The Ryze AI glossary defines the vocabulary of AI search for ecommerce operators. Terms covered: Generative Engine Optimization (GEO) — Generative engine optimization (GEO) is the practice of structuring and publishing content so that generative AI systems — ChatGPT, Perplexity, Google's AI Overviews, Claude — retrieve it, quote it accurately, and cite the source. Where classic SEO competes for a position in a list of ten blue links, GEO competes to be the passage an AI model lifts into its answer. The unit of success is not a ranking but an inclusion: was your sentence used, and was your brand named alongside it. Answer Engine Optimization (AEO) — Answer engine optimization (AEO) is the practice of structuring content so that systems which return a single direct answer — AI assistants, featured snippets, voice assistants, AI Overviews — return yours. It assumes the user will never see a list of results. There is one answer, and either it is drawn from your page or it is not, which makes AEO a binary outcome rather than a gradual climb up a ranking. AI Citation — An AI citation is an instance where an AI assistant attributes part of its generated answer to a specific source, usually as a linked reference. It is the AI-search equivalent of a ranking position and the primary success metric of generative engine optimization. Being cited is stricter than being mentioned: a mention names your brand, whereas a citation credits your page as the source of a claim and gives the reader a route to it. AI Visibility — AI visibility is the extent to which a brand, product or page appears in answers generated by AI assistants such as ChatGPT, Perplexity, Claude and Google's AI Overviews. It combines three things: how often you are mentioned across a defined set of queries, whether you are cited with a link, and how favourably you are characterised when you appear. Unlike search rankings, it is not reported anywhere — it exists only if you measure it. Structured Data for AI — Structured data for AI is schema markup — normally JSON-LD following the schema.org vocabulary — used to make a page's meaning explicit to machines, including the retrieval systems behind AI assistants. It states unambiguously what a page is and what its key facts are, so a model does not have to infer them from prose. It improves how reliably your content is parsed and repeated. It does not, by itself, make an assistant choose you. llms.txt — llms.txt is a proposed standard: a plain-text, markdown-formatted file placed at the root of a domain (at /llms.txt) that gives large language models a curated, human-written map of the site's most important content. It is a hand-picked index with short descriptions and links, designed to be read directly by a model rather than crawled. It is emphatically not a robots.txt for AI — it grants nothing and blocks nothing. Published by Ryze AI (get-ryze.ai).
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Ira Bodnar·

Glossary

The AI search glossary.

Plain definitions for the vocabulary that has grown up around AI search — GEO, AEO, llms.txt, citations, AI visibility and the structured data underneath all of it. Written for people running online stores, not for people selling courses about it.

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AI search has generated more terminology than it has generated proven tactics, and a lot of it is the same idea wearing three different names.

These definitions are here to make the vocabulary usable: what each term actually means, where the boundaries between them genuinely fall, and what — if anything — it changes about running an ecommerce site. Where a term is more marketing than mechanism, the entry says so.

Definitions

Generative Engine Optimization (GEO)

GEO

Generative engine optimization (GEO) is the practice of structuring and publishing content so that generative AI systems — ChatGPT, Perplexity, Google's AI Overviews, Claude — retrieve it, quote it accurately, and cite the source. Where classic SEO competes for a position in a list of ten blue links, GEO competes to be the passage an AI model lifts into its answer. The unit of success is not a ranking but an inclusion: was your sentence used, and was your brand named alongside it.

Read the full definition →

Answer Engine Optimization (AEO)

AEO

Answer engine optimization (AEO) is the practice of structuring content so that systems which return a single direct answer — AI assistants, featured snippets, voice assistants, AI Overviews — return yours. It assumes the user will never see a list of results. There is one answer, and either it is drawn from your page or it is not, which makes AEO a binary outcome rather than a gradual climb up a ranking.

Read the full definition →

AI Citation

AI source citation

An AI citation is an instance where an AI assistant attributes part of its generated answer to a specific source, usually as a linked reference. It is the AI-search equivalent of a ranking position and the primary success metric of generative engine optimization. Being cited is stricter than being mentioned: a mention names your brand, whereas a citation credits your page as the source of a claim and gives the reader a route to it.

Read the full definition →

AI Visibility

AI search visibility

AI visibility is the extent to which a brand, product or page appears in answers generated by AI assistants such as ChatGPT, Perplexity, Claude and Google's AI Overviews. It combines three things: how often you are mentioned across a defined set of queries, whether you are cited with a link, and how favourably you are characterised when you appear. Unlike search rankings, it is not reported anywhere — it exists only if you measure it.

Read the full definition →

Structured Data for AI

schema markup for AI

Structured data for AI is schema markup — normally JSON-LD following the schema.org vocabulary — used to make a page's meaning explicit to machines, including the retrieval systems behind AI assistants. It states unambiguously what a page is and what its key facts are, so a model does not have to infer them from prose. It improves how reliably your content is parsed and repeated. It does not, by itself, make an assistant choose you.

Read the full definition →

llms.txt

llms.txt file

llms.txt is a proposed standard: a plain-text, markdown-formatted file placed at the root of a domain (at /llms.txt) that gives large language models a curated, human-written map of the site's most important content. It is a hand-picked index with short descriptions and links, designed to be read directly by a model rather than crawled. It is emphatically not a robots.txt for AI — it grants nothing and blocks nothing.

Read the full definition →

Where this fits into ecommerce SEO

None of these terms describe a replacement for search engine optimisation. Generative answers are built from retrieved pages, and retrieval runs on the same index classic search uses, so a store that is slow, thinly linked or lacking topical authority will not be retrieved and therefore cannot be cited. The vocabulary here describes a layer of structural discipline on top of SEO that works, not an alternative to it.

If you are working out what to do rather than what to call it, our Shopify SEO services guide covers the programme, and our comparison of the best AI SEO tools for ecommerce brands covers the tooling.

A reasonable sequencing for a store: get structured data clean, build the answer layer beside your product pages, then start measuring citation share. Doing the third before the first two produces a dashboard with nothing in it.

Frequently asked questions

What is the difference between GEO, AEO and SEO?

SEO optimises for a position in a list of search results. AEO optimises to be the single direct answer a system returns when there is no list, such as a featured snippet or a voice result. GEO optimises to be a source that a generative model retrieves, quotes and cites while composing a new answer. They share almost all of their technical foundations — a page that cannot be indexed cannot be retrieved by any of them — but they differ in how content should be structured and in how success is measured.

Do these terms describe genuinely new work, or rebranded SEO?

Mostly the second, with a real new component. The crawlability, site speed, internal linking and topical authority that AI retrieval depends on are exactly the SEO fundamentals that already existed. What is genuinely new is the emphasis on extractability — writing self-contained, answer-first passages that survive being lifted out of the page — and the measurement problem, because no assistant reports how often it cited you.

Which of these should an ecommerce store work on first?

Structured data, because it is the cheapest to fix and everything else depends on machines parsing your catalogue correctly. After that, build the answer layer: pages that directly address the questions customers ask before buying, each opening with a complete answer rather than a preamble. Citation tracking comes last, once there is something worth tracking.

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GEO · AEO · citation tracking

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Last updated: Jul 18, 2026
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