Reference

RankOps Glossary

The vocabulary of the operating layer for ranking. SEO is the floor; AEO, GEO and AI visibility are the ceiling. Definitions written by the team building the platform — not lifted from training data.

RankOps: The operating layer for ranking. RankOps unifies six disciplines brands currently buy as separate tools — SEO, AEO, GEO, AI content generation, multi-platform distribution, and continuous monitoring — and runs them as one closed loop: detect, fix, publish, distribute, measure, repeat. RankOps is to ranking what DevOps is to shipping code.
SEOaka Search Engine Optimization · Search Engine Optimisation: Optimising a website to rank in traditional keyword-based search engines, primarily Google. Signals include on-page metadata, technical crawlability, backlinks, and content quality. SEO is the floor of RankOps — necessary but no longer sufficient now that search has fragmented across answer engines and generative engines.
AEOaka Answer Engine Optimization · Answer Engine Optimisation: Optimising content for AI answer engines and featured snippets (Google AI Overviews, voice assistants, ChatGPT, Perplexity). Focus areas: FAQPage / HowTo / Speakable schema, question-form H2 and H3 headings, 40–60 word "snippet-sized" answer paragraphs, and conversational phrasing rather than skim-friendly bullets.
GEOaka Generative Engine Optimization · Generative Engine Optimisation: Optimising content for generative AI engines — ChatGPT, Gemini, Perplexity, Claude. GEO measures how citation-worthy a page is to a language model that synthesises an answer. Signals: entity coverage, citation quality of outbound links, author credibility, content depth, freshness, and claim specificity. A perfect SEO page can score near zero on GEO if it offers nothing a model would want to reference.
AI Visibility: The degree to which a brand is mentioned and cited in AI-generated answers across ChatGPT, Perplexity, Claude, and Gemini. Tracked by running real prompts at each engine and parsing the response for: mention presence, mention position (first vs supporting vs trailing), citation status (was a URL referenced), and sentiment (recommended vs neutral vs unfavourable). The metric AEO and GEO work moves.
Rank Unitsaka RU: Rankverse's usage-based billing currency. Each capability has a published RU rate — article generation, keyword refresh, AI-visibility prompt set, audit, scan. Included in tier subscriptions; top-up packs available beyond tier limits (5k, 25k, 100k, 500k RU bands with stepped discounts). 1 RU = ₹1 (ex-GST). Balance valid 12 months.
Answer Engine: A search interface that responds with a synthesised answer rather than a list of blue links. Includes Google AI Overviews, featured snippets, voice assistants (Alexa, Siri, Google Assistant), and ChatGPT-style chat search. The optimisation discipline for these is AEO.
Generative Engine: An LLM-powered system that produces original text answers, typically with retrieval-augmented generation. Examples: ChatGPT (GPT-4o with browsing), Claude (with web search), Gemini, Perplexity. The optimisation discipline is GEO.
Citation: A reference — typically a URL — included by an AI engine when generating an answer. The currency of AI visibility: being cited drives both discovery and downstream trust. Different from a backlink in that no second-site HTML link exists; the citation lives only in the model output.
JSON-LDaka Structured Data: Machine-readable markup using the schema.org vocabulary, embedded as a <script type="application/ld+json"> block in HTML. JSON-LD is Google's recommended structured-data syntax. AI engines parse it to understand entities (Organization, Product, Person), relationships, and page type (FAQPage, Article, BreadcrumbList). Necessary for AEO eligibility.
FAQPage: A schema.org type used to mark up question-and-answer content. Each Question has an acceptedAnswer (or suggestedAnswer). Required for Google's rich-result FAQ display and used by AEO scoring. Common failure modes: schema rendered client-side (invisible to crawlers), Q&A pairs that don't match visible on-page text, or missing surrounding question-form headings.
Speakable: A schema.org specification (SpeakableSpecification) that identifies sections of a page suitable for text-to-speech extraction by voice assistants. Implemented via a cssSelector or xpath pointing at the speakable nodes. Underused but cheap AEO win — declares that your FAQ answers are voice-ready.
E-E-A-Taka Experience, Expertise, Authoritativeness, Trustworthiness: Google's quality framework introduced in its Search Quality Rater Guidelines. AI engines apply a similar logic. High E-E-A-T pages have named credible authors, transparent affiliations, citations to primary sources, and clear evidence of first-hand experience. Critical for GEO: language models preferentially cite content with explicit author entities.
Core Web Vitalsaka CWV · LCP · INP · CLS: Google's user-experience signals and a ranking factor since 2021: Largest Contentful Paint (LCP, how fast main content paints), Interaction to Next Paint (INP, how responsive the page feels to input), and Cumulative Layout Shift (CLS, how stable the layout is during load). Measured against thresholds at the 75th percentile of real-user data.
BreadcrumbList: A schema.org type that describes a page's position in a site hierarchy as an ordered list of ListItems. Helps search and AI engines understand site structure and enables breadcrumb-style rich results. Should be added to every non-home page alongside a WebPage entry.
llms.txt: An emerging convention for sites to publish a curated content index for large language models, served at /llms.txt as plain Markdown. Acts as a "machine-readable table of contents" so LLM-driven agents can navigate a site without scraping the full HTML graph. A companion /llms-full.txt concatenates long-form content for retrieval.

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