GEO terms: complete glossary to master AI optimization

The GEO (Generative Engine Optimization) field has spawned an entire vocabulary in two years: citation capsule, Share of Model, llms.txt, RAG, AI framing, AI Overviews, GPTBot, IDO. This glossary brings together the essential GEO terms in 2026, organized by family, with operational definitions, examples and links to our detailed guides. The goal: give a CMO, SEO manager or content lead a single reference to speak GEO without wasting time on rough translations.

The timing is right. 32.7% of Europeans used a generative AI tool in 2025 according to Eurostat (December 2025), 67% of Belgians are already users per the Semactic & PingPrime study from November 2025, and Gartner expects a 25% drop in traditional search volume by the end of 2026 (Gartner, February 2024). Understanding the words of GEO means understanding the ground where your brand now plays out.

The bottom line

• GEO covers seven families of terms: fundamentals (GEO, AEO, AIO, LLMO), citability, platforms (ChatGPT, Perplexity, Gemini), KPIs (Share of Model, citation rate), techniques (answer-first, schema, chunking), narrative authority and technical elements (llms.txt, GPTBot).
• According to Princeton researchers, applying GEO techniques boosts visibility in generative engines by an average of +40% (Aggarwal et al., KDD 2024).
• Reddit is the #1 source cited by AIs across all platforms, ahead of Wikipedia. And only 11% of domains are cited by both ChatGPT and Perplexity.
• Mastering this vocabulary determines the ability to talk to a GEO agency, brief a content team and steer an AI visibility budget.

What are the fundamentals of GEO vocabulary?

Five acronyms structure the entire discipline. According to PwC Belgium (Bridging the AI Gap, 2025), 76% of Belgian companies are experimenting with or piloting AI, but only 21% have moved past the pilot stage. That gap comes partly from a lack of shared vocabulary between marketing, SEO and data teams. Clarifying terms means aligning decisions.

GEO (Generative Engine Optimization)

Discipline of optimizing a brand, its content and its external sources to be understood, remembered and cited by generative engines (ChatGPT, AI Overviews, Perplexity, Claude, Gemini). The term was formalized by researchers from Princeton, Georgia Tech and Allen AI in their founding November 2023 paper, presented at KDD 2024. For a complete definition, see our guide What is GEO.

AEO (Answer Engine Optimization)

Optimization for answer engines. Concept that predates GEO, focused on featured snippets, People Also Ask and voice assistants (Alexa, Siri). AEO shares answer-first logic and Schema markup with GEO, but targets narrower answer formats. In 2026, AEO and GEO overlap heavily, with AEO often perceived as a subset. Detailed comparison in GEO vs SEO vs AEO.

AIO (AI Optimization) and LLMO (LLM Optimization)

Commercial synonyms of GEO, used by some agencies to stress the generative AI dimension. AIO can also stand for Google's AI Overviews (watch the double meaning by context). LLMO emphasizes optimization for Large Language Models (ChatGPT, Claude, Gemini), including off-search uses (integrated chatbots, agents).

SGE and AI Mode

SGE refers to the Search Generative Experience, the historical name Google gave its AI search tests in 2023-2024. The term was replaced by AI Overviews (AI summaries atop the results) then AI Mode (a fully-fledged conversational mode). According to Google (October 2025), AI Mode is now deployed in 200+ countries/territories and 35-36 languages, including Belgium in French, Dutch and German.

RAG (Retrieval-Augmented Generation)

Architecture that pairs an LLM with a real-time search system. The LLM fetches fresh sources from the web (or an internal base), ranks them, extracts passages, then generates its answer based on them. ChatGPT Search, Perplexity, AI Overviews and Claude all use RAG variants. For the full mechanics, see How RAG works and why it matters.

What terms define content citability?

Citability is the operational heart of GEO. An AirOps study run in 2025 shows that adding citations boosts AI visibility by +37%, and adding statistics by +22% (AirOps, 2025). Six terms describe the mechanisms by which a page becomes citable.

Citation and mention

A citation is an explicit link or referral to your source within the AI answer (visible on Perplexity and AI Overviews, sometimes implicit on ChatGPT). A mention is the appearance of your brand name in the generated text, with no mandatory link. According to AirOps, ChatGPT mentions 3.2 times more than it cites, and combining "mentioned + cited" boosts +40% the odds of re-surfacing from one run to the next.

