AEO Glossary: 80 Terms You’ll See in 2025
Your definitive AI SEO glossary for 2025 — 80 essential AEO/GEO terms with clear definitions, anchor links, and sources. Targets “ai seo glossary” and “aeo terminology.”

AEO Glossary: 80 Terms You’ll See in 2025 — a practical reference for teams working on AI SEO, AEO, and GEO. Use the anchor index to jump to terms, and check the source links for deeper reading. For a nuts-and-bolts walkthrough of Google’s pipeline, see How AI Overviews Work (Without the Hype).
Authoritative references used throughout: Google’s AI Overviews and AI features explainers (Google) (how it works) (AI features & your website); Structured data docs (Article) (FAQPage) (HowTo); RAG paper (Lewis et al., 2020); BM25 intro (Okapi BM25); INP metric (web.dev); robots.txt (Search Central); E-E-A-T (QRG update).
A
- AEO (Answer Engine Optimization)
- Practice of preparing content to be cited inside AI-generated answers across Google AI Overviews, Perplexity, and Copilot; emphasizes answer-first passages, structure, and trust.
- AI Mode (Google)
- Conversational search experience that expands on Overviews with deeper reasoning and chat-like follow-ups. See Google’s updates on AI experiences in Search (Google, 2025).
- AI Overviews
- AI-generated snapshots with links to “learn more,” triggered when synthesis helps; powered by a custom Gemini model for Search (Google).
- Anchor Text
- The clickable text of a link; descriptive anchors help retrieval systems understand relationships between pages and entities.
- Answer Engine
- System that synthesizes answers (with citations) instead of listing links; examples include AI Overviews, Perplexity, Bing Copilot.
- Answer Passage
- A short, self-contained paragraph that directly answers a question; the unit engines often extract and cite.
- Answer Surface
- The UI area where an AI-generated summary appears (e.g., AI Overviews block) with inline citations.
- Article schema
- JSON-LD describing articles (headline, author, datePublished, etc.), improving machine parseability (Docs).
- Use Person/Organization structured data and on-page bios to establish credentials and trust (Org schema).
- The depth and coherence of coverage across a topic cluster (pillar + supporting pages); correlated with citation likelihood.
B
- BM25
- Classic lexical ranking function used in retrieval; balances term frequency and document length (Okapi BM25).
- Backlink
- An external link to your page; still a trust signal, but AEO emphasizes corroborated, answer-ready content over sheer link volume.
- Bing Copilot
- Microsoft’s answer engine that blends summaries with structured cards; shows citations alongside results.
- Markup that clarifies page position in your site’s hierarchy for users and crawlers.
C
- Canonical URL
- Signals the preferred version of a page when duplicates/params exist; helps consolidate signals and avoid dilution.
- Inline Citation
- Linked reference inside an AI summary; the core mechanic answer engines use to let users verify claims.
- Chunking
- Splitting long text into smaller passages for retrieval; improves recall and extractability.
- Core Web Vitals
- Field UX metrics (LCP, CLS, INP) used by Google; better responsiveness and stability support engagement (INP).
- Crawl Budget
- The number of URLs Googlebot can and wants to crawl; wasteful params and duplicates consume budget.
- Crawling & Indexing
- Discovery and storage phases of search; prerequisite for any AEO visibility.
- Click-through Rate (CTR)
- Share of impressions that become clicks; with Overviews, expect fewer low-intent clicks and higher qualified ones.
- Content Freshness
- Recency of facts and timestamps; essential for topics where AI features favor current information.
D
- Data Provenance
- Traceability of sources and updates; improves trust for both users and answer engines.
- Deep Page
- Specific, non-homepage URL with expert content; frequently cited in AI summaries versus generic homepages.
- Deduplication
- Systems collapse near-duplicate content to avoid redundant results; helps reduce noise in retrieval.
- robots.txt Disallow
- Rule to restrict crawler access to paths; note robots.txt is not a privacy mechanism (Search Central).
- Unofficial, vendor-created metric; useful directionally, not a Google ranking factor.
E
- E-E-A-T
- Experience, Expertise, Authoritativeness, Trustworthiness; principles from Google’s rater guidelines (QRG).
- Embedding
- Vector representation of text/images enabling semantic retrieval and re-ranking.
- Entity
- A distinct thing/concept (person, org, product). Entity clarity strengthens topical signals and disambiguation.
- Entity Home
- The canonical page that best describes an entity (often your about/author page) used for disambiguation.
- Entity Linking
- Connecting mentions to the correct entity (schema, consistent naming, sameAs) to reduce ambiguity (schema.org).
- Extractive vs Abstractive Summarization
- Extractive quotes text verbatim; abstractive composes new sentences. Overviews generally synthesize (abstractive) but ground in sources.
F
- FAQPage schema
- Explicit Q&A structure for common questions; boosts machine readability (Docs).
- Faceted Navigation
- Filters that explode URL combinations; control crawl with canonicals/noindex and maintain clean indexation.
- Featured Snippet
- Single-source extract shown atop results; distinct from Overviews, which synthesize multi-source summaries.
- First-party Data
- Your owned data (analytics, CRM). Useful for personalization and measuring AEO impact, not a direct ranking factor.
- Fine-tuning (LLMs)
- Adapting a base model on task-specific data; in search, often complemented by retrieval grounding (RAG).
