AI Visibility Glossary

AI Marketing Performance Dashboard. A platform that measures and scores brand visibility across AI-powered discovery platforms including ChatGPT, Perplexity, Claude, Gemini, Copilot, Grok, and DeepSeek. AMPD provides actionable insights to help brands improve how they are cited and recommended by AI systems.

Composite Performance Score. An aggregate metric combining multiple visibility signals into a single normalised score (0–100) that represents a brand’s overall AI visibility performance. CPS accounts for domain authority, content quality, citation frequency, social presence, and technical factors.

Citation Frequency Index. A measure of how often a brand or domain is cited, referenced, or recommended in AI-generated responses across multiple platforms. Higher CFI indicates stronger presence in AI-mediated discovery.

Semantic Authority Visibility. AMPD’s proprietary framework for scoring how well a brand’s content is understood and valued by AI systems. SAV evaluates structured data, entity clarity, topic authority, and contextual relevance to determine how likely AI platforms are to surface a brand in relevant queries.

Generative Engine Optimisation. The practice of optimising content and digital presence specifically for AI-powered generative search engines. GEO extends beyond traditional SEO by focusing on how content is retrieved, synthesised, and cited by large language models and AI assistants.

Answer Engine Optimisation. A content strategy focused on structuring information so it is directly selected and presented as answers by AI assistants and answer engines. AEO prioritises concise, authoritative, and well-structured content that AI systems can confidently cite.

AI Experience Optimisation. The holistic practice of optimising a brand’s entire digital footprint—including content, structured data, reviews, and technical infrastructure—to improve the overall experience and representation of the brand within AI-mediated interactions.

AI Optimisation. A broad term encompassing all strategies and techniques aimed at improving a brand’s visibility, representation, and citation rates across AI platforms. AIO includes GEO, AEO, and AXO as specialised sub-disciplines.

Platform-Adjusted Weighted Citation. A scoring methodology that weights citation frequency differently based on the AI platform generating the citation. PAWC reflects the fact that different AI platforms (ChatGPT, Claude, Perplexity, etc.) have different user bases, influence levels, and citation behaviours.

Signal Integrity. A quality metric that measures the reliability and consistency of the data signals used to calculate visibility scores. High SI indicates that the underlying data sources are fresh, complete, and verified, giving greater confidence in the resulting scores.

Retrieval-Augmented Generation. An AI architecture pattern where a language model retrieves relevant documents or data from external sources before generating a response. RAG is the mechanism by which AI platforms cite and reference brand content, making it a critical pipeline for AI visibility.

Experience, Expertise, Authoritativeness, and Trustworthiness. Originally a Google quality framework, E-E-A-T is now recognised as influential in how AI platforms evaluate and prioritise sources for citation. Brands with strong E-E-A-T signals across their content and digital presence are more likely to be referenced by AI systems.

A research-backed methodology developed by Aggarwal et al. that identifies the key factors influencing how content is selected, cited, and ranked by generative AI systems. The Aggarwal Framework provides the academic foundation for many of AMPD’s scoring algorithms and emphasises structured content, source credibility, and contextual relevance.

The degree to which a brand or domain is recognised by AI systems as an authoritative source on specific topics or entities. Semantic authority is built through consistent, comprehensive, and well-structured content that clearly establishes expertise in a defined subject area.

A measure of how closely a brand’s content matches the context and intent of user queries processed by AI platforms. High contextual relevance increases the likelihood that AI systems will retrieve and cite a brand’s content when generating responses to related queries.

The perceived trustworthiness and reliability of a content source as evaluated by AI systems. Source credibility is influenced by domain authority, backlink profile, citation history, factual accuracy, review signals, and consistency of information across the web.

Universal Compliance Protocol. A set of ethical and regulatory standards that AMPD adheres to when collecting, processing, and presenting data. UCP compliance ensures that visibility scoring is conducted transparently, user data is protected, and recommendations are made in accordance with applicable data protection regulations.

A visibility signal measuring how recently content has been published or substantially updated. AI platforms tend to favour fresh, current content when generating responses, particularly for queries where timeliness is relevant. Regularly updating content with accurate, current information can improve citation rates.