Citation capsule

Self-contained block of 40 to 80 words containing a claim, a figure and its source. Format designed to be extracted and cited as-is by an LLM. It is the base unit of any Answer-First page. Our practical guide: Structuring an Answer-First page to be cited by AI.

Passage-level citation

Citation mode at the level of a specific passage of a page (a paragraph, a statistic, a table), rather than the whole page. LLMs have reasoned at passage level since Google introduced passage indexing in 2020 and generative models added semantic extraction in 2023. Consequence: a single strong passage can be enough to get your entire page cited.

Extractability

Ability of a piece of content to be identified, isolated and reformulated by an LLM. An extractable page features: an H2 phrased as a question, a direct answer in under 80 words in the first paragraph of the section, sourced figures, a Q&A structure. By contrast, narrative, vague or unsourced content is barely extractable.

Snippet and chunk

A snippet is a page fragment displayed in a search result (Google snippet) or in an AI answer. A chunk is a fragment indexed internally by the LLM or its RAG system (typically 200 to 500 tokens). Chunking means cutting content into coherent blocks at indexing. Chunking content well means making each section standalone and citable.

Our field observation. Based on our 2025-2026 audits across 27 B2B and consumer brands, the pages most cited by LLMs share a common trait: every H2 opens with a 40-to-60-word citation capsule and a sourced statistic. Purely editorial pages, without this discipline, are cited 3 to 5 times less often, at equivalent domain authority.

Which players and platforms should you know?

Five platforms concentrate most of AI search in 2026. According to the 5W AI Citation Source Index (2026), only 11% of domains are cited by both ChatGPT and Perplexity. Understanding who is who determines the targeting of your GEO strategy.

LLM (Large Language Model)

Large language model trained on hundreds of billions of words, capable of generating, summarizing and reasoning over text. The main consumer LLMs in 2026: GPT-5 (OpenAI), Claude (Anthropic), Gemini (Google), LLaMA (Meta), Mistral (FR/EU). An LLM alone has no web access: it has to be paired with a RAG system or an index.

ChatGPT and ChatGPT Search

OpenAI's conversational app, launched in November 2022. ChatGPT passed 800 million weekly active users in October 2025 per Sam Altman's announcement at DevDay (TechCrunch, October 2025). ChatGPT Search is its real-time search feature, integrated since late 2024. For the levers in detail: How to appear in ChatGPT.

Google AI Overviews and AI Mode

AI Overviews are the AI summaries generated atop Google results, triggered on nearly 48% of tracked queries per BrightEdge (Q4 2025), with peaks at 88% in health. AI Mode is Google's full conversational mode, deployed in Belgium since October 2025. France remains excluded to date.

Perplexity

Natively "citation-first" AI search engine: every answer systematically displays its sources. Perplexity processes 780 million queries per month per its CEO in May 2025, x3 versus mid-2024. Specifics: strong preference for Reddit (46.7% of citations) and for content less than 30 days old. See How to appear in Perplexity.

Claude (Anthropic) and Gemini (Google)

Claude is Anthropic's LLM, particularly used in B2B and tech, and favors editorial and academic sources. Gemini is Google's family of models powering AI Overviews, AI Mode and Workspace. For Claude: How to appear in Claude.

AI agent (agentic AI)

AI capable of carrying out autonomous actions on behalf of the user (booking, comparing, buying), beyond a simple text answer. According to Gartner (November 2025), 90% of B2B purchases will be intermediated by AI agents by 2028, worth more than $15 trillion. Yet 67% of Belgian companies have never heard of AI agents (PwC Belgium, 2025). Our dossier: OpenAI Operator, complete guide.

Sources: Eurostat (December 2025), Semactic & PingPrime (November 2025), Deloitte Belgium Digital Consumer Trends (2025).

To compare the three prescribing platforms in detail, read our dossier ChatGPT Search vs Google AI Overviews vs Perplexity.

What are the key GEO KPIs and indicators?

Measuring AI visibility requires specific vocabulary. According to AirOps, only 30% of brands stay visible from one run to the next (AirOps, 2025). Without indicator-based steering, you cannot tell if your efforts pay off. Here are the five KPIs that structure GEO reporting in 2026.

