Working in GEO means colliding with SEO jargon, AI terminology and product slang all at once. Here are 30 core terms, one line each, bilingual — for aligning your own team, and you are welcome to cite it.
Fundamentals
- GEO (Generative Engine Optimization / 生成式引擎优化) — the practice of getting a brand accurately mentioned, recommended and cited inside generative AI engines' answers. See What is GEO.
- AEO (Answer Engine Optimization / 答案引擎优化) — GEO's near-synonym with earlier roots (the featured-snippet and voice-assistant era); in practice the two overlap almost entirely.
- SEO (Search Engine Optimization / 搜索引擎优化) — the thirty-year-old discipline of ranking on results pages; GEO's foundation, not its rival.
- AI visibility (AI 可见度) — the degree to which a brand is mentioned, recommended and cited in AI answers; can be normalized into a score and tracked over time.
- Generative engine (生成式引擎) — an AI system that retrieves from the web, synthesizes multiple sources and generates a natural-language answer; the academic term for ChatGPT-class systems.
- Answer engine (答案引擎) — a retrieval system that returns an answer rather than a list of links; the predecessor and synonym of the generative engine.
- AI-native search (AI 原生搜索) — search products whose core interaction is an AI-generated answer (e.g. Metaso, Perplexity).
- Zero-click (零点击) — the user gets what they need inside the answer and clicks nothing; the default shape of brand exposure in the GEO era.
Engines and crawling
- LLM (large language model / 大语言模型) — the model underneath a generative engine. A model is not a product entrance: the same model can power many products.
- RAG (retrieval-augmented generation / 检索增强生成) — retrieve first, then answer from the retrieved material; it makes "being retrievable" the precondition of "being mentioned".
- Web-connected retrieval (联网检索) — an engine's ability to fetch live web pages; behaviour varies enormously between engines.
- AI crawler (AI 爬虫) — the bots AI vendors use to fetch web pages (GPTBot, ClaudeBot and friends); whether robots.txt lets them in directly affects whether you can appear in answers.
- llms.txt — a convention for a site-description file at the web root, aimed at AI engines, so one fetch explains what the site is (ours is at /llms.txt).
- Knowledge cutoff (知识截止) — the time boundary of a model's training corpus; brands and facts newer than it can only enter answers via web retrieval.
- Hallucination (幻觉) — a model generating false information; brands should monitor not just "were we mentioned" but "what was said wrongly".
- MCP (Model Context Protocol / 模型上下文协议) — an open protocol that lets AI agents call external tools and data in a standard way (our MCP endpoint is documented on the developers page).
Measurement and metrics
- Monitoring prompt (监测问题) — a fixed set of questions sent to engines repeatedly under a fixed methodology; the basic unit of continuous measurement.
- Mention (提及) — the brand name (including aliases) appears in the answer body. Our detection is tone-neutral — a mention is a mention.
- Citation (引用) — a reference link attached to an answer; counted per domain, it reveals "who the AI considers authoritative".
- Mention rate (提及率) — the share of monitoring prompts in which the brand is mentioned; normalized, it becomes the engine sub-score.
- Recommendation rank (推荐位次) — the brand's position in an answer's recommendation list; first and fifth are both "mentions", with very different value.
- Sample size (样本量) — the number of samples behind a score; flagging "not enough data" honestly beats faking precision (our rules: how we score).
- Score version (评分版本) — the version number of the scoring methodology; historical batches keep their version tag so trends compare like with like.
Content and strategy
- Pillar content (支柱内容) — a deep, systematic answer to one core question; a high-frequency citation source type for AI answers.
- Structured data (结构化数据) — Schema.org markup (Organization, FAQPage, Article…) that makes a page machine-readable to engines.
- Authoritative source (权威来源) — the third parties engines prefer to cite: media, Q&A communities, industry lists; China and the West run two separate ecosystems (see our observations).
- Brand alias (品牌别名) — every name a brand goes by: local and English names, product names, nicknames. Monitoring without an alias table systematically understates visibility.
- White-hat GEO (白帽 GEO) — improving visibility only through public, sustainable means: content, structure, authority building, continuous measurement.
- Prompt injection (提示注入) — hiding instructions in web pages to manipulate AI answers — a black-hat tactic. We don't do it and don't recommend it: engine vendors will claw it back.
- Bilingual content assets (双语内容资产) — content estates built separately for the Chinese and Western sides; translation is not localization, because the two citation ecosystems differ.