What actually gets cited: patterns across 40+ AI answer engine queries
A working note on which page structures and entity signals AI answer engines (ChatGPT, Perplexity, Google AI Mode) actually pull from, based on what weve tracked across client domains.
Founder, Griot
We track which pages get pulled into AI-generated answers across every domain we run AEO on. This is a working note on the patterns that have held up across more than 40 tracked queries, not a final answer — the citation behavior of these engines changes month to month, and this note will be updated as it does.
What consistently gets cited
- Direct-answer paragraphs near the top of a page. Pages that open with a one-to-two sentence direct answer get pulled far more often than pages that build up to the answer narratively.
- Specific numbers over qualitative claims. "13,000 clicks in 90 days" gets cited where "significant growth" does not. Engines appear to prefer extractable facts over framing.
- Recently updated pages on otherwise-stable topics. A page that's been quietly refreshed in the last 30-60 days outperforms an older, unmaintained page covering the same question — even when the underlying answer hasn't materially changed.
What doesn't move the needle as much as expected
- Backlink volume, in isolation, correlates weakly with citation frequency for AEO specifically — it's a far stronger signal for traditional Google ranking than it is for whether ChatGPT or Perplexity choose to cite a page.
- Long-form depth doesn't help if the direct answer is buried. A 3,000-word page that takes 800 words to state its core claim gets outcited by an 800-word page that states it in the first paragraph.
The open question
We don't yet have enough data to say definitively whether entity authority (being a recognized, citable source generally) outweighs page-level formatting, or vice versa, when the two are in tension. Current working hypothesis: formatting determines whether a specific page gets cited; entity authority determines whether a domain gets considered as a candidate source in the first place. Both matter, but they're solving different parts of the problem.
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