- Field vs Lab (UX)
- Field data (real users) vs lab data (synthetic tests). CWV are field-based; optimize for actual user conditions.
G
- GEO (Generative Engine Optimization)
- Another name for AEO; emphasizes the generative pipeline that selects and cites passages.
- Gemini (model)
- Google’s family of models; AI Overviews use a custom Gemini for Search (Google).
- Googlebot
- Google’s crawler; respects robots.txt and fetches content to index.
- Knowledge Graph
- Google’s entity graph connecting people, places, things; supports disambiguation and richer results.
- Grounding
- Tying generated text to retrieved sources to reduce hallucinations; core idea in RAG (RAG).
- Google Search Console (GSC)
- Google’s measurement/diagnostics tool; track impressions/clicks and crawling/indexation. Some AI features have unique tracking caveats.
H
- Hallucination
- Confident but incorrect model output; mitigated (not eliminated) by grounding and evaluation loops.
- Helpful Content
- People-first pages that demonstrate expertise and satisfy intent; follow Google’s guidance on creating helpful content.
- HowTo schema
- Structured steps, tools, and materials for procedures; improves extractability (Docs).
- Headings (H1–H3)
- Semantic structure for scannability and passage discovery; map questions to H2/H3 where possible.
- Human-in-the-Loop (HITL)
- Human review for accuracy, safety, and nuance—especially critical in YMYL domains.
I
- Internal Linking
- Connects pillar pages to supporting content; clarifies topic clusters and improves passage discovery.
- INP (Interaction to Next Paint)
- Core Web Vital for responsiveness; lower INP reflects faster interactivity (web.dev).
- Intent (Search Intent)
- User purpose behind a query (informational, transactional, etc.); guides format and angle of answers.
- Information Gain
- New, non-obvious utility your page adds beyond existing results; a practical lens for differentiation.
- Index Coverage (GSC)
- Reports showing which URLs are indexed, excluded, or erroring; fix blockers before chasing AEO wins.
- ImageObject schema
- Structured data describing images (url, caption, author), aiding media understanding and licensing signals.
- URL Parameters
- Args appended to URLs that can cause duplicate content; consolidate with canonicals or parameter handling.
J
- JSON-LD
- Preferred format for structured data markup embedded in pages (Intro).
- Jump Link (Anchor)
- In-page link to a section; helps UX and can align with “answers above the fold.”
- JavaScript SEO
- Ensuring JS-rendered content is crawlable and indexable (SSR/ISR or hydration best practices).
K
- Keyword Clustering
- Grouping semantically related queries to design pillar/cluster coverage and avoid cannibalization.
- Knowledge Graph (KG)
- See also “Graph” above; entity relationships informing search understanding.
- KNN Search
- k-nearest neighbors retrieval over vectors; typical primitive for semantic search in vector DBs.
O
- Ontology
- Formal model of concepts and relationships in a domain; improves consistency of entity-centric content.
P
- PAA (People Also Ask)
- Expandable Q&A units in Google Search; useful for mining real questions to structure answer-first content.
- Passage Ranking
- Retrieval focus on specific paragraphs within a page; favors clearly scoped, answerable passages.
- Perplexity (Answer Engine)
- Real-time, citation-forward engine that summarizes with numbered sources; an additional discovery surface.
- Product schema
- Structured data for offers, reviews, and product details; important for ecommerce discovery (Docs).
- Page Experience
- Holistic UX signals (speed, stability, mobile-friendliness, HTTPS) that influence engagement and trust.
Q
- Query Expansion
- System strategy to broaden/clarify a query with related terms/entities to improve recall.
- Quality Raters Guidelines (QRG)
- Instructions guiding human raters in evaluating search systems; the source of E-E-A-T principles (Docs).
R
- RAG (Retrieval-Augmented Generation)
- Pipeline that retrieves sources, then generates text grounded in them; reduces hallucinations (Lewis et al.).
S
- Scaled Content Abuse
- Spam policy violation where many low-value pages are generated; Google permits AI content if it meets quality standards (Policy).
- Structured Data Markup
- Machine-readable JSON-LD describing your content; helps understanding and rich presentation (Intro).
T
- Tokens
- Sub-word units processed by LLMs; impact context window and the size of passages for retrieval.
U
- URL Parameters
- See “Index Params” above—manage to avoid duplicate content and crawl waste.
V
- Vector Database
- Store/retrieve embeddings for semantic search; backbone of modern RAG retrieval.
- Vector Search
- Similarity search over embeddings (ANN/KNN); complements keyword retrieval (e.g., BM25).
X
- X-Robots-Tag
- HTTP header alternative to meta robots; control indexing for non-HTML assets and edge cases.
Y
- YMYL (Your Money or Your Life)
- High-stakes topics (finance, health, safety) where E-E-A-T and expert review are critical.
Z
- Zero-click Search
- Answers delivered on the SERP without a traditional click; Overviews intensify this for certain queries while still linking out.
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Authoritative Sources & Further Reading
- Google: Generative AI in Search (AI Overviews rollout)
- Google: How AI Overviews work & quality updates
- Search Central: AI features & your website
- Structured Data: Article · FAQPage · HowTo
- Lewis et al. (2020): Retrieval-Augmented Generation (RAG)
- INP (Interaction to Next Paint) · robots.txt (Search Central) · Okapi BM25