GEO • Generative Engine Optimization

GEO agency: get cited by AI

ChatGPT, Gemini, Claude, Perplexity and Google's AI Overviews no longer just rank pages: they retrieve passages, cross-check them and write an answer. We make sure yours is part of it, and gets cited.

Google
  • RAG
  • query fan-out
  • embeddings
  • schema.org @graph
  • llms.txt

Visualisation: an embedding space. The query (white dot) retrieves its nearest neighbours. The goal of GEO: that these are your contents (in red).

In short

What is GEO?

GEO (Generative Engine Optimization) covers the techniques that increase the likelihood that a generative engine retrieves your content, understands your business and cites it in its answer: ChatGPT, Gemini, Claude, Perplexity, Copilot, as well as Google's AI Overviews and AI Mode.

SEO puts you in the list of links; GEO gets you into the answer. The two complement each other, because generative engines draw heavily on search indexes.

At JSANCHEZ, the AI visibility audit is free and GEO packages start at €390 excl. VAT per month (see pricing).

  • 22/07/2026Google's AI Overviews and AI Mode launched in FranceSource: Google France
  • +40%visibility in generative answers, the maximum gain measured by the founding GEO studySource: Aggarwal et al., Princeton, arXiv 2311.09735
  • HTMLis what OpenAI, Anthropic and Perplexity crawlers read: they do not execute JavaScriptSource: Vercel, December 2024
Under the hood

Anatomy of a generative answer

Between your customer's question and the answer displayed, five steps decide who gets cited. GEO acts on each of them.

simplified trace • illustration
› prompt   "GEO agency for an SME in Lyon?"
› fan-out  [GEO pricing SME] [GEO agency reviews]
           [GEO vs SEO] [AI visibility audit]
› retrieve 120 passages → top-k = 12
› rerank   reliability · freshness · consensus
› answer   3 sources cited [1] [2] [3]
  1. prompt

    Intent

    “Which agency can make us visible in ChatGPT?” The question is interpreted with its context: language, location, conversation history.

    map your customers' real prompts

  2. query fan-out

    Decomposition

    The engine breaks the question down into sub-queries run in parallel: prices, reviews, comparisons, alternatives, proximity.

    cover every related intent

  3. retrieval

    Retrieval

    Search in a web index (Google, Bing or proprietary) and by vector similarity: only the closest passages (top-k) are kept.

    self-contained passages, readable in HTML

  4. rerank + grounding

    Source selection

    Passages are re-ranked according to the source's reliability, freshness and corroboration between independent sources.

    consistent entity, third-party evidence, dates

  5. generation

    Cited answer

    The LLM writes a summary and cites a handful of sources [1] [2] [3]. Being selected here means being recommended.

    quotable answer sentences, named brand

Our GEO stack

Six technical workstreams

No magic recipe: information engineering, applied to your brand.

01

Entity & Knowledge Graph

Your business must exist as an unambiguous entity: a schema.org JSON-LD graph linked by @id, sameAs properties pointing to your official profiles, Wikidata where relevant, identical name, address and phone number everywhere, and a complete Google Business Profile.

  • @graph
  • @id
  • sameAs
  • Organization
  • LocalBusiness
  • Wikidata
02

Quotable content

Passage-level optimisation: each section answers in one or two sentences, then goes into detail. One passage = one idea, understandable once extracted. Question headings, definitions, tables, dated and sourced figures.

  • answer-first
  • chunking
  • FAQPage
  • DefinedTerm
  • dated data
03

Fan-out coverage

We map the sub-queries that engines generate around your services (prices, reviews, comparisons, alternatives, proximity) and cover each intent with a dedicated page or passage.

  • query fan-out
  • semantic clusters
  • embeddings
  • intent mapping
04

AI crawler access

robots.txt configured user agent by user agent, server-side HTML rendering (OpenAI, Anthropic and Perplexity crawlers do not execute JavaScript), sitemap with lastmod, IndexNow, llms.txt file, server response time.

  • OAI-SearchBot
  • ChatGPT-User
  • ClaudeBot
  • Claude-SearchBot
  • PerplexityBot
  • Google-Extended
  • SSR
  • IndexNow
  • llms.txt
05

Authority & consensus

Models cross-check: the more consistently your brand is described by third-party sources (directories, press, comparison sites, reviews, forums), the more often it is selected. We work on co-citations and get incorrect information corrected.

