GEO & AI Search Glossary

AI Search

The process of using artificial intelligence and large language models to search for and retrieve information. Unlike traditional search engines that return a list of links, AI search platforms provide direct answers, summaries, and conversational responses. Examples include ChatGPT with web browsing, Perplexity, and Google AI Overviews.

Brand Visibility Score

A metric that measures how frequently a brand is mentioned in AI-generated responses across various queries and platforms. Higher brand visibility indicates that AI models recognize and reference your brand more often when users ask relevant questions. This is a core KPI for GEO success.

Citation Rate

The frequency with which AI platforms cite your content as a source in their responses. High citation rates indicate that AI models consider your content authoritative and trustworthy. Citations typically include links to your website, driving referral traffic.

GEO (Generative Engine Optimization)

The practice of optimizing digital content and online presence to increase visibility in AI-generated responses from large language models and AI search platforms. GEO is the AI-era evolution of SEO, focusing on how AI models discover, understand, and cite content.

LLM (Large Language Model)

An artificial intelligence model trained on vast amounts of text data to understand and generate human-like text. Examples include GPT-4 (powers ChatGPT), Gemini, Claude, and others. LLMs are the technology behind most AI search platforms.

RAG (Retrieval-Augmented Generation)

A technique used by AI systems where they first retrieve relevant information from external sources (like the web) and then generate a response based on that retrieved information. This is how platforms like ChatGPT with web browsing and Perplexity work. RAG ensures responses are based on current, real-world data rather than just the model’s training data.

The percentage of AI mentions your brand receives compared to competitors within your industry or category. For example, if AI platforms mention your brand 30 times and competitors 70 times for relevant queries, your share of voice is 30%. This metric helps benchmark your AI visibility against the competition.

Prompt

A question or instruction given to an AI model by a user. In GEO, understanding common prompts in your industry helps you optimize content to appear in AI responses. For example, “What are the best running shoes for marathons?” is a prompt that running shoe brands want to rank for.

AI Overviews

Google’s AI-powered feature (formerly called SGE - Search Generative Experience) that appears at the top of search results. AI Overviews provide an AI-generated summary of the topic with cited sources, representing Google’s integration of generative AI into traditional search.

Topical Authority

The perceived expertise a brand or website has on a specific topic, as recognized by AI models. Building topical authority through comprehensive, high-quality content increases the likelihood of being cited by AI platforms as a trusted source.

Zero-Click Search

When a user gets their answer directly from an AI platform without clicking through to any website. This is increasingly common with AI search and represents both a challenge (reduced click-through traffic) and opportunity (brand visibility without requiring clicks).

Hallucination

When an AI model generates false or inaccurate information presented as fact. Hallucinations are a challenge in AI search. Strong GEO practices, like being cited as an authoritative source, help AI models provide accurate information about your brand.

E-E-A-T

Experience, Expertise, Authoritativeness, and Trustworthiness - Google’s quality framework that influences both traditional SEO and AI search visibility. AI models prioritize content demonstrating these qualities when selecting sources to cite. Strong E-E-A-T signals include author credentials, citations from reputable sources, and demonstrated expertise in your field.

Why it matters: Content with high E-E-A-T is significantly more likely to be cited by AI platforms as a trusted source.

Semantic Search

AI’s ability to understand the meaning and context behind queries beyond just matching keywords. Semantic search considers user intent, query context, and the relationships between concepts. This means content optimized only for specific keywords may miss visibility opportunities if it doesn’t address the underlying intent and related concepts.

Example: A query for “cold brew maker” might surface content about “iced coffee equipment” because AI understands the semantic relationship between these concepts.

Citation Velocity

The rate at which your citation frequency increases over time. High citation velocity indicates growing authority and visibility in AI search. Tracking citation velocity helps identify which content strategies are working and which topics are gaining traction with AI platforms.

Why it matters: Brands with positive citation velocity are building compounding authority, making future citations more likely.

Prompt Engineering

The practice of crafting effective prompts to achieve desired AI responses. In GEO, prompt engineering has two applications: (1) understanding how your target audience queries AI platforms, and (2) optimizing content to rank for those specific prompts.

Example: Understanding that users might ask “What’s the difference between X and Y?” vs “X vs Y comparison” vs “Should I choose X or Y?” - and optimizing content for all variations.

Content Clusters

Groups of related content pieces that work together to establish topical authority. A content cluster typically includes one comprehensive pillar page and multiple supporting articles that link back to it. AI models recognize these relationships and are more likely to cite brands with comprehensive coverage of a topic.

Example: A pillar page on “Email Marketing Strategy” linked to by articles on “Email Subject Lines,” “Email Automation,” “List Segmentation,” etc.

AI Crawler

Bots used by AI companies to discover and index web content for training and retrieval purposes. Major AI crawlers include GPTBot (OpenAI), GoogleBot-Google-Extended (Google Gemini), ClaudeBot (Anthropic), and PerplexityBot. Managing AI crawler access through robots.txt impacts which AI platforms can access your content.

Why it matters: Blocking AI crawlers prevents AI platforms from citing your content, while allowing them can increase visibility.

Context Window

The amount of information an AI model can process at once, measured in tokens. Larger context windows allow AI to analyze more content, understand broader context, and provide more comprehensive answers. Modern models have context windows ranging from 8,000 to over 1 million tokens.

Why it matters: AI with larger context windows can better understand long-form content and complex topics, making comprehensive content more valuable.