Glossary
Definitive reference for AI visibility concepts
Zero-Click AI: When Users Never Visit Your Website
Zero-click AI responses give users complete answers without needing to visit your website. Learn the implications and how to adapt.
Content Velocity for AI: How Publishing Frequency Affects LLM Awareness
Content velocity measures how frequently you publish new content and how it affects your AI visibility.
Brand Safety in AI: Managing Misinformation and Hallucinations
AI models can generate inaccurate information about your brand. Learn how to monitor and manage brand safety risks.
AI Crawler Optimization: Helping AI Bots Index Your Content
AI crawlers index content for language models. Learn how to optimize your site for GPTBot, ClaudeBot, and other AI bots.
Retrieval-Augmented Generation (RAG): What Marketers Need to Know
RAG combines AI generation with real-time information retrieval. Learn how it works and why it matters for your AI visibility strategy.
Knowledge Graph and AI: How Structured Knowledge Feeds LLMs
Knowledge graphs are structured databases of facts that AI models rely on. Learn how they influence what LLMs know about your brand.
AI Visibility Score: How to Measure and Benchmark Your Performance
The AI visibility score is a composite metric measuring your brand's presence across AI models.
Multi-Pass Verification: Getting Reliable AI Visibility Data
Multi-pass verification queries AI models multiple times to account for response variability and produce reliable data.
Citation Gap Analysis: Finding Where Competitors Outperform You in AI
Citation gap analysis identifies prompts where competitors are cited by AI models but you are not.
AI Sentiment Analysis: Understanding How LLMs Describe Your Brand
AI sentiment analysis reveals whether AI models describe your brand positively, neutrally, or negatively.
Prompt-Keyword Mapping: Connecting Search Intent to AI Queries
Prompt-keyword mapping bridges traditional keyword research and AI prompt optimization.
AI Content Attribution: How LLMs Decide What to Credit
Understand the mechanisms AI models use to attribute content and how to increase your brand's attribution rate.
E-E-A-T for AI: How Experience, Expertise, Authority, and Trust Apply to LLMs
Google's E-E-A-T framework applies to AI visibility too. Learn how these signals influence what LLMs say about your brand.
Structured Data for AI: Schema Markup That LLMs Actually Use
Learn which structured data and schema markup help AI models understand and cite your content.
AI Readiness: How to Audit Your Website for LLM Compatibility
AI readiness measures how well your website is prepared for AI crawlers and language models.
llms.txt: The New Standard for AI Crawlability
llms.txt is an emerging standard that helps AI models understand and properly crawl your website.
AI Search vs Traditional Search: How Discovery Is Changing
Compare AI search and traditional search to understand how information discovery is evolving and how to optimize for both.
What Is an LLM? A Marketer's Guide to Large Language Models
A marketer-friendly explanation of what large language models (LLMs) are, how they work, and why they matter for brand visibility.
AI Brand Mentions: Tracking What LLMs Say About You
AI brand mentions track how and when large language models reference your brand. Learn why monitoring matters and how to manage your AI presence.
Citation Signal Matrix: The Factors That Drive AI Mentions
The citation signal matrix maps the factors that influence whether AI models cite your brand.
Share of Voice in AI: Measuring Brand Presence Across LLMs
Share of voice in AI measures how often your brand is mentioned relative to competitors in AI-generated responses.
LLM Citations: How AI Models Reference Sources
Understand how large language models cite sources in their responses and how to earn more LLM citations for your brand.
AI Visibility: What It Means for Brands in 2026
AI visibility measures how often and how favorably AI models mention your brand. Learn what drives AI visibility and how to improve it.
Answer Engine Optimization (AEO): What It Is and Why It Matters
Answer Engine Optimization (AEO) is the practice of structuring content to appear in AI-generated answers. Learn strategies and measurement approaches.
Generative Engine Optimization (GEO): The Complete Guide
Learn what Generative Engine Optimization (GEO) is, why it matters for modern brands, and how to optimize your content so AI models recommend you.