  • co-citations
  • customer reviews
  • mentions
  • E-E-A-T
  • hallucinations
06

Measurement

A panel of prompts run every month on each engine, several times, because answers vary: citation rate, AI share of voice, position in the answer, accuracy. On the website side: traffic from chatgpt.com, perplexity.ai or gemini.google.com and AI crawler logs.

  • share of model
  • citation rate
  • GA4
  • server logs
  • Search Console
GEO pioneers

We apply GEO to ourselves first

Being a pioneer has to be proven. This website is our lab: everything we offer is live here, and anyone can check it.

  • llms.txt and llms-full.txt publishedA structured summary of the agency and a text version of our pages, for language models, following the standard proposed in 2024. See /llms.txt
  • 19 crawlers declared one by oneGooglebot, OAI-SearchBot, ChatGPT-User, GPTBot, ClaudeBot, Claude-SearchBot, PerplexityBot, Google-Extended, Applebot-Extended… each one explicitly allowed. See /robots.txt
  • An entity graph on every pageAgency, founder, services, FAQ and breadcrumb linked by @id, with company registration and VAT numbers to remove any ambiguity about who we are.
  • Answer-first pagesEvery page opens with an “In short” block written to be extracted as is by an answer engine.
  • AI, our second tradeWe also support companies with artificial intelligence: assistants, automation, training. We know from the inside how a model retrieves, filters and cites a source.
  • 20 years of disruptionOn the web since 2005: the shift to mobile, Core Web Vitals, BERT, Helpful Content, AI Overviews. Every disruption rewarded those who had prepared for it.
jsanchez.fr — terminal
$ curl -s https://www.jsanchez.fr/llms.txt | head -3
# Agence JSANCHEZ

> Agence de référencement fondée en 2016 sur la Côte d'Azur…

$ curl -s https://www.jsanchez.fr/robots.txt | grep -c "User-agent"
20

$ # excerpt of the JSON-LD graph on every page
{
  "@type": ["ProfessionalService", "Organization"],
  "@id": "https://www.jsanchez.fr/#agence",
  "foundingDate": "2016-05-09",
  "knowsAbout": ["Generative Engine Optimization (GEO)",
                 "Retrieval-Augmented Generation (RAG)",
                 "Query fan-out", …]
}
SEO and GEO

What changes technically

Technical comparison between SEO and GEO
SEO (search engine optimisation)GEO (generative engines)
Unit optimisedThe page (URL)The passage and the entity
MechanismInverted index and ranking algorithmsRetrieval (index + vector similarity), reranking, generation by an LLM
Key signalsRelevance, links, technical health, Google Business Profile, reviewsExtractable passages, entity consistency, structured data, co-citations, freshness
Visible resultList of links, Local PackA written answer citing a few sources
WhereGoogle, BingChatGPT, Gemini, Claude, Perplexity, Copilot, Google's AI Overviews and AI Mode
KPIsRankings, CTR, clicks, conversionsCitation rate, AI share of voice, accuracy, traffic from AI
What your customers ask

Questions, not just keywords

  • “Which agency should I choose to be visible in ChatGPT?”ChatGPT
  • “Best invoicing software for a tradesperson in 2026”Google AI Mode
  • “Boutique hotel with spa near Monaco”Gemini • Google Maps
  • “Comparison of accounting firms in Lyon”Perplexity • Claude
Our method

4 steps, measured every month

  1. AI baseline

    A panel of real prompts run on 5 engines, several times each: who is cited, from which sources, with which errors. This is your dated starting point.

  2. Entity & technical

    schema.org graph, sameAs, NAP consistency, Google Business Profile, robots.txt, HTML rendering, llms.txt and IndexNow.

  3. Content & fan-out

    Pages and passages covering each sub-query, answer first, dated and sourced figures, comparison tables.

  4. Authority & monitoring

    Co-citations, reviews, third-party mentions. Monthly report: citation rate per engine, accuracy, traffic from AI.

GEO pricing

Our GEO packages

Monthly prices excluding VAT. The AI visibility baseline is free.

