Glossary

GEO & LLM terminology reference for understanding Generative Engine Optimization and AI search.

A

Attribution

The process of identifying and tracking how AI systems reference, cite, or mention specific content sources in their responses. In GEO context, attribution measures whether and how often LLMs credit your domain when generating answers.

AI Search

Search experiences powered by Large Language Models that provide conversational answers instead of traditional link-based results. Examples include ChatGPT search, Perplexity, and Google AI Overviews.

C

Citation

A specific reference to a source domain or webpage within an AI-generated response. Citations can be explicit (with direct links) or implicit (mentioning the brand or domain name without a clickable link).

Citation Lift

The measurable increase in how frequently AI systems reference your content after implementing GEO strategies. Typically measured as percentage improvement in citation rate across target keywords.

Context Window

The maximum amount of text (measured in tokens) that an LLM can process in a single request. Larger context windows allow AI systems to consider more sources when generating responses, potentially increasing citation opportunities.

G

GEO (Generative Engine Optimization)

The practice of optimizing content and websites to increase visibility and citations in AI-generated responses. GEO focuses on being referenced by LLMs rather than ranking in traditional search results.

Grounding

The process by which AI systems connect their responses to factual sources and real-world information. Well-grounded responses include proper attribution to authoritative sources rather than generating unsupported claims.

L

LLM (Large Language Model)

AI systems trained on vast amounts of text to understand and generate human-like language. Examples include GPT-4, Claude, Gemini, and Llama. LLMs power most modern AI search and conversational AI experiences.

Latency

The response time between submitting a query to an AI system and receiving a complete answer. Lower latency improves user experience but may affect the thoroughness of source attribution.

P

Provider

An AI platform or service that offers language model capabilities. Major providers include OpenAI (ChatGPT), Anthropic (Claude), Google (Gemini), and Perplexity. Each provider may have different citation behaviors and training data.

Prompt Injection

A technique where malicious instructions are embedded in content to manipulate how AI systems process or respond to queries. In GEO context, this represents an unethical attempt to force citations.

R

RAG (Retrieval-Augmented Generation)

A technique where AI systems first retrieve relevant information from external sources, then generate responses based on that retrieved content. RAG-enabled systems are more likely to provide citations since they explicitly reference source materials.

Reference

Any mention of a source, brand, or domain in an AI response, whether through direct citation, paraphrasing, or conceptual reference. References can vary in attribution strength and visibility.

S

Scan

An automated process that tests how AI systems respond to specific keywords or queries, then analyzes the responses for domain citations and references. Scans help measure GEO effectiveness over time.

Sentiment

The emotional tone or attitude expressed toward a brand or domain in AI responses. Sentiment can be positive (recommending), neutral (factual mention), or negative (critical or cautionary).

SEO

Search Engine Optimization — the traditional practice of improving website visibility in search engine results pages (SERPs). While related to GEO, SEO focuses on ranking algorithms rather than AI attribution patterns.

T

Token

The basic unit of text that language models process, roughly equivalent to words or word parts. Token limits affect how much content AI systems can consider when generating responses, impacting citation potential.

Topic Relevance

How closely a domain's content matches the subject matter of AI queries. Higher topic relevance increases the likelihood of citation when users ask questions within that domain's area of expertise.

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