AI Marketing Glossary

The discipline of analyzing how AI models perceive, describe, and position brands and entities. It measures visibility, sentiment, narrative alignment, and competitive positioning within AI-generated responses. AIPI is a new category of strategic intelligence for the AI era.

A measure of how often and prominently a brand appears in AI-generated responses. High AI visibility means AI models frequently mention, describe, and recommend your brand when users ask relevant questions.

A comprehensive metric that quantifies a brand's presence across AI platforms. It combines mention frequency, sentiment, positioning, and context quality into a single score representing overall AI discoverability.

How AI models describe, characterize, and position a brand in their responses. This includes the tone, sentiment, attributes, and comparisons AI uses when discussing your brand.

Instances where AI models generate false or inaccurate information about a brand. This can include wrong facts, made-up features, or incorrect associations. Monitoring and correcting hallucinations is crucial for brand protection.

The gradual divergence between how AI models describe your brand and your intended brand identity. Brand drift can occur as AI training data becomes outdated or when AI picks up incorrect information.

The practice of structuring content to maximize the likelihood of being cited or referenced by AI models. Includes creating quotable statements, clear definitions, and authoritative content.

Optimizing content for natural language queries and conversational AI interactions. This includes targeting question-based queries and structuring content to answer the way humans naturally ask.

The practice of optimizing your brand, content, and digital presence to be discovered, understood, and recommended by AI-powered systems including large language models (LLMs), AI assistants, and generative search engines. GEO is the evolution of SEO for the AI era.

A proprietary metric by Refractia (0-100) that measures how well-optimized a brand is for AI discovery. It evaluates factors including AI visibility, sentiment, narrative alignment, citation likelihood, and competitive positioning.

The practice of optimizing content to appear in AI-generated responses from large language models like ChatGPT, Claude, and Gemini. Unlike traditional SEO which focuses on search rankings, LLM SEO focuses on AI understanding and recommendation.

The degree to which AI descriptions of your brand match your intended brand identity and messaging. High narrative alignment means AI accurately represents your brand story, values, and positioning.

In the AI context, Share of Voice measures how often a brand is mentioned in AI-generated responses compared to competitors when users ask about a category or topic. It's a key competitive metric in the AI era.

The degree to which content is structured for AI understanding. Semantically clear content uses consistent terminology, logical structure, and unambiguous language that AI can easily parse and interpret.

Google's AI-powered search feature that generates comprehensive answers using AI. SGE represents the integration of generative AI into traditional search, blending search results with AI-generated summaries.