Reference
GEO Glossary
Every term you need to know about Generative Engine Optimization, AI visibility, and the metrics that drive brand presence in AI-generated answers.
21 terms defined. Each term has a direct link you can share (e.g. /geo-glossary#share-of-voice). New to GEO? Start with our introductory guide.
A
- AI Overviews
- Google's AI-generated summaries that appear at the top of search results for certain queries. Powered by Gemini, AI Overviews synthesize information from multiple sources to provide a direct answer before traditional organic results. They represent a major intersection of traditional SEO and GEO because they are displayed within Google Search but generated by an AI model.
- AI Visibility
- The extent to which a brand, product, or entity is represented in AI-generated outputs. AI visibility encompasses whether you are mentioned at all (presence), how prominently you are featured (position), and how accurately and positively the model describes you (quality). It is the foundational concept behind Generative Engine Optimization — you cannot optimize what you cannot see.
B
- Brand Sentiment (AI)
- A qualitative and quantitative measure of how positively or negatively an AI model portrays a brand in its generated responses. Unlike traditional sentiment analysis of social media posts or reviews, AI brand sentiment measures the model's own synthesized characterization of a brand — which can differ significantly from public opinion because of how training data is weighted and retrieved.
C
- Citation Source
- A URL or document that an AI model references when generating a response. Models like Perplexity and Google's AI Overviews display inline citations, allowing you to see exactly which web pages informed the answer. In GEO, tracking citation sources reveals which content assets the model trusts most, giving you a direct optimization target for improving your AI visibility.
- Comparison Prompt
- A user query that explicitly asks an AI model to compare two or more brands, products, or solutions. Examples include 'How does Notion compare to Confluence?' or 'What are the differences between HubSpot and Salesforce?' Comparison prompts are high-intent and directly influence purchase decisions, making them a critical category in any GEO prompt library.
D
- Daily Snapshot
- A timestamped record of an AI model's complete response to a specific prompt, captured on a regular cadence (typically daily). Snapshots create a historical log that lets you track exactly how AI responses about your brand change over time — after content updates, product launches, PR events, or model retraining. They are the raw data from which GEO metrics like visibility rate and share of voice are calculated.
- Discovery Prompt
- A user query that seeks to learn about available options in a category without naming specific brands. Examples include 'What are the best tools for email marketing?' or 'Which CRM should a small business use?' Discovery prompts represent the top of the AI-driven funnel and are where first-choice positioning is most valuable, because the user has not yet formed a preference.
F
- First-Choice Rate
- The percentage of AI responses where a brand is the first mentioned or explicitly recommended option. In AI-generated answers, the first recommendation carries disproportionate influence because users often anchor on it and treat it as the default choice. First-choice rate is one of the most competitively significant GEO metrics.
G
- Generative Engine Optimization (GEO)
- The practice of measuring, understanding, and improving how a brand appears in AI-generated responses across large language model platforms such as ChatGPT, Gemini, Claude, and Perplexity. GEO encompasses prompt tracking, visibility measurement, competitive analysis, citation monitoring, and content optimization — all focused on the AI response surface rather than the traditional search engine results page.
- Grounding
- The process by which an AI model anchors its generated response in verifiable external data rather than relying solely on its parametric knowledge (training data). Grounding typically involves retrieving real-time information from the web, a knowledge base, or a document index, then using that information to produce a more accurate and current answer. Grounded responses are generally more trustworthy and more likely to include citations.
L
- Large Language Model (LLM)
- A neural network trained on massive text datasets that can generate human-like text, answer questions, and perform reasoning tasks. Major LLMs include OpenAI's GPT series (powering ChatGPT), Google's Gemini, Anthropic's Claude, and Meta's LLaMA. In the context of GEO, LLMs are the 'engines' whose outputs you are optimizing for — the models that produce the AI-generated answers where your brand needs to appear.
P
- Presence Quality
- A composite measure of how well a brand is represented when it does appear in an AI response. Presence quality goes beyond binary visibility (mentioned vs. not mentioned) to evaluate accuracy of description, positivity of sentiment, completeness of feature coverage, and prominence of positioning. A brand can have high visibility but low presence quality if the model consistently describes it with outdated or incorrect information.
- Prompt Engineering
- The practice of designing, structuring, and refining input prompts to elicit specific or optimal outputs from an AI model. In the GEO context, prompt engineering has a dual meaning: (1) crafting the prompts in your tracking library to accurately simulate real user queries, and (2) understanding how prompt phrasing affects which brands the model recommends, so you can identify vulnerabilities in your visibility.
R
- Retrieval-Augmented Generation (RAG)
- An architecture pattern where an AI model retrieves relevant documents from an external knowledge source (such as a web index or database) before generating its response. RAG allows models to access information beyond their training cutoff, produce more accurate answers, and cite specific sources. RAG is the mechanism that makes your live web content directly relevant to GEO — if your content is retrievable and authoritative, RAG pipelines will use it to inform AI responses.
- Recommendation Position
- The ordinal position at which a brand appears within an AI-generated list or recommendation. If an AI model lists five CRM tools and your brand is third, your recommendation position is 3. Like traditional search rankings, earlier positions receive more attention and carry more implicit endorsement from the model. Tracking recommendation position over time reveals whether your brand is gaining or losing competitive ground.
- Response Hash
- A unique fingerprint (cryptographic hash) of an AI model's response to a specific prompt at a specific point in time. Response hashes are used to detect when an AI model's answer has changed — even subtly — between snapshots. If the hash changes, the content changed, triggering a detailed diff analysis to identify what shifted in the model's representation of your brand or competitors.
S
T
- Trust Tier
- An informal ranking of content sources based on the level of authority an AI model assigns to them during retrieval and generation. Top-tier sources (major publications, academic papers, official documentation) are more frequently cited and more heavily weighted in AI responses than lower-tier sources (personal blogs, thin affiliate sites, outdated pages). Understanding trust tiers helps GEO practitioners prioritize where to build brand presence.
- Trust Validation Prompt
- A user query that asks an AI model to evaluate the reliability, reputation, or legitimacy of a specific brand or product. Examples include 'Is Stripe safe for payment processing?' or 'Can I trust monday.com for enterprise project management?' Trust validation prompts are critical in the consideration phase of the buyer journey, and poor AI responses to these prompts can derail conversions even when your discovery visibility is strong.
V
- Visibility Rate
- The percentage of tracked prompts where a brand is mentioned in the AI model's response. Calculated as (number of responses containing your brand / total number of tracked prompts) * 100. Visibility rate is the most fundamental GEO metric — it answers the binary question of whether you are showing up at all. A brand with a 60% visibility rate appears in 60 out of every 100 tracked AI responses.
W
- Web Search Grounding
- A specific form of grounding where an AI model performs a real-time web search (typically via a search API like Google or Bing) and uses the results to supplement or verify its response. Web search grounding is the bridge between traditional SEO and GEO: pages that rank well in web search are more likely to be retrieved, cited, and used as evidence in AI-generated answers. This means your SEO investment directly supports your GEO outcomes.
Related Resources
- What is Generative Engine Optimization (GEO)? — A comprehensive introduction to GEO
- GEO vs SEO: What's the Difference? — Side-by-side comparison of both disciplines
Put these terms into practice
Velova measures every metric in this glossary across ChatGPT, Gemini, Claude, and Perplexity — automatically, every day.