Reference definitions of the key terms in modern search and AI visibility.
The umbrella discipline of optimising a website to be surfaced, summarised, and cited by generative AI systems including ChatGPT, Claude, Perplexity, Gemini, Google AI Overviews, and Bing Copilot. GEO combines two closely related practices, AEO (answer-engine extraction) and LLMO (large-language-model citation), and is the term used most often in academic and industry literature for the broader category. In CiteFlow audits, GEO is reported as a synthesised score derived equally from the AEO and LLMO pillars.
A component of GEO focused on structuring content so that answer engines extract and present it as a direct response to user queries. Targets visibility in AI Overviews, featured snippets, and conversational AI assistants rather than traditional ranked search results.
A component of GEO focused on writing and structuring content to maximise the likelihood of being cited by large language models including ChatGPT, Claude, Perplexity, and Gemini. Covers content formatting, entity signals, schema markup, and citation graph position.
The synthesised answer block Google displays at the top of certain search results, generated by Gemini. AI Overviews draw on multiple web sources and cite the ones used. Visibility in AI Overviews is one of the primary goals of AEO and LLMO work.
A search or conversational system that returns a direct synthesised answer rather than a list of links. Includes Google AI Overviews, Bing Copilot, ChatGPT search, Claude, Perplexity, and Gemini.
A measure of how often a given domain or piece of content is cited by AI engines relative to its competitors. Functions as the AI-era equivalent of share of search visibility.
A plain text file placed at the root of a domain providing structured information about the site's content for large language model crawlers. Acts as a table of contents for AI systems.
A Schema.org structured data type that explicitly identifies question-and-answer content on a web page. One of the most reliably extracted formats by both traditional search and AI assistants.
A distinct, identifiable thing (person, organisation, place, concept, or product) recognised by search engines and AI systems. Entity-rich content uses named entities consistently and is easier for AI to interpret and cite.
Search that interprets meaning rather than matching keywords. Modern search engines and all AI assistants use semantic search, which means content benefits from clear meaning and entity relationships rather than keyword density.
A structured representation of entities and the relationships between them, used by search engines and AI systems to understand the world. Google's Knowledge Graph and equivalents in other systems determine which entities are recognised as authoritative.
A summary answer Google displays at the top of search results, extracted directly from a web page. Featured snippets pre-date AI Overviews and remain a significant driver of traffic.
Structured data added to web pages, typically in JSON-LD format, that tells search engines and AI systems what the content is and means. Schema.org defines the standard vocabulary.
The practice of generating large numbers of pages through templates and data, typically targeting many low-competition keywords at scale. Effective when paired with quality controls; risky when used to create thin content.
A group of related content pieces organised around a central theme, internally linked to establish topical authority. A primary structural approach for both traditional SEO and AEO.
