GEO — Generative Engine Optimization
The practice of optimizing web content to be discovered, cited, and accurately represented by AI-powered search and answer engines such as ChatGPT, Perplexity, and Google AI Overviews.
Unlike traditional SEO, which targets ranking positions in link-based result pages, GEO focuses on citation-worthiness, answer structure, and entity clarity for retrieval-augmented generation systems.
SOV — Share of Voice
The percentage of AI-generated answers in a given topic or keyword cluster where a specific brand is mentioned or cited.
CitationGraph measures SOV across multiple AI platforms independently, because citation patterns differ substantially between engines.
SAAI — Share of AI-Attributed Income
A four-dimensional attribution model that connects AI visibility to actual product-level revenue. The four dimensions are: Attention (brand appeared in AI answer), Referral (user clicked through), Commercial Intent (user viewed product or pricing), and Realized Revenue (purchase completed).
SAAI replaces simple last-click attribution with a layered model that accounts for the delayed, multi-touch nature of AI-assisted purchase journeys.
CQS — Citation Quality Score
A composite metric that evaluates how well a specific page or URL is being cited by AI systems. Factors include citation frequency, citation accuracy (whether the AI correctly represented the page content), citation context (positive, neutral, or negative framing), and downstream traffic generated.
AI Readiness Score
A diagnostic model that evaluates a website's preparedness for AI-driven discovery and citation across four dimensions: Infrastructure (HTTPS, robots.txt, sitemap, response speed), Metadata (title, description, canonical, Open Graph), Structured Data (JSON-LD coverage, schema depth, FAQ presence), and AI Guidance (llms.txt quality, crawler policy).
The score is not a universal ranking formula. It is a diagnostic tool designed to surface specific weaknesses and guide targeted improvements.
llms.txt
A machine-readable text file placed at a website's root that provides structured guidance to AI retrieval systems. It describes the site's product boundary, key public resources, preferred citation surfaces, and trust pages.
While not a formal standard, llms.txt has emerged as an effective practice for helping AI systems understand site intent and structure, complementing robots.txt and sitemap.xml.
Key takeaways
- •GEO extends SEO toward citation-worthiness for AI answer engines.
- •SOV, SAAI, and CQS form the core measurement vocabulary of AI visibility analytics.
- •The AI Readiness Score is diagnostic, not prescriptive.
- •llms.txt is a guidance layer, not a replacement for technical SEO fundamentals.