LOCAL GEO

from 390 € excl. VAT / month
  • Local visibility
  • AI baseline: panel of prompts on 5 engines
  • schema.org entity graph (@id, sameAs)
  • Google Business Profile and NAP consistency
  • Answer-first content and fan-out coverage
  • AI robots.txt, llms.txt and IndexNow
  • Monthly report: citation rate and accuracy

NATIONAL GEO

from 490 € excl. VAT / month
  • Nationwide visibility
  • AI baseline: panel of prompts on 5 engines
  • schema.org entity graph (@id, sameAs)
  • Google Business Profile and NAP consistency
  • Answer-first content and fan-out coverage
  • AI robots.txt, llms.txt and IndexNow
  • Monthly report: citation rate and accuracy

INTERNATIONAL GEO

from 690 € excl. VAT / month
  • International visibility
  • AI baseline: panel of prompts on 5 engines
  • schema.org entity graph (@id, sameAs)
  • Google Business Profile and NAP consistency
  • Answer-first content and fan-out coverage
  • AI robots.txt, llms.txt and IndexNow
  • Monthly report: citation rate and accuracy
Glossary

The words of GEO

Twelve concepts to understand how an AI chooses its sources.

GEO
Generative Engine Optimization: optimising a brand's visibility in the answers of generative engines. Related terms: AEO, LLMO, “SEO for AI”.
LLM
Large Language Model: a language model trained on vast corpora (GPT, Gemini, Claude, Mistral…), able to understand and generate text.
RAG
Retrieval-Augmented Generation: the model first retrieves documents (web, internal database), then writes its answer based on them.
Grounding
Anchoring an answer in verifiable sources, displayed as links. This is the mechanism that produces citations.
Query fan-out
Breaking a question down into sub-queries run in parallel, used in particular by Google's AI Mode.
Embedding
Representation of a text as a vector: two texts with close meanings have close vectors. This is the basis of semantic search.
Chunk
A passage of a page indexed and retrieved separately. A good chunk can be understood on its own, without the rest of the page.
Reranking
A second, finer ranking of the retrieved passages, just before the answer is generated.
Entity
An unambiguously identified object (company, person, place) in a knowledge graph, linked to its attributes and profiles (sameAs).
Share of model
The share of answers from a panel of prompts in which your brand is cited or recommended. The AI equivalent of share of voice.
Hallucination
False information produced by a model (opening hours, prices, services). It is corrected by making the right information consistent and plentiful across sources.
llms.txt
A Markdown file placed at the root of a website, summarising for language models what they need to know and where to find the key pages.

GEO delivers its best results when backed by solid SEO, Google Ads campaigns for urgent searches and a fast, well-structured website. At JSANCHEZ, all three are run by the same person.

Free baseline

What does AI say when asked about you?

We ask ChatGPT, Gemini, Claude, Perplexity and Google your customers' questions, and show you who is cited instead of you.

Frequently asked questions

GEO: your questions

GEO covers the techniques that increase the likelihood that a generative engine (ChatGPT, Gemini, Claude, Perplexity, Copilot, Google's AI Overviews and AI Mode) retrieves your content, understands your business and cites it in its answer. The term comes from a research paper published at the end of 2023 by researchers at Princeton University and their partners. It is also called AEO or LLMO.
No. Generative engines rely largely on search indexes (Google, Bing) and on sources considered reliable: a well-ranked website remains the foundation. GEO adds a layer: passages that are easy to extract and cite, an entity that is consistent everywhere on the web and third-party evidence that corroborates it.
Yes. Google launched AI Overviews and AI Mode in France on 22 July 2026. AI Mode uses the query fan-out technique: it splits the question into sub-topics and runs several searches in parallel. Websites that cover these sub-topics well are more likely to be cited.
We build a panel of questions your customers really ask (“best … in Lyon”, comparisons, prices, alternatives) and submit them to each engine, several times, because answers vary from one session to the next. We record whether you are cited, in what position, with what information and which sources. This survey is included in the free AI visibility audit.
Rarely. Above all, you need a fast website whose content is present in the HTML: OpenAI, Anthropic and Perplexity crawlers do not execute JavaScript. Add pages that answer clearly, schema.org structured data, a robots.txt that allows AI crawlers and an llms.txt file. We also build websites designed for GEO from the start.
Entity corrections (Google Business Profile, directories, structured data) are often taken into account within a few weeks by engines that search in real time. Gains on competitive questions take several months. No agency can guarantee a citation: we measure progress every month from a dated starting point.
The AI visibility audit is free. GEO packages start at €390 excl. VAT per month for local visibility, €490 excl. VAT for national and €690 excl. VAT for international. You receive a precise proposal after the audit.
No. Our head office is in Vence, but we support businesses across France, in Monaco and internationally, in English and in French, by video call or in person.