Answer engines don’t rank pages, they extract claims

Disclosure: I work on this product — posting on behalf of the team.

Been watching how ChatGPT, Perplexity and Google's AI Overviews decide what to cite, and the model that explains the behaviour is different from classic search.

Search ranks pages. Answer engines extract claims, then look for something to attribute them to. A few things follow:

**Specific beats comprehensive.** A 3,000-word guide gets skimmed for one sentence. A page stating a concrete, checkable fact in one clean sentence gets cited for that fact. The citation attaches to a passage, not the page.

**Structure is a retrieval affordance, not a ranking signal.** Headings phrased as the actual question, a direct answer in the first sentence under it, tables for anything comparative. Retrieval works on chunks, and a passage that still makes sense after being pulled out of context is the one that survives.

**Freshness matters more than in search**, especially for anything with a number in it – pricing, model names, version strings. Stale specifics get dropped while the page still ranks fine.

The uncomfortable part: you can do all of this and still not get cited, because the engine already likes an answer from a higher-trust domain.

Has anyone found a way to measure citation share that's stable week to week? Everything I've tried is too noisy to act on.