aeogeoai.net
Miami AI Search Specialist
Ask ten people how ChatGPT decides which websites to cite and you'll probably get ten confident answers. The problem is that many are presented as facts when they're actually educated guesses.
This guide takes a different approach by separating three categories: confirmed behaviour (what we can observe and verify), strong observations (patterns we've seen repeatedly but haven't been officially confirmed), and working hypotheses (interesting ideas that deserve testing but shouldn't be treated as settled). This distinction matters because not all claims deserve equal confidence—and treating them differently is actually more useful for your strategy.
⚠️ A note on scope: AI retrieval systems evolve continuously. Everything in this article reflects publicly observable behaviour at the time of writing, not internal documentation from OpenAI. As systems change, some observations may shift or become outdated.
Summary
ChatGPT cites websites through live retrieval of candidate sources. This article separates confirmed behavior (ChatGPT browses the web, synthesises multiple sources, cites them) from strong observations (editorial mentions matter, consensus across sources increases visibility) from working hypotheses (entity consistency may help). The key distinction: ChatGPT assembles evidence from multiple sources rather than ranking a single "best" page. Bing indexing is critical—if ChatGPT cannot access a page, it cannot cite it. The article avoids speculation about internal mechanisms and instead focuses on patterns observable through public testing.
These are patterns we have good evidence for. ChatGPT or OpenAI has either confirmed them, or they're observable through straightforward testing.
None of these require speculation. They're either directly observable through testing or are consistent with publicly documented ChatGPT capabilities.
These patterns have been observed repeatedly across different queries and contexts, but OpenAI hasn't officially confirmed them. They're solid enough to act on, but they should be understood as observations rather than laws.
We should phrase these as observations: "Across testing..." or "Repeated observations suggest..." rather than treating them as proven facts. They're strong enough to guide your strategy, but they're not guarantees.
| Claim | Confidence Level |
|---|---|
| ChatGPT can browse live websites | High |
| ChatGPT synthesises information across multiple sources | High |
| Editorial mentions influence recommendations | Medium |
| Schema markup directly increases citations | Low–Medium |
| Domain authority metrics directly determine recommendations | Low |
Not all claims deserve equal confidence. This table summarizes the evidence strength behind common assertions about ChatGPT citation patterns.
These are interesting patterns that we suspect may matter, but we don't have enough evidence to recommend them confidently. They're listed here for completeness, and because monitoring them is worth the effort if you have the resources.
These are worth testing and monitoring, but they shouldn't be the focus of your initial effort. Start with the confirmed behaviours and strong observations.
Understanding the retrieval pipeline helps explain why certain pages get cited and others don't. This is the likely sequence, based on what we can observe:
Notice that each step is something we either know or can reasonably infer. There's no invented precision here. The key insight is that retrieval is not ranking—it's synthesis. Your goal is not to be "#1" in ChatGPT; it's to be a credible source that contributes evidence to an answer.
ChatGPT doesn't use live browsing for every query. Understanding when it does and doesn't browse is crucial—it explains why the same question might cite sources one day and not the next.
The practical implication: if your business serves time-sensitive needs or is responding to current events, being discoverable through browsing is critical. If your value proposition is more timeless, appearing in training knowledge (through historical mentions and foundational content) may matter more.
ChatGPT doesn't behave the same way for every type of query. Understanding which type of question you're optimising for is essential.
"What is AI search visibility?" "How does ChatGPT browsing work?"
For these, ChatGPT retrieves pages that explain concepts clearly. Your goal is to write the clearest, most concise explanation available. Cited pages often define terms, provide step-by-step breakdowns, or explain the "why" behind a concept.
"Best AI search agency in Miami" "Which tool should I use for AI visibility?"
For these, ChatGPT retrieves pages that recommend providers, compare options, or describe services. Inclusion typically requires independent editorial mention (reviews, comparisons, articles by third parties) or very high domain authority.
"AI search specialist near me" "Best lawyer in Miami for immigration law"
Local queries are harder. ChatGPT retrieves location-specific pages, local citations, and directory mentions. Optimisation here typically requires explicit location markup, local business citations, and content that clearly targets geographic intent.
"ChatGPT vs Claude vs Gemini" "SEO vs AEO"
These favour pages that structure comparisons clearly—tables, side-by-side analysis, pros and cons. Pages that address multiple sides of a question are retrieved more readily than one-sided advocacy.
"AEOGeoAI" "[Specific company name]"
For navigational queries, ChatGPT retrieves official pages, brand pages, and high-authority mentions. If you're being asked about by name, ChatGPT almost always cites your official channels first, then news mentions and industry recognition.