Share of Model

Share of times your brand is mentioned by LLMs across a basket of strategic queries. It is the AI equivalent of advertising share of voice. Calculated by testing 50 to 200 priority queries in your category on ChatGPT, Perplexity, AI Overviews, and counting your brand mentions vs competitors. Our complete method: AI citation monitoring.

AI Share of Voice

Variant of Share of Model that weights mentions by the platform's estimated weight (usage volume, target audience). Allows multi-platform visibility comparison in a single metric. More relevant than raw Share of Model when your audiences split across ChatGPT, Perplexity and AI Overviews.

Citation rate

Frequency at which your content appears as a cited source (clickable link) in AI answers, on platforms that surface their sources (Perplexity, AI Overviews). Direct indicator of a page's citability. To measure by URL, by thematic cluster and by platform.

Brand mention rate

Share of brand-name mentions in AI answers, regardless of links. Includes positive, neutral and negative mentions. To cross with framing (see below) to assess mention quality. According to AirOps, brand search volume is the best predictor of AI citations, with a 0.334 correlation.

AI framing

The way AI describes your brand: positioning, attributes, competitive comparisons, tone. Framing can be accurate, biased or wrong. Auditing framing means reading what ChatGPT or Perplexity says about your brand, not just whether they mention it. Our methodological framework: GEO and branding: how AI shapes perception.

Qualified AI-referred traffic

Visits from AI platforms (referrers chatgpt.com, perplexity.ai, claude.ai, copilot.microsoft.com) that lead to a conversion. According to Search Engine Land (2025), ChatGPT converts at 15.9% versus 1.76% for organic Google, a 9-to-1 ratio. Volume remains low (often under 2% of referral traffic), but quality is exceptional.

What optimization techniques fall under GEO?

Princeton's founding academic study across 10,000 queries measured the comparative impact of nine GEO techniques. According to Aggarwal et al. (KDD 2024), citations, quotations and statistics far outperform cosmetic techniques (rewriting, simplification, keywords) with measured gains between +22% and +37%. Here are the six operational techniques to know.

Answer-first

Writing principle that puts the direct answer to the H2 question in the first paragraph (40 to 80 words, with a sourced statistic), before any context. Inverts classic narrative logic. It is the most effective editorial technique to make a page extractable. Full method: Structuring an Answer-First page.

Chunking

Cutting a long piece of content into coherent, self-contained blocks, each able to be indexed and cited independently. In GEO, we target chunks of 200 to 500 tokens (roughly 150 to 350 words) with one topic, one figure and one source. Good chunking maximizes the chance that at least one block is selected at retrieval time.

Schema markup (structured data)

Standardized Schema.org markup (FAQPage, HowTo, Article, Organization, Product) that gives the engine explicit clues about page structure. Schema does not guarantee a citation, but it eases extraction and proper framing. Our complete guide: Schema Markup for GEO.

Q&A formatting

Structuring content as questions (in H2 or H3) followed by concise answers. Format particularly effective for FAQs, product pages and blog posts. LLMs prioritize extracting these blocks because they resemble the final form they aim to produce. Our best practices: GEO FAQ: creating FAQs that AI actually picks up.

Freshness

Ability of content to be perceived as recent and up to date. Key criterion on Perplexity, which cites content less than 30 days old x3.2 more often (Discovered Labs, 2025). Practical levers: visible update date, regular rewrites, explicit current-year mention in H1 and H2.

Entity authority

Recognition by LLMs of your brand as a distinct, identifiable entity, with its attributes, products and executives. Strengthened by: Wikipedia presence, Organization markup on the site, consistent mentions across third-party media, complete LinkedIn profiles of founders. Without a recognized entity, no stable framing.

Sources: Discovered Labs (AI citation patterns 2025), 5W AI Citation Source Index 2026. Reading: Perplexity favors Reddit (46.7%) while ChatGPT cites Wikipedia heavily (47.9%). For Perplexity, content less than 30 days old is cited 3.2 times more.

How is narrative authority defined in GEO?

Narrative authority is the hinge concept between technical GEO and brand strategy. According to AirOps, brand search volume is the best predictor of AI citations, and combining "mentioned + cited" boosts +40% the odds of re-surfacing from one run to the next (AirOps, 2025). Five terms define this brand capital in AI.

