GEO, AEO, and AI Search Glossary

New to AI search optimization? This glossary covers the key terms you'll encounter in AI Rankia and the industry.

Core concepts

GEO (Generative Engine Optimization) — the practice of optimizing your content to appear in AI-generated search results. The AI-era equivalent of SEO. Instead of ranking in a list of 10 blue links, you're optimizing to be mentioned or cited when AI generates an answer.

AEO (Answer Engine Optimization) — often used interchangeably with GEO. Some practitioners distinguish AEO as focused on featured snippets and direct answers, while GEO covers the broader AI search landscape.

AI Search — any search experience powered by a large language model. Includes ChatGPT's web search, Perplexity, Google AI Overviews, Google AI Mode, Gemini, Claude, and others.

LLM (Large Language Model) — the AI model that generates responses. Examples: GPT-5, Claude, Gemini, Llama 4, DeepSeek. These models power AI search engines.

Visibility metrics

Brand mention — when an AI model includes your brand name in its generated response to a query.

Citation — when an AI model references a URL from your website as a source for its response. Citations can drive referral traffic.

Share of Voice — the percentage of AI responses in your space that mention your brand vs. competitors. The primary competitive metric in AI search.

Query Fan-Out — the process where an AI decomposes a single user query into 8-12 sub-queries to gather comprehensive information before generating a response. Understanding fan-out is critical for content strategy.

AI search engines

Google AI Overviews — AI-generated summaries that appear at the top of Google search results for ~44% of queries. Previously called SGE (Search Generative Experience).

Google AI Mode — Google's dedicated AI search experience where the entire results page is AI-generated, including product cards and local business listings.

Perplexity — an AI-first search engine that always cites its sources with direct links.

Native models — AI models that have their own web search capability (GPT 5 Search, Perplexity, Gemini Search). They simulate what real users experience.

Non-native models — AI models accessed via API without web search (DeepSeek, Llama, Qwen). They respond from training data only.

Technical terms

Schema markup — structured data (JSON-LD format) added to your HTML that helps search engines and AI models understand your content. Uses vocabulary from Schema.org.

llms.txt — a text file at your website's root (like robots.txt) that provides AI models with a summary of your site structure and content. An emerging standard.

robots.txt — a file that tells web crawlers which pages they can access. Important for AI search because blocking AI crawlers (GPTBot, ClaudeBot, PerplexityBot) prevents those models from citing your content.

E-E-A-T — Experience, Expertise, Authoritativeness, Trustworthiness. Google's quality framework that AI models also use to evaluate which sources to cite.

AI Rankia-specific terms

Explorer mode — monitoring using native AI models with web search capability. Produces the most realistic results.

Voyager mode — monitoring using non-native AI models via API. Useful for understanding how LLMs respond from training data.

Credits — the currency powering all AI Rankia tools. Each action costs a specific number of credits based on complexity.

Scheduled prompts — prompts set up for recurring automated monitoring (weekly or daily).