The point: Your optimisation strategy should differ based on the type of query you want to appear in. A strategy that works for informational queries (clear writing, strong definitions) won't work for commercial queries (which need editorial coverage). Clarify which query types matter to your business.
One of the most common mistakes businesses make is treating Bing as an afterthought. That approach made sense when Google was the only search engine that really mattered. AI search has changed that.
While OpenAI hasn't published the exact mechanics of ChatGPT's retrieval pipeline, its live browsing capabilities have long relied on Microsoft's search ecosystem. In practice, websites that are poorly indexed, poorly represented, or technically inaccessible in Bing appear less frequently among ChatGPT's live citations.
How confident should you be in this observation? Across our own testing and many real-world examples, Bing visibility appears to have a disproportionate influence on ChatGPT's live citations. OpenAI has not documented this relationship directly, but it is consistent with Microsoft's role in powering ChatGPT's browsing capabilities. Treat this as a strong signal, not a law.
Does this mean Google doesn't matter? No. Google remains the dominant search engine and an important source of authority and discoverability. But if AI visibility is one of your goals, Google alone is no longer sufficient. Think of Bing as a first-class search engine—not a secondary one.
Rule of thumb: If Bing can't reliably discover your content, ChatGPT is less likely to cite it during live browsing.
This is the most important conceptual shift in moving from SEO to AI visibility.
In Google search, the goal is clear: rank your page #1 in the results. The top result gets the most traffic. Pages below don't get traffic.
In ChatGPT, there is no "#1." ChatGPT is assembling evidence to answer a question. Multiple sources can each contribute information to the final answer. A page doesn't need to be the "best" source—it needs to be a credible contributor to the evidence base.
Example:
User: "What makes a good AI visibility agency?"
ChatGPT might cite your company for one point (entity consistency practices), a competitor's blog for another point (the importance of structured data), an industry publication for a third point (citation-generation strategies), and a framework from an SEO publication for a fourth point (the role of established editorial reputation).
In this scenario, you're cited once, but you're part of the answer. You don't need to be cited for everything to be valuable in ChatGPT's response.
This changes optimisation priorities. Instead of fighting for the top spot, you're building a strong evidence profile: clear explanations, independent corroboration, editorial mentions, structural consistency across sources. You want to be a credible piece of the puzzle, not necessarily the only piece.
ChatGPT's retrieval system needs to be able to parse your page. Basic technical accessibility is table stakes.
Use semantic HTML: proper heading hierarchy (h1, h2, h3...), lists for enumerated content, strong and em tags for emphasis, blockquotes for quoted material. Avoid pseudo-headings (divs styled to look like headings). This helps ChatGPT understand page structure.
Don't block ChatGPT's user agent in robots.txt (unless you've opted out of training data use entirely). Allow crawling of key pages. If you're using client-side rendering (JavaScript), make sure important content is available to crawlers—don't hide all text behind JS walls.
Schema.org markup (JSON-LD format) helps ChatGPT understand what your page is about. For company pages, use Organisation schema. For articles, use NewsArticle or BlogPosting. For local businesses, use LocalBusiness. This isn't a ranking factor, but it aids comprehension.
Pages that load quickly and don't time out are more likely to be fully parsed. Slow or unreliable pages may be skipped during retrieval.
Ensure your page displays correctly on mobile. Crawlers increasingly use mobile rendering, and broken layouts can interfere with content extraction.
ChatGPT doesn't have aesthetic preferences. Clear information in any format—bullets, paragraphs, tables—is fine. Use the format that best serves your content, not based on a guess about what AI prefers.
Length doesn't matter. Clarity does. A well-written 800-word essay will be retrieved over a poorly written 200-word fragment if the longer piece is more informative.
Absolutely false. Semantic HTML and clear structure matter. Excessive nesting doesn't help—it often hurts by complicating the DOM.
Wikipedia is cited frequently because it's well-written, comprehensive, and recognized as authoritative. Those are the real reasons, not bias. If your content is equally clear and credible, you can compete.
Backlinks matter for domain authority, which matters somewhat for retrieval. But direct evidence (editorial mentions, structured citations, clear information) often matters more. This isn't Google—a link is not a vote.
AI search optimisation is still a young discipline. The businesses that succeed won't be the ones chasing undocumented "ranking factors" or copying what competitors are doing. They'll be the ones building trustworthy entities with clear expertise, publishing evidence-rich content that actually helps people, and validating ideas through testing rather than assumption.
That approach is harder than following a checklist. But it's also more durable. In five years, when AI systems have matured and the landscape has shifted, the businesses with genuine expertise and real credibility will still be visible. The ones built on speculation will not.
We test your presence across ChatGPT, Claude, and Gemini—and help you build a strategy tailored to your business. Not marketing folklore; evidence-based optimisation.
Learn about our services →