Ask ChatGPT or Perplexity a question and it hands back an answer with two or three sources cited. Somewhere behind that answer, a decision got made about which pages made the cut.
That decision does not run on the same logic as a Google ranking. A page can rank well in classic search and never get cited by an AI answer, and the reverse happens just as often.
Quick summary, if you’re short on time:
- OpenAI’s own documentation confirms ChatGPT rewrites a question into one or more targeted search queries, sent to a search partner, then often refines with follow-up queries before answering.
- Perplexity’s own help centre states responses are “supported by citations from reputable news organizations, academic publications, and established content sources.”
- A 2023 Princeton-led study, GEO: Generative Engine Optimization, found specific content changes could lift a source’s visibility in generative answers by up to 40%.
- Most of that study ran on a benchmark simulation, though the strongest methods were also validated against live Perplexity.ai on a smaller sample, so treat the direction as real and the exact number as a best-case figure, not a guarantee.
- What consistently helps: clear factual statements, credible sourcing, and content structured so a specific sentence can be lifted and quoted on its own.
Jump to a section:
- What actually happens when ChatGPT searches the web
- What Perplexity says about its own sourcing
- The one controlled study on what moves the needle
- What this means for how you write
- What doesn’t move the needle
- Using AI to check your own content for citability
- Questions worth answering directly
What actually happens when ChatGPT searches the web
OpenAI’s own help documentation lays out the mechanism plainly: ChatGPT does not simply pass your question to a search engine word for word. It rewrites the question into one or more targeted queries first.
OpenAI’s own example is a good illustration: a researcher asking about CCR8-targeting cancer drugs might trigger a query like “CCR8 immunotherapy drug development 2025,” then a narrower follow-up query once the first results come back.
The same documentation names its actual search partners: Microsoft (Bing) and Shopify. The Shopify inclusion matters for anyone selling products, since it means commerce queries can draw on structured product data, not just general web pages.
That two-step pattern matters for anyone writing content to be found this way. A page has to answer the broad version of a question clearly, and also contain the specific, narrower detail a refined follow-up query would surface.
What Perplexity says about its own sourcing
Perplexity is less specific about its exact ranking mechanics publicly, but its own help centre is direct about the standard it holds sources to: responses are built on citations “from reputable news organizations, academic publications, and established content sources.”
That phrasing rewards exactly what it says: publications and pages with an established track record on a topic, not necessarily the newest or most keyword-optimised page on the web. A single strong, well-sourced page tends to outperform a thin one built purely to target a query.
The one controlled study on what moves the needle
Most of what circulates about AI citation behaviour is inference from watching outputs. One study is different: GEO: Generative Engine Optimization, from researchers at Princeton University and the Indian Institute of Technology Delhi, published in 2023 and later presented at ACM SIGKDD 2024.
The researchers built a benchmark, GEO-bench, simulating how a generative engine retrieves top search results and synthesises an answer with citations. Testing specific content changes against that simulation, they found visibility could improve by up to 40%.
Worth being precise about what that number does and doesn’t prove: most of the testing ran on a controlled benchmark (GEO-bench), though the researchers also validated their strongest methods against live Perplexity.ai on a smaller sample. The 40% is a best-case figure for specific methods and domains, not an average result any page should expect to reproduce.
What this means for how you write
The consistent thread across both the official documentation and the research is that these systems reward content that is easy to lift cleanly. A dense paragraph mixing five ideas together is hard to extract a clean citation from.
A page structured around clear, self-contained factual statements, each one true and useful on its own, gives a generative engine something it can quote directly without needing to paraphrase or guess at context. This is the same instinct behind structuring content with clear headings and schema markup, covered in more depth in our guide to schema for AI visibility.
Citing real, checkable sources within your own content also matters more than it does for traditional SEO. A page that references genuine primary sources signals the kind of credibility both OpenAI’s and Perplexity’s own guidance point toward.
What doesn’t move the needle
Repeating a brand name or target phrase across a page does nothing here. Neither ChatGPT’s query-rewriting nor Perplexity’s stated preference for established sources rewards keyword density; both are explicitly built around extracting and verifying factual content.
Chasing traditional keyword rankings and generative citations as if they were the same goal also leads nowhere useful. A page can be written for one and genuinely hurt its chances at the other, since dense, keyword-heavy copy is exactly what’s hard to cleanly quote.
Using AI to check your own content for citability
A useful, low-effort check is to ask an AI model to try quoting your own page back to you, and see what it struggles with.
“Read the page at [URL] or the text I’ve pasted below.
Task:
1. Pick the three sentences on this page you would be most confident quoting directly, word for word, if asked a relevant question.
2. Point out any paragraph where the main point is buried in a mix of other ideas, making it hard to extract cleanly.
3. Tell me honestly whether the sourcing and factual claims on this page look credible enough to cite, or whether they read as unsupported opinion.”
If the model struggles to find three cleanly quotable sentences, that’s a real, actionable signal about how the page is structured, regardless of how well it happens to rank in traditional search.
Questions worth answering directly
Does ranking well on Google mean a page will get cited by ChatGPT or Perplexity?
Not automatically. Google ranking and generative-engine citation use different mechanics: ChatGPT rewrites queries and searches through a partner index, and Perplexity states it favours established, credible sources specifically. A page can do well in one and be overlooked in the other.
Is the 40% visibility improvement from the Princeton study something any page can expect?
Not exactly. Most of the testing ran on a benchmark simulation (GEO-bench), but the researchers did validate their strongest methods against live Perplexity.ai on a smaller, 200-sample test. Either way, 40% is a best-case figure for specific methods and domains, not a guaranteed result for any given page.
Does keyword stuffing help get cited by AI answers?
No. Both OpenAI’s query-rewriting approach and Perplexity’s stated preference for established, credible sources work against keyword-dense content. Clear, quotable factual statements perform better than repeated phrases.
What is the single most useful thing to fix first?
Look for paragraphs mixing several ideas into one dense block. Splitting them into clear, self-contained factual statements makes a page easier for a generative engine to quote directly, which is the behaviour both OpenAI and Perplexity describe rewarding.
How does ChatGPT decide what to search for?
OpenAI’s help documentation says ChatGPT rewrites your question into one or more targeted search queries first, sends them to a search partner, and often refines with follow-up queries before answering. The documentation names Microsoft (Bing) and Shopify as partners.
How does Perplexity describe the sources it uses?
Its help centre says responses are supported by citations “from reputable news organizations, academic publications, and established content sources.” That rewards pages with an established track record on a topic more than the newest or most keyword-optimised page.
Where this actually pays off
Nobody outside OpenAI or Perplexity has the exact ranking formula, and anyone claiming otherwise is guessing. What’s verifiable is what both companies say about their own systems, and what one controlled study found when it tested real content changes.
Not sure whether your own content is structured to be citable, not just rankable? We review this as part of every AI SEO and GEO engagement we run.
