Beyond Mentions glossary

The vocabulary that makes AI decisions readable.

Short definitions to understand the criteria, proof, categories and metrics that structure an AI answer.

Structuring terms

Understand the words that shape the shortlist, tender and comparison.

AI buying criteria are the purchasing criteria proposed by AI before a buyer writes the technical specification.

An AI Cognitive Map Audit measures how AI systems understand a market, its categories, criteria, proof and actors before a decision.

Bridge Vocabulary refers to the terms that help a new offer be understood by buyers and AI before a proprietary category is introduced.

Category Compression Risk measures the risk that AI reduces a new offer to an existing category that is too narrow or misleading.

Citation Efficiency is the ratio of a page's AI citations to its SERP impressions. It measures a page's ability to convert visibility into citations.

Consensus patterns are recurring formulations AI systems repeat when describing a market, standard or supplier.

Decision share of voice measures a brand's ability to be associated with the criteria AI systems use to compare and shortlist offers.

A documentation blind spot is a missing proof, standard or criterion that lets AI reconstruct an overly generic answer.

Intent Match is a page's ability to match the exact natural phrasing of a question, a key factor in being cited by generative AI.

Pre-launch GEO tests how AI systems understand an offer or category before public publication.

Pre-tender criteria setting describes the moment when AI influences buying criteria before the formal specification is written.

The specification gap is the distance between the required technical level and the criteria AI helps the buyer formulate.

A short diagnostic identifies category compression, documentation gaps and criteria that influence the decision.