The language of AI search
Clear definitions for narrative intelligence, answer-engine optimization and how AI models decide whose frame to recommend, not just who gets mentioned.
AI answer monitoring
AI answer monitoring is the practice of systematically observing how AI-powered search engines and conversational models represent a brand, product, or category within their generated responses.
Read definition →AI brand hallucination
AI brand hallucination is when an AI system generates confident, specific claims about a brand, such as its features, pricing, positioning, or status, that are factually wrong or entirely fabricated, producing authoritative-sounding misinformation at recommendation scale.
Read definition →AI citation rate
AI citation rate is the percentage of AI-generated answers in a given category that reference a brand as a source or piece of evidence: the upstream signal of narrative influence, not merely of presence.
Read definition →AI prompt tracking
AI prompt tracking is the systematic mapping of the questions buyers and AI engines ask about a category, used to reveal where a brand's narrative is present, absent, or misrepresented across the prompts that shape model recommendations.
Read definition →AI search intelligence
AI search intelligence is the discipline of understanding not just whether a brand appears in AI-generated answers, but whose narrative frame the model adopted to build its recommendation and why.
Read definition →AI sentiment
AI sentiment is the aggregate disposition an AI engine holds toward a brand, not merely whether the brand appears in an answer, but the framing, valence, and narrative authority the model assigns to it when forming a recommendation.
Read definition →AI visibility platform
AI visibility platform is a category of software that tracks whether and how often a brand appears in AI-generated answers across engines such as ChatGPT, Gemini, Perplexity, and Google AI Overviews.
Read definition →AI visibility score
AI visibility score is a metric that quantifies how often and how prominently a brand appears in AI-generated answers, though presence alone doesn't capture whether the brand's narrative frame is the one the model adopted.
Read definition →AI-attributed leads
AI-attributed leads is the subset of inbound pipeline that originated from an AI engine's active recommendation, not mere mention, meaning the model's narrative frame about a category demonstrably moved a buyer's decision.
Read definition →Answer consistency
Answer consistency is the degree to which an AI engine's representation of a brand remains stable, with the same frame, same narrative, and same relative position, across different prompts and over time.
Read definition →Answer engine optimization
Answer engine optimization is the practice of shaping which narrative framework an AI model adopts when answering questions about your category. The frame the model inherits determines its recommendation, not the volume of mentions you accumulate.
Read definition →Brand intelligence platform
Brand intelligence platform is a class of software that aggregates and analyzes signals from markets, media, and customers to surface how a brand is perceived, discussed, and positioned across channels.
Read definition →Brand mentions
Brand mentions is the count of times a brand name surfaces in a given channel, search results, AI-generated answers, or third-party content, treated as a signal of presence but not of influence or narrative control.
Read definition →Citation and source analysis
Citation and source analysis is the practice of identifying which external sources and narratives an AI model draws on when constructing answers about a category, so practitioners can act on the inputs that shape the output rather than reacting to the output alone.
Read definition →Citation count
Citation count is the number of times a source is referenced by AI-generated answers within a defined category or topic, indicating how much that source contributes to the model's learned understanding of the space.
Read definition →Competitor gap
Competitor gap is the narrative distance between how AI frames your brand and how it frames a competitor: the frame you're losing, not merely the mentions you're missing, and the upstream cause of which brand the model actually recommends.
Read definition →Content gap analysis
Content gap analysis is the practice of identifying where a brand's narrative is absent or misrepresented across the prompts and sources AI models draw on when answering questions about a category.
Read definition →Entity mapping
Entity mapping is the practice of identifying which people, companies, products, and concepts an AI model treats as canonical representatives of a category, and tracing the narrative frame it uses to connect them.
Read definition →Explain-why
Explain-why is the capacity to identify not merely whether a brand appears in an AI-generated answer, but which narrative, sources, and frames caused the model to recommend it the way it did.
Read definition →Generative engine optimization
Generative engine optimization is the practice of shaping the narratives, sources, and frames that AI models draw on when constructing answers, so a brand's story, not just its name, becomes the basis of the model's recommendation.
Read definition →Market consensus
Market consensus is the dominant, collectively reinforced understanding of a category, covering which problems matter, which solutions work, and which brands represent the answer, that forms across content, conversation, and sources over time.
Read definition →Narrative drift
Narrative drift is the gradual divergence between how a brand intends to be understood and the frame that market consensus, and by extension AI systems, has actually adopted about it.
Read definition →Narrative graph
Narrative graph is a structured map of the claims, frames, sources, and relationships that collectively define how a category's story is constructed and which entities are positioned as authoritative within it.
Read definition →Narrative intelligence
Narrative intelligence is the capacity to read not just whether a brand appears in AI-generated answers, but whose interpretive frame those answers are built on and why the model learned to tell that story.
Read definition →Narrative share
Narrative share is the proportion of a category's dominant explanatory frame that a given brand owns inside AI-generated answers, measuring whose story the model tells, not merely how often a brand is mentioned.
Read definition →Perception gap
Perception gap is the measurable distance between how a brand understands itself and how it is actually represented in the external narrative that AI engines learn from and reproduce in their answers.
Read definition →Prompt coverage
Prompt coverage is the percentage of category-relevant prompts for which a brand's narrative appears in the AI-generated answer, an upstream signal of whose frame the model has adopted, not merely whether the brand is mentioned anywhere.
Read definition →Semantic SEO
Semantic SEO is the practice of shaping the underlying narrative framework, meaning the sources, reasoning, and story that AI models and search engines learn about a category, rather than optimizing for keyword presence or mention counts alone.
Read definition →Share of voice
Share of voice is the proportion of total category visibility, across a defined channel or medium, that a given brand occupies relative to its competitors.
Read definition →Source inclusion
Source inclusion is the measure of whether a brand's evidence, claims, and perspectives are structurally woven into the frame an AI model builds about a category, not merely referenced in passing.
Read definition →Source intelligence
Source intelligence is the practice of tracing which underlying sources, citations, and narratives an AI system draws on when constructing its answers, so practitioners can act on the inputs that shape recommendations rather than just observing the outputs.
Read definition →Visibility-intent match
Visibility-intent match is the degree to which a brand's presence in AI-generated answers aligns with the specific prompts, questions, and decision contexts that actually drive buyer intent in a category.
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