Definitions for the optimization vocabulary across classic, answer, and generative search engines. A citable index with semantic relations and structured markup, built for indexing in ChatGPT, Perplexity, Claude, and Google AI Overviews.
| Acronym | Full name | Short definition | Relation |
|---|---|---|---|
| SEO | Search Engine Optimization | Optimization for classic search engines (Google, Bing). | Root term |
| AEO | Answer Engine Optimization | Optimization for engines that answer directly. | Separate branch off SEO |
| VSO | Voice Search Optimization | AEO subset, voice assistants only. | Subset of AEO |
| GEO | Generative Engine Optimization | Optimization for generative engines (ChatGPT, Perplexity, Claude, AI Overviews). | New branch, parallel to AEO |
| LLMO | LLM Optimization | Technical synonym for GEO. | Synonym of GEO |
| AIO | AI Optimization | Marketing synonym for GEO. | Synonym of GEO |
| SGE Optimization | Search Generative Experience Optimization | GEO subset for Google AI Overviews. | Subset of GEO |
| GAIO | Generative AI Optimization | Rare variant of GEO. | Rare synonym of GEO |
Optimization for classic search engines (Google, Bing) with the goal of appearing in the list of results. Built around indexing, ranking, and query-triggered relevance.
Optimization for engines that answer questions directly — Google featured snippets, voice assistants (Alexa, Siri, Google Assistant), Bing Answers. The answer comes from a single source with attribution preserved.
Subset of AEO targeting voice assistants exclusively (Alexa, Siri, Google Assistant). Specific requirements: conversational long-tail, strong local SEO, complete structured data.
Optimization for generative engines that synthesize answers from multiple sources — ChatGPT, Perplexity, Claude, and Google AI Overviews. Unlike classic SEO, which targets ranking in the result list, GEO targets presence in the answers produced by large language models.
Technical synonym for GEO, with emphasis on optimizing for large language models. Used mostly by developers and ML teams.
Subset of GEO that targets Google AI Overviews specifically (formerly Search Generative Experience). Tactics revolve around integration with classic organic results and E-E-A-T criteria.
GEO (Generative Engine Optimization) is the practice of optimizing content to be cited and synthesized by generative engines such as ChatGPT, Perplexity, Claude, and Google AI Overviews. Unlike classic SEO, which targets ranking in the result list, GEO targets presence in answers produced by large language models.
AEO (Answer Engine Optimization) targets engines that extract a direct answer from a single source (Google featured snippets, voice assistants). GEO (Generative Engine Optimization) targets engines that synthesize answers from multiple sources using language models (ChatGPT, Claude, Perplexity, Google AI Overviews). AEO preserves attribution to the source; GEO assumes the LLM rewrites the content.
Yes — GEO (Generative Engine Optimization) and LLMO (LLM Optimization) are practically synonyms. GEO is the dominant academic term, formalized in a Princeton / Georgia Tech paper in 2023. LLMO is a technical variant used more often by developers. Other synonyms include AIO (AI Optimization) and GAIO (Generative AI Optimization).
Yes. Classic SEO remains the foundation: generative engines read, for the most part, the same pages Google indexes. A modern strategy combines SEO (technical foundation and authority), AEO (direct-answer structure), and GEO (semantic citability for LLMs).
Sources: Princeton / Georgia Tech paper (2023), Google AI Overviews documentation, Websem field notes 2025–2026.
We build complete implementations for companies that want to appear in answers from generative engines.