GEO & AI search
Retrieval-augmented answer
Definition
An AI response generated by first searching for relevant live pages, then having the model read and synthesize from those specific pages — as opposed to answering purely from training data. Perplexity's shopping answers are retrieval-augmented, which is why what's on your page right now matters more than what a model "knows" about your brand.
Defined in How Perplexity Picks Products (Observed Behavior).
Related terms
- Commerce GEO
- Generative engine optimization applied to commerce — the practice of structuring a catalog and content so AI assistants like ChatGPT, Claude, Gemini, and Perplexity cite and recommend it.
- Shared foundation
- Technical and data work — structured data, attribute completeness, site architecture, page performance — that simultaneously improves classic search rankings and AI-assistant citation accuracy. It should be budgeted once, not split across SEO and GEO line items.
- Answer-first structure
- Writing the conclusion or direct answer as the first sentence of a section, with supporting reasoning and caveats following it — the inverse of narrative or journalistic structure, which builds to a conclusion.
- Corroboration
- Independent confirmation of a claim from a source that isn't the brand itself. In GEO terms, it's the difference between a fact an assistant can state with confidence and one it has to hedge or omit.
- Server-side rendering
- Generating the full HTML — including product facts and JSON-LD — on the server so it's present in the initial response, before any JavaScript runs. The opposite of client-rendering facts into the page after load.
- AI citation audit
- A structured test of how AI assistants treat your brand when shoppers ask buying questions in your category. You run a fixed panel of questions across the major assistants and score each answer on a three-level scale - named in the recommendation, cited as a source, or absent - producing a score you can track and a gap log you can act on.
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