Answer Engine Optimization The Fundamentals
Get cited by ChatGPT, Perplexity, and Google AI Overviews.
Answer Engine Optimization (AEO) is the practice of structuring web content so generative AI assistants - ChatGPT, Perplexity, Google AI Overviews, Claude, Gemini - can find it, trust it, and cite it verbatim in their responses. Where SEO optimizes for the ten blue links, AEO optimizes for the single sentence an AI quotes back to a buyer asking "what is the best...".
The technical baseline for AEO is well-established: explicit FAQ schema, entity-rich semantic markup, citation-ready chunks (one claim per paragraph, definitions at the top of sections), credible author attribution, and a clean robots.txt that explicitly allows the major AI crawlers (GPTBot, ClaudeBot, PerplexityBot, Google-Extended). Sites that ship all five start appearing in AI Overview citations within 2-4 weeks.
Beyond the basics, the moats are structural: Wikidata entity definitions, comparison content ("X vs Y" pages with explicit pros and cons), measurable claims with sources, and a topic-cluster architecture (a hub page per theme, with 5-15 spoke articles linking up to it). SCAILE's Content Engine ships all of these continuously - the LipoCheck deployment hit #1 in AI Health rankings within 5 months using exactly this pattern.
This hub indexes every SCAILE article on AEO foundations: what an answer engine actually does, how to audit your current AI visibility, the schema markup patterns that drive citations, and the difference between AEO and traditional SEO.
In this topic
- What AEO is and how it differs from SEO
- How AI assistants choose what to cite
- The schema markup that drives 80% of AI citations
- A 29-point audit you can run on your site today
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