Canonical definitions for every term used across Astiva's product, methodology, and reports. Each term has a fact-first definition and links to related concepts. Written to be citation-safe for AI platforms that extract definitions from the open web.
The practice of monitoring, analyzing, and improving how a brand appears in AI-generated answers across platforms like ChatGPT, Claude, Gemini, and Perplexity. The category Astiva operates in. Related: AEO, GEO, Share of Voice.
The practice of optimizing content so that answer-oriented search surfaces (Google AI Overviews, Bing Copilot) extract and present the content as the direct answer to a user query. Related: AISO, GEO, Featured Snippet.
The practice of optimizing content so that generative AI engines cite, recommend, or mention a brand inside their responses. GEO overlaps heavily with AISO; usage differs by vendor and region. Related: AISO, AEO, RAG.
The share of tracked prompts in which a brand is mentioned at least once. The headline AISO metric.
The proportion of brand mentions in a tracked competitive set that belong to a given brand. SoV = brand mentions / (brand mentions + competitor mentions).
Where a brand appears within an AI-generated response — first mentioned, middle, or later. One of the 7 AISO metrics Astiva tracks at 24h, 7d, and 30d windows.
The tone (positive, neutral, negative) of each brand mention in an AI response, aggregated per platform and per time window.
The share of AI responses in which a brand is named before any competitor in the tracked set. A top-of-mind awareness indicator.
The total count of brand mentions across all AI responses in a time window, de-duplicated at the response level.
Week-over-week variance in brand sentiment across AI platforms. Rising volatility with stable average sentiment is an early signal that perception is polarising.
A reference by an AI platform to a specific source (URL, publication, or brand) inside a generated response. Citations are the primary unit of earned AI visibility.
A prompt or topic where a competitor is cited by AI platforms and a brand is not. Identifying citation gaps is the input to the Displace stage of the Detect to Diagnose to Displace to Prove framework.
The rate at which a brand earns new citations from AI platforms over time. Rising velocity signals that published content is being indexed by AI retrieval systems.
An AI architecture where a model fetches external information at query time, then uses that information to generate a response. Perplexity is the clearest example; ChatGPT and Claude use RAG selectively.
A Schema.org structured-data type that wraps question-and-answer pairs on a page. FAQPage schema materially increases the chance of inclusion in featured snippets and AI Overview extractions.
A lightweight format for embedding Schema.org structured data in HTML. The preferred way to ship Organization, SoftwareApplication, FAQPage, and BreadcrumbList schema to both search engines and AI crawlers.
An emerging convention for a root-level text file that describes a site in a format optimized for AI crawlers — canonical product definition, pricing, methodology pointers, and FAQ summaries. Astiva publishes both llms.txt and llms-full.txt.
The date through which an AI model was trained on data. Events, products, or claims after the cutoff are invisible to the model unless it has real-time retrieval (RAG).
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