AI-Suche

GEO is the discipline of shaping content for visibility in AI answer engines — AI Overviews, Perplexity, ChatGPT Search, Claude. The goal is not the classic SERP click, but appearing as a cited source inside the generated answer.

Answer Engine Optimization (AEO) is optimising content so it is delivered as a direct answer — in featured snippets, voice assistants and AI answers. Rather than just ranking pages, the content itself should become the answer.

ChatGPT Search is OpenAI's web search integrated into ChatGPT, synthesizing answers from real-time web sources. Conversational search instead of a link list — directly in the ChatGPT interface.

Perplexity is an AI-based answer engine that synthesizes web search results with a language model and delivers answers with inline source citations — an alternative to Google, focused on conversational research.

Google's AI-generated SERP answers. SGE was the beta name (2023), AI Overviews the production name (May 2024), AI Mode the dedicated chat tab (2025).

AI Optimization (AIO) is the umbrella term for measures that increase the visibility of content in AI-powered answer systems. AIO encompasses variants such as GEO (Generative Engine Optimization) and AEO (Answer Engine Optimization).

Brand mentions are references to a brand on third-party sites — even without a link. For AI visibility (GEO) they count as a strong signal: language models learn from frequent, credible mentions that a brand is a known entity.

Citation optimization covers measures that deliberately shape content so it appears as a cited source in AI answers — for instance in Perplexity or Google AI Overviews. The goal is the numbered citation, not the classic ranking.

Entity SEO establishes a brand, person or topic as an unambiguous entity in knowledge graphs such as Google's Knowledge Graph. The goal is for search and AI systems to identify, classify and connect the entity with facts reliably.

llms.txt is a proposed text file in a website's root directory meant to give AI models and LLM crawlers curated, important content in a simple form. As of 2026 it is an unofficial proposal with low practical adoption.

RAG-friendly content is structured so AI systems can easily split it into meaningful sections, extract individual passages and cite them correctly. Clear structure, unambiguous statements and self-contained sections raise the chance of appearing in AI answers.

OpenAI's search-engine prototype, originally launched as a standalone product — now largely folded into ChatGPT Search. Delivers AI-generated answers with source citations.

Share of model is a metric that measures how often a brand is mentioned in the answers of AI language models, relative to the mentions of all competitors in the same category. It is considered the AI counterpart to the classic share of voice.

Structured data for LLMs are machine-readable annotations (usually Schema.org as JSON-LD) that describe content explicitly — author, date, entity, rating. This lets AI systems classify, summarise and cite the content more reliably.