AI Visibility Glossary
36+ terms and definitions to help you understand AI brand monitoring.
AI Search
The practice of using AI assistants like ChatGPT, Claude, or Gemini to find information and recommendations instead of traditional search engines.
AI Visibility Score
A metric (0-100) measuring how often and prominently your brand appears in AI assistant responses when users ask relevant questions.
Answer Engine
An AI system that provides direct answers to user queries rather than a list of links. Examples include ChatGPT, Perplexity, and Google AI Overviews.
Brand Perception
How AI models understand and describe your brand based on their training data. This includes sentiment, positioning, and key attributes.
Brand Sentiment
The overall positive, negative, or neutral tone that AI assistants use when discussing your brand.
ChatGPT
OpenAI's conversational AI assistant, one of the most widely used AI platforms. A primary target for AI visibility optimization.
Citation Source
A website or document that AI assistants reference when making recommendations. Being a citation source increases brand visibility.
Claude
An AI assistant developed by Anthropic, known for its helpful, harmless, and honest approach. One of the major platforms tracked for brand visibility.
Competitor Ranking
Your brand's position relative to competitors when AI assistants are asked for recommendations in your category.
Competitor Tracking
Monitoring how your competitors appear in AI responses compared to your own brand, including position, sentiment, and mention frequency.
Content Gap
Information about your brand that AI models lack or get wrong. Identifying and filling content gaps improves AI visibility.
Embedding
A numerical representation of text that AI models use to understand meaning and relationships between concepts.
Gemini
Google's AI assistant (formerly Bard), integrated into Google products. Important for brands targeting Google ecosystem users.
Generative Search
Search experiences powered by AI that generate synthesized answers rather than returning links. Examples include Perplexity and Google SGE.
GEO (Generative Engine Optimization)
The practice of optimizing content and brand presence to appear prominently in AI-generated responses. Similar to SEO but for AI assistants.
Hallucination
When an AI generates false or inaccurate information about your brand. Monitoring for hallucinations is crucial for brand protection.
Knowledge Cutoff
The date after which an AI model has no training data. Information published after this date may not be reflected in AI responses.
Knowledge Gap
Specific information about your brand that AI models don't know or understand. Filling knowledge gaps is key to improving AI visibility.
Knowledge Graph
A structured database of facts and relationships that AI models use to understand entities like brands, products, and people.
LLM (Large Language Model)
The AI technology behind assistants like ChatGPT, Claude, and Gemini. LLMs are trained on vast text data and generate human-like responses.
LLM Ranking
Where your brand appears in the order of recommendations provided by AI assistants. Higher rankings lead to more visibility and traffic.
LLMO (LLM Optimization)
Strategies and tactics to improve how your brand appears in Large Language Model responses. Similar to GEO.
Mention Frequency
How often your brand is mentioned in AI responses across different queries. A key metric for overall AI visibility.
Multi-Platform Analysis
Analyzing your brand's presence across multiple AI platforms (ChatGPT, Claude, Gemini) to understand platform-specific differences.
Perplexity
An AI-powered search engine that provides sourced answers. Often used for real-time information and brand research.
Platform Comparison
Comparing how different AI platforms (ChatGPT vs Claude vs Gemini) perceive and recommend your brand differently.
Prompt Engineering
The practice of crafting effective queries to get specific information from AI assistants. Used in brand monitoring to test various scenarios.
RAG (Retrieval-Augmented Generation)
A technique where AI models retrieve real-time information before generating responses, improving accuracy and timeliness.
Real-time Data
Current, up-to-date information that AI can access (vs. static training data). Important for brands with frequently changing information.
Recommendation Rate
The percentage of relevant queries where an AI assistant recommends your brand. A key conversion metric for AI visibility.
Semantic Search
Search that understands meaning and context rather than just matching keywords. How AI assistants find relevant information.
Sentiment Analysis
Analyzing the emotional tone (positive, negative, neutral) of AI responses about your brand.
Source Visibility
How often your website or content is cited as a source in AI responses. Higher source visibility builds credibility.
Training Data
The text and information used to train AI models. Your brand's representation in training data affects how AI perceives you.
Vector Database
A database storing embeddings that enables semantic search and retrieval for AI applications.
Visibility Trend
How your AI visibility score changes over time. Tracking trends helps measure the impact of optimization efforts.
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