Narrative authority

Ability of a brand to impose its frame of reference in AI-generated answers: its definitions, positioning, figures, comparisons. A brand with narrative authority is cited as the source on its topic, not as one source among many. For the mechanics: The new rules of narrative authority.

Framing

Interpretive frame AI applies to your brand: who you are, what you do, who you compete against, your perceived strengths and weaknesses. Good AI framing is consistent with your real positioning. Bad framing can attribute competitor or obsolete attributes to your brand. To audit quarterly.

IDO method

Insights, Demand, Optimization method developed by PingPrime to structure a GEO strategy in three steps: map AI queries and current framing (Insights), identify uncovered latent demand (Demand), then execute content, technical and authority optimizations (Optimization). Concrete case in +42% AI mentions in 3 months: the IDO method in action.

Authority capital

Cumulative stock of signals that make a brand citable: Wikipedia presence, media mentions, verified customer reviews, content signed by identifiable experts, complete LinkedIn profiles, published barometers and studies. Authority capital is built over 12 to 24 months and cannot be bought back. Our op-ed: Stop chasing AI mentions, build authority capital.

Digital PR for GEO

Digital media relations designed to generate mentions on the sources LLMs consult (Wikipedia, Reddit, specialized media, sector barometers). Differs from traditional digital PR by its focus on verifiability and citability, not just raw coverage. Go deeper: The role of Digital PR in GEO.

On the brands we support. We observe that GEO programs combining external authority capital with on-site answer-first discipline generate on average 2 to 3 times more AI mentions than those playing a single lever. Synthesis matters more than the intensity of a single vector.

What technical elements does GEO mobilize?

GEO is not just editorial: it has its technical layer. 34% of Belgian workers use AI regularly at work (vs 13% in 2024) according to PwC Belgium, creating an unprecedented volume of crawls. Mastering the files and signals your servers send to AI bots has become an infrastructure issue, not just a marketing one.

robots.txt

Historical file placed at the root of a domain, telling robots which pages to crawl or not. Still in use in 2026, it now also serves to allow or block AI crawlers (GPTBot, ClaudeBot, PerplexityBot, Google-Extended). Our practical guide: Robots.txt and AI crawlers.

llms.txt

File proposed in 2024 by Jeremy Howard to give LLMs a structured map of a site's content (at the root, Markdown format). Gradually adopted in 2025-2026 by SaaS players and publishers. Not a ratified standard, but a rising best practice: it eases AI agents' understanding of the site and clarifies priority content.

GPTBot, ClaudeBot, PerplexityBot

Specific crawlers of the major LLMs. GPTBot is OpenAI's (training and indexing), OAI-SearchBot is ChatGPT Search's, ClaudeBot is Anthropic's, PerplexityBot is Perplexity's. Each identifies through a dedicated user-agent. Blocking a training bot does not prevent the brand from being cited if mentioned elsewhere on the web.

Google-Extended

User-agent introduced by Google in September 2023 to let publishers block the use of their content by Bard and the Vertex AI Generative API, without blocking classic Search crawl. Enables a nuanced consent policy: "OK to appear in Google Search, not to train Gemini."

Structured data and schema

Structured data in JSON-LD or Microdata format, exposed in the `` or page body, explicitly describing the content (article, product, FAQ, recipe, organization). Standard maintained by Schema.org. Key lever to help LLMs interpret your page correctly without guessing.

Vector embeddings

Numerical representations (vectors) of text content, used by LLMs and RAG systems to compute semantic similarity between a question and candidate passages. It is the technology allowing AI to recognize that "AI search engine" and "LLM with RAG" refer to close concepts. Understanding embeddings means understanding why a good synonym can be enough to get found.

What results do GEO techniques actually deliver?

Academic research and market studies converge on one finding: the most effective GEO techniques are those that add verifiable proof to content. According to Aggarwal et al. (KDD 2024), adding citations boosts AI visibility by +37%, adding quotations by +33%, adding statistics by +22%. Cosmetic techniques (paraphrasing, keywords) are marginal, even negative.

Source: Aggarwal, Murahari, Rajpurohit et al., GEO: Generative Engine Optimization, KDD 2024 (analysis on 10,000 queries).

These gains translate into business. According to Adobe Analytics (March 2025), visitors from an AI source convert +31% better and show a 33% lower bounce rate. And 36% of Belgians say they have already bought based solely on an AI recommendation (Semactic & PingPrime, November 2025). GEO vocabulary translates into revenue.

