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ChatGPT May Scrape Google, but the Results Don’t Match

ChatGPT May Scrape Google, but the Results Don’t Match

We know that AI assistants like ChatGPT access search indices, like Google and Bing, to retrieve URLs for their response. But how, exactly?

To find out, we’ve run a series of experiments looking at the relationship between the URLs cited by AI assistants, and the results found in Google when searching for the same topics.

So far, we’ve tested long-tail prompts (very long, very specific queries just like those you’d enter into ChatGPT); fan-out queries (mid-length prompts that relate to the original long-tail prompt); and today we’re testing short-tail keywords—ultra-short, ultra-specific “head” terms.

Short-tail keywords offer the clearest illustration of how AI citations track with Google results.

Based on three separate studies, our conclusion is that ChatGPT (and similar systems) don’t just lift URLs directly from Google, Bing, or other indexes. Instead, they apply additional processing steps before citing sources.

Even when we examined fan-out queries—the actual search prompts these systems send to search engines—the overlap between AI and search engine citations was surprisingly low.

In other words, while ChatGPT may pull from Google’s search index, it still appears to apply its own selection layer that filters and reshuffles which links appear.

It’s therefore not enough to identify fan-out queries and rank well for them—there are additional factors influencing which URLs get surfaced, that are outside of a publisher’s control.

Xibeijia Guan analyzed citation overlap between AI and search results for informational long-tail and fan-out prompts, using Ahrefs Brand Radar.

A screenshot of Ahrefs Brand Radar dashboard, highlighting 15 AI mentions for the long-tail query "how much does it cost to install a security camera"

This time, she has taken a sample of 3,311 classic SEO-style head terms, covering informational, commercial, transactional, and navigational intent.

Example query Informational Commercial Transactional Navigational
1 cincinnati bearcats basketball best credit card rewards pools for sale onedrive sign in
2 protein in shrimp soundbar for tv shop girls dress verizon customer support
3 what is cybersecurity at home sauna buy a domain costco toilet paper

Each keyword has been run through ChatGPT, Perplexity, and Google’s top 100 SERPs to analyze citation overlap between AI and search.

OpenAI and Perplexity have been scraping Google results via a third-party provider.

It’s possible we’d see more overlap if our study focused only on ‘real-time’ queries (e.g., news, sports, finance), since those are reportedly the kinds ChatGPT scrapes Google for.

ahrefs.com/writing-tools/, while ChatGPT finds a better “fit” on ahrefs.com/blog/ and cites another.

If true, this reinforces the value of creating cluster content—optimizing multiple pages for different topic intents, to have the best chance of being found.

Another possibility is that both lean on the same pool of authoritative domains, but disagree on arbitrary pages.

Assess your cluster content in AI and search

You can check the SEO performance of your cluster content in the Related Terms report in Ahrefs Keywords Explorer.

This will show you if and where you rank across an entire cluster of related keywords.

Just add a Parent Topic filter, and a Target filter containing your domain.

A screenshot of Ahrefs "Clusters by Parent Topic" tab within the Related Terms report. A parent topic filter has been applied for "Is: check google ranking", and a target filter has been applied for "ahrefs.com". An arrow points from the target filter to a pop-up report which shows the highlighted ranking positions for Ahrefs across the parent topic.

Once you’ve done that, head to Ahrefs Brand Radar to check on the AI performance of your cluster content.

Run individual URLs through the Cited Pages report in Ahrefs Brand Radar to see if your cluster content is being cited by AI assistants like ChatGPT, Perplexity, Gemini, and Copilot.

A screenshot of the Cited Pages report in Ahrefs Brand Radar, circling a "Page URL Contains:" filter, with a specific Ahrefs blog included. An arrow points to the circled filter, with the writing "Check specific domains, URLs, and subfolders being cited in AI" A trend chart shows the trended performance of the blog in ChatGPT.

Work out if any content is missing from either surface, then optimize until you’ve filled those gaps and enriched the overall cluster.

You can use topic gap recommendations in Ahrefs’ AI Content Helper to help with this.

A screenshot of Ahrefs AI Content Helper interface, with the AI generated "Recommendations" section circled, which provides suggestions on how to fill topic gaps.

studied by SQ and Xibeijia) show the least overlap. They match only 6.82% of Google’s top 10 results.

A bar chart showing three bars representing short-tail (10%), long-tail (7.05%), and fan-out queries (6.82%). The chart is titled: ChatGPT URL overlap with SERP across query types (Ahrefs study of ~3K queries)

We’re not comparing apples-with-apples here. These percentages represent different studies, and different sized datasets.

But each study produces similar findings: the pages that ChatGPT cites don’t overlap significantly with the pages that Google ranks. And it’s largely the opposite for Perplexity.

SQ seems the most probable one to me:

“ChatGPT likely uses a hybrid approach where they retrieve search results from various sources, e.g. Google SERPs, Bing SERPs, their own index, and third-party search APIs, and then combine all the URLs and apply their own re-ranking algorithm.”

Whatever the case, search and AI are shaping discovery side-by-side, and the best strategy is to build content that gives you a chance to appear on both surfaces.

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