest way to see ChatGPT's queries is simply to ask.

Step 1: Ask a question that requires web browsing

Step 2: After it responds, ask for the queries

Step 3: Ask which sites it read

ChatGPT will typically provide a clear breakdown of its search process.

Intermediate Method: Browser Network Tab (10 minutes)

For more detailed insight, you can watch the actual network requests.

Step 1: Open Developer Tools

• Chrome/Edge: Press F12 or right-click → "Inspect"
• Firefox: Press F12 or right-click → "Inspect Element"
• Safari: Enable Developer menu in preferences, then Cmd+Option+I

Step 2: Go to the Network tab

Click "Network" at the top of the Developer Tools panel. This shows all HTTP requests the page makes.

Step 3: Filter for relevant requests

• Click "Fetch/XHR" to filter for API calls
• Type "search" or "browse" in the filter box
• Watch for requests as ChatGPT processes your question

Step 4: Inspect the request details

Click on any request to see:

• Headers: What was sent
• Payload: The query parameters (including search terms)
• Response: What came back

Advanced Method: API with Tool Call Logging

If you're a developer, the OpenAI API gives you complete visibility into ChatGPT's browsing behaviour.

Step 1: Set up an API call with browsing enabled

import openai

client = openai.OpenAI()

response = client.chat.completions.create(
    model="gpt-4-turbo",
    messages=[
        {"role": "user", "content": "Who are the best plumbers in Manchester?"}
    ],
    tools=[{"type": "web_search"}],  # Enable browsing
)

Step 2: Extract the tool calls

# The response includes tool_calls array
for tool_call in response.choices[0].message.tool_calls:
    print(f"Tool: {tool_call.function.name}")
    print(f"Arguments: {tool_call.function.arguments}")
    # This shows the exact search queries run

Step 3: Log and analyse patterns

Build up a database of queries for your industry:

# Example: Track queries over multiple tests
queries_log = []
for question in customer_questions:
    response = run_chatgpt_with_browsing(question)
    queries_log.append({
        "question": question,
        "searches": extract_search_queries(response),
        "sources_cited": extract_sources(response)
    })

# Analyse: What queries surface your competitors but not you?

What to Look For in the Queries

Once you're tracing queries, here's what to analyse:

1. Query reformulation

ChatGPT often rephrases user questions. A user asking "good plumber near me" might trigger searches like:

• "best rated plumbers [city]"
• "emergency plumbing services [area]"
• "plumber reviews [location]"

2. Multi-step searches

ChatGPT often runs multiple queries to build context:

• First: Find options ("plumbers in Manchester")
• Then: Verify quality ("[company name] reviews")
• Finally: Check specifics ("[company] emergency callout")

3. Trust-verification queries

Before recommending a business, ChatGPT often searches for:

• Reviews and ratings
• Company credentials or certifications
• Comparison articles mentioning the business

Practical Example: Tracing a Local Business Query

Let's trace a real example. User asks ChatGPT:

Using the methods above, we might see ChatGPT run:

1. Query 1: "best travel agents Plymouth UK"
2. Query 2: "Plymouth travel agency family holidays reviews"
3. Query 3: "[top result company name] reviews trustpilot"

If your travel agency doesn't appear in any of these searches, ChatGPT can't recommend you—no matter how good you are.

Using Query Traces to Improve Visibility

Once you've traced the queries, here's how to act on them:

Common Gaps We Find

From tracing hundreds of queries, here are the most common reasons businesses are invisible:

• Location not explicit: Your site says "we serve the local area" instead of "we serve Plymouth, Saltash, and South Devon"
• No review presence: ChatGPT can't find reviews to verify you're trustworthy
• Generic descriptions: "Quality service" doesn't match "24/7 emergency callout" queries
• Missing from directories: If you're not on industry directories, you're not in the search results ChatGPT reads

Next Steps

Start with the quick method—ask ChatGPT a question about your industry and then ask what it searched. You'll immediately see whether your business is even in the running.

For ongoing monitoring, set up a simple process: once a week, test 5-10 questions your customers might ask. Trace the queries, note which competitors appear, and track your progress as you make improvements.

The businesses that understand ChatGPT's search behaviour—and optimise for it—are the ones that get recommended.