How do GEO terms compare to each other?

To ease diagnosis, here is an overview of the main GEO terms, their family and learning priority by role (CMO, SEO manager, content manager). Terms tagged "priority 1" are the ones to master in the first month of any GEO initiative.

• Term|Family|Priority|Internal link
• GEO|Fundamentals|1|GEO guide
• AEO / AIO / LLMO|Fundamentals|2|GEO vs SEO vs AEO
• RAG|Fundamentals|2|RAG explained
• Citation capsule|Citability|1|Answer-First page
• Extractability|Citability|1|GEO content audit
• AI Overviews / AI Mode|Platforms|1|Appearing in AIO
• Perplexity|Platforms|1|Appearing in Perplexity
• Share of Model|KPIs|1|AI citation monitoring
• AI framing|KPIs|2|GEO and branding
• Answer-first|Techniques|1|Answer-First page
• Schema markup|Techniques|1|GEO Schema
• IDO method|Narrative authority|2|IDO method in action
• Authority capital|Narrative authority|1|Digital PR GEO
• llms.txt|Technical|3|Robots.txt and AI
• GPTBot / ClaudeBot|Technical|2|AI crawlers

For a condensed view aimed at executives, see our article The 10 GEO terms every CMO should know in 2026.

Frequently asked questions on GEO terms

What is the difference between GEO and AEO?

GEO (Generative Engine Optimization) targets generative engines: ChatGPT, Perplexity, AI Overviews, Claude, Gemini, which produce synthesized answers. AEO (Answer Engine Optimization) originally targeted narrower answer engines: Google featured snippets, voice assistants, People Also Ask. In 2026, the two disciplines converge heavily: content optimized for AEO (short answers, schema, FAQPage) serves as the base for any GEO strategy, but GEO adds the narrative authority and multi-platform citability dimensions.

Does GEO replace SEO?

No. GEO layers on top of SEO. According to Bain & Company (February 2025), 80% of users rely on AI summaries for at least 40% of their searches, but 60% of searches end without a click. SEO remains vital for the 40% of searches that end in a click; GEO becomes necessary to exist in the remaining 60%. A solid 2026 strategy weaves both disciplines into the same content, with a differentiated editorial structure.

What is RAG used for in a GEO strategy?

RAG (Retrieval-Augmented Generation) is the architecture that lets LLMs fetch fresh sources from the web before generating their answer. Understanding RAG means understanding that your brand can only be cited if it is retrieved by the system: your content must be indexable, structured and authoritative. According to AirOps, content citing third-party sources is +37% more visible in RAG answers. Without retrieval optimization, no AI visibility.

How do you measure a brand's AI visibility?

Three key indicators: Share of Model (share of mentions across 50 to 200 priority queries), citation rate (frequency of appearing as a cited source on Perplexity and AI Overviews), and qualified AI-referred traffic (visits from chatgpt.com, perplexity.ai, claude.ai measured in GA4). According to AirOps (2025), only 30% of brands remain stable from one run to the next: steering must be monthly. Our complete guide: AI citation monitoring.

What is a "citation capsule" and why is it central?

A citation capsule is a self-contained block of 40 to 80 words that contains a claim, a figure and its source, written in a format directly extractable by an LLM. It is the base unit of an Answer-First page. According to Princeton researchers, applying citation and quotation techniques boosts AI visibility by +30 to +37% (Aggarwal et al., KDD 2024). On the pages we support, generalizing citation capsules at the opening of every H2 has shown visible effect in 6 to 10 weeks.

Conclusion: an operational vocabulary, not jargon

GEO terms are not decorative jargon. Each names a precise mechanism (a crawler, a citation format, a KPI) that weighs on your brand's visibility in ChatGPT, Perplexity, AI Overviews, Claude or Gemini. Mastering this vocabulary gives you the means to brief properly, measure rigorously and arbitrate between levers. It also protects you against agencies reselling SEO under a GEO label.

To go further, three resources: our complete GEO guide that lays the foundations, our State of GEO in 2026 giving the year's figures and trends, and our case studies page showing concretely how these terms translate into results. If you prefer to move forward with support, our team offers a 12-week GEO sprint based on the IDO method: contact PingPrime or see our support offer.