SEO and GEO
How to position your brand in Google AND in generative AI (ChatGPT, Claude, Gemini). The lexicon of hybrid visibility for the next ten years.
- AEO (Answer Engine Optimization)AEO (Answer Engine Optimization) is a sub-discipline of GEO, focused on producing direct answers to user questions. It targets answer engines (Google AI Overviews, ChatGPT, Perplexity) that require a concise, sourced response, restituable as is, rather than a page to browse.
- CitabilityCitability is the property of a piece of content of being extracted, restituted, and attributed as is by an AI engine in its response to a user. It is built through writing (self-contained sentences), markup (Schema.org), and topical authority (consistency and editorial density on a domain). It is the central objective of GEO.
- Conversational indexingConversational indexing is the process by which AI engines build their responses from web content: ingestion at training (dated corpus), retrieval at inference (RAG via web search), or both combined. It replaces the keyword indexing of classic engines with indexing by questions and intentions.
- Generative referenceA generative reference is the mention of a source in an AI engine's response to a user: textual citation, explicit attribution, or hyperlink to the original content. It progressively replaces the classic organic link as a signal of editorial and brand visibility on the web.
- GEO (Generative Engine Optimization)GEO (Generative Engine Optimization) is the set of practices aimed at making content identifiable, trustworthy, and citable by generative answer engines (ChatGPT, Claude, Perplexity, Gemini, Google AI Overviews). It succeeds traditional SEO when users seek answers, not links.
- llms.txtllms.txt is a proposed web standard introduced in September 2024 by Answer.AI, providing AI models with a structured map of a website's content. Placed at the root of the domain, it is not a formal standard and its adoption by major LLMs remains uneven in 2026.
- Schema.org for AISchema.org is a standard structured semantic markup vocabulary (most often JSON-LD) that AI engines use to understand the nature of a web page: defined term, FAQ, article, product, event. Properly implemented, it multiplies by two to four the probability of being cited by generative answer engines.