- Generative Engine Optimization (GEO)
- The practice of getting a brand mentioned and cited by generative AI engines like ChatGPT, Claude, Gemini and Perplexity when people ask them questions. Where SEO targets a ranked list of links, GEO targets the answer itself.
- Answer Engine Optimization (AEO)
- Optimizing content so answer engines (AI assistants and AI search) surface it directly as the answer. Closely related to GEO, with more emphasis on clear, extractable, question-shaped content.
- AI 可见度
- How often, and how prominently, a brand shows up when AI engines answer questions in its category. It combines whether the brand is named, whether its own site is cited, and how central it is to the answer.
- 回答占有率
- A brand's portion of the AI answer for a given question, relative to competitors. If an engine names five companies for "best X" and you are one of them, your share of answer is roughly one fifth, weighted by prominence.
- AI citation
- A reference an AI engine makes to a specific source, usually a link or a named publication, to support part of its answer. Earning citations from sources the engines trust is how a brand becomes part of the answer.
- Answer engine
- A tool that responds to a question with a synthesized answer rather than a list of links. ChatGPT, Claude, Gemini, Perplexity and AI Overviews in Google are answer engines.
- Retrieval-augmented generation (RAG)
- A technique where an AI model retrieves relevant documents at question time and grounds its answer in them. It is why fresh, well-structured, crawlable content can be cited even if it was not in the model's training data.
- llms.txt
- A plain-text file at a site's root that gives AI systems a concise, structured guide to the site, like a sitemap written for language models. Cites X publishes one at /llms.txt.
- Hallucination
- When an AI engine states something false or invents a source. Strong, consistent, well-cited information about a brand reduces the chance an engine gets its facts wrong.
