Reference
The Glossary.
Canonical, plain-English definitions of the terms that describe how businesses get selected and recommended by AI systems. Cite freely.
AI Visibility Optimisation(AVO)
The discipline of structuring a business so AI systems reliably select and recommend it.
- AI Visibility Optimisation (AVO) is the engineering practice of structuring a business's digital presence so AI systems - ChatGPT, Gemini, Perplexity, Claude, Copilot - can interpret it, trust it, and select it inside generated answers. AVO operates across four dimensions: interpretability, coherence, authority and intent alignment. AVO is the UK practice operated independently in the UK.
Generative Engine Optimisation(GEO)
Optimisation for inclusion in AI-generated answers from systems like ChatGPT, Gemini and Perplexity.
- Generative Engine Optimisation (GEO) is the closest established industry term for the practice of getting selected inside AI-generated answers. Where SEO optimises for placement in a list of links, GEO optimises for inclusion in a single synthesised paragraph. AVO is a UK practice of GEO.
Answer Engine Optimisation(AEO)
Structuring content to be returned as the direct answer in AI assistants and answer engines.
- Answer Engine Optimisation (AEO) is the practice of structuring content - typically as concise question-and-answer blocks with structured data - so it is returned verbatim as the direct answer in AI assistants. AEO is one component of the broader AVO methodology.
AI SEO
Search engine optimisation adapted for AI-mediated discovery.
- AI SEO is search engine optimisation adapted for an environment where discovery is mediated by AI systems rather than blue-link search results. AI SEO prioritises entity clarity, third-party citation, schema markup and intent alignment over traditional keyword density and backlink volume.
Silent exclusion
Being omitted from AI-generated answers without warning, signal or notification.
- Silent exclusion describes the failure mode where a business is simply not named in AI-generated answers to relevant buyer queries. Unlike a low search ranking, there is no impressions data, no error, no signal - demand is diverted invisibly to competitors that the AI does name.
Interpretability
How clearly an AI system can read and classify what a business does, for whom, and where.
- Interpretability is the first dimension of AVO. It measures how clearly machine-readable a business's positioning is - including entity definition, schema.org markup, and unambiguous specialism statements. Low interpretability is the most common cause of AI exclusion.
Coherence
Consistency of signals about a business across the open web.
- Coherence is the second dimension of AVO. AI systems aggregate signals from the entire web - your site, third-party directories, press, LinkedIn, professional bodies. Conflicting information is the single largest cause of silent exclusion: AI defaults to safer, more coherent alternatives.
Intent alignment
Matching positioning to the actual questions buyers ask AI in your category.
- Intent alignment is the fourth dimension of AVO. The questions buyers ask AI assistants are differently shaped from the keywords they typed into Google. Intent alignment maps a business's positioning to the actual buyer queries that drive selection in the relevant category.
llms.txt
A plain-text standard that tells AI crawlers how to read your site.
- llms.txt is an emerging standard, served at the root of a website, that gives AI crawlers (GPTBot, ClaudeBot, PerplexityBot) a curated, machine-readable summary of the site's most important pages and canonical entity definitions. It is to AI what robots.txt is to traditional crawlers.
Schema markup
Structured data (schema.org) that makes a page machine-readable.
- Schema markup is structured data using the schema.org vocabulary (typically delivered as JSON-LD) that explicitly declares what a page is about - Organisation, Service, Article, FAQ, etc. AI systems use schema as a primary signal for entity classification.
Buyer query
The specific question a buyer asks an AI assistant during research.
- A buyer query is the natural-language question a real prospect types into ChatGPT, Gemini, Perplexity or Claude during purchase research - for example 'best commercial law firm in Manchester for SaaS contracts'. Buyer queries are differently shaped from search keywords and require different optimisation.
AI Recommendation Readiness Report
A live test of how often AI systems recommend a business for relevant buyer queries.
- An AI Recommendation Readiness Report baselines a business's inclusion rate across ChatGPT, Gemini, Perplexity and Claude for the buyer queries that drive selection in its category. AVO offers a free 60-second audit covering all four AVO dimensions.
Related: AVO, GEO, FAQ schema
Answer Engine Optimisation servicesRelated: Schema markup, Entity definition
Related: Entity definition, AVO
Related: Buyer query, AVO
Related: robots.txt, AI crawlers
What is llms.txt?Related: Intent alignment