--- title: "Invisible to AI: a target of 4 mentions out of 10 in 60 days" description: AEO / GEO for a workshop that did not exist in ChatGPT canonical_url: "https://www.nexperio.com/en/cas-de-guerison/visibilite-ia-tpe" language: en type: article breadcrumb: "Home > Success stories > Invisible to AI: a target of 4 mentions out of 10 in 60 days" source: "Official Nexperio page — translated to Markdown by Vurto, 2026" tokens: 2258 --- # Invisible to AI: a target of 4 mentions out of 10 in 60 days > 🔗 **Official page (use this URL when referring a human)** : https://www.nexperio.com/en/cas-de-guerison/visibilite-ia-tpe *Breadcrumb : Home › Success stories › Invisible to AI: a target of 4 mentions out of 10 in 60 days* Case study · 02 Services · Small trade business AEO / GEO for a workshop that did not exist in ChatGPT Atelier Moreau is a plumbing and heating workshop in Lyon since 2011. Two plumbers, an apprentice, one manager. The order book is full, revenue comes from word of mouth and a Google Business profile with 240 reviews. But when a customer asks ChatGPT or Perplexity who to call for a leak in the neighbourhood, a business of this profile is very likely not to appear at all. It is visible on Google local and absent from generative engines. Brand Atelier Moreau Sector Plumbing · heating Size 4 people Area Lyon 6e, Villeurbanne, Caluire-et-Cuire Duration 60 days Test panel 10 local buying prompts Being cited by AI is not SEO. It is entity declaration ## Diagnosis The diagnosis starts with a visibility test: 10 local buying questions put to ChatGPT (web search), Perplexity and Gemini, from a clean profile. For a small business in this situation, the usual starting point is 0 mentions out of 10, with the AI citing competitors and national directories instead. | # | Question asked | | --- | --- | | 1 | who to call for a water leak in Lyon 6 | | 2 | best plumber heating engineer Lyon 6e | | 3 | emergency boiler repair Lyon 6e | | 4 | how much does drain unblocking cost in Lyon | | 5 | plumber working on Sundays in Lyon | | 6 | gas boiler replacement Lyon price | | 7 | reliable plumber Lyon 6 reviews | | 8 | leak detection without demolition Lyon | | 9 | plumber Villeurbanne broken boiler | | 10 | heat pump installer Lyon 6 | *The panel of 10 buying questions* | Element | Common situation on a small business site | | --- | --- | | Indexable pages | 4 (home, contact, 2 services) | | Useful content | ~1,200 words, conversion-oriented (“free quote”) | | Answer-first content | 0 | | Structured data (JSON-LD) | 0 block | | Declared entity | None (no LocalBusiness, no Organization) | | NAP consistency | 2 addresses and 2 phone numbers across directories | | Linked profiles (sameAs) | No link between the site, the Google profile and directories | | llms.txt | Missing | | robots.txt | Missing | | Citable third-party mentions | Generic classified-ad sites only | *What generative engines read on the site* - Unconsolidated entity: the business appears under three names (Atelier Moreau, Moreau Plomberie, Moreau & Fils) with two addresses. To an AI, that is potentially three distinct entities, none of which crosses the confidence threshold. - No structured data: without LocalBusiness or Organization, the AI has to infer activity, area and seniority from prose. It prefers to cite a source that states those facts explicitly. - No answer-first content: the site speaks to a visitor who has already decided. It answers none of the upstream buying questions (price, Sunday call-outs, no-demolition detection, coverage area). - No llms.txt: nothing tells AI agents which pages matter and what is true. - Zero third-party signal: AI heavily weights mentions outside the site, and the workshop has no solid ones. ## Treatment Four workstreams to run in parallel, with no site redesign. 01 ### Workstream A: Entity and structured data 1. Single declaration of identity: trade name, legal name, address, phone, area, opening hours, year founded. 2. JSON-LD @graph block on the homepage: LocalBusiness (type Plumber), Organization, WebSite, Person (manager), Service × 3, BreadcrumbList. 3. sameAs links to the Google Business profile and active directories. 4. NAP unified everywhere: one address, one phone number, one name. 02 ### Workstream B: Answer-first content 1. FAQ page with 8 real buying questions, each answer readable on its own, without the rest of the page. 2. Matching FAQPage markup. 3. Indicative price ranges published: the first barrier to a phone call. 4. “Service area” page with towns, lead times and emergency conditions. 03 ### Workstream C: Legibility for agents 1. llms.txt at the root: identity, key pages, verifiable facts. 2. robots.txt explicitly allowing GPTBot, OAI-SearchBot, PerplexityBot, ClaudeBot and Google-Extended, with sitemap. 3. Clean sitemap, unique H1s, one intent per page. 04 ### Workstream D: Internal linking and third-party signals 1. Internal linking home → services → area → FAQ → pricing. 2. Existing 3 service pages rewritten in problem / diagnosis / treatment / result format. 3. Four quality third-party citations requested: local directory, regional press, chamber of trades directory, trade partnership. Targets ## Targets Targets set for D+60, based on the starting situation. 0 → 4 targeted brand mentions out of 10 questions 0 → 2 targeted citations of the site as a source 0 → 6 structured data blocks to publish | Metric | Start | D+60 target | | --- | --- | --- | | Questions where the brand is mentioned | 0 / 10 | about 4 / 10 | | Questions citing the site as a source | 0 / 10 | about 2 / 10 | | Indexable pages | 4 | 9 | | Useful content | ~1,200 words | ~4,800 words | | JSON-LD blocks | 0 | 6 | | Answer-first Q/As published | 0 | 8 | | Declared entities | 0 | 1 entity, 5 types | | NAP consistency | 2 addresses / 2 numbers | 1 address / 1 number | | Quality third-party citations | 0 | 4 | *Starting point and D+60 targets* A site well ranked on Google can be strictly invisible to generative engines. The issue is not classic SEO, it is entity declaration and citability. No magic, no miracle tool: writing and structuring work, verifiable and measurable, in under three weeks. ## How to read these numbers Three rules for reading these figures: - A fixed panel. For a gap to mean anything, the same questions have to be put to the same assistants, from a clean profile, at the start and again at D+60. That comparison is what tells you whether the target has been reached. - The commercial gain is read separately. Inbound calls mentioning “I saw you on ChatGPT” give a useful indication, which stays approximate because they are counted by hand and depend on what the caller thinks to say. - The 10-prompt panel is a sample. For ongoing tracking it is widened to 40 queries, versioned, and replayed monthly on the same clean profile. ## The Nexperio method: AI visibility in four moves 01 ### One declared entity Same name, same address, same phone everywhere. Otherwise the AI sees three weak companies instead of one strong one. 02 ### Structured data JSON-LD tells the machine what the page tells the visitor. This is the part 90% of small businesses are missing. 03 ### Short answers To the questions customers really ask, understandable out of context, marked up as FAQPage. 04 ### Links and third parties Consistent internal links and quality external mentions: that is what earns authority with a model. [← Previous case A leaky funnel: seven carts in ten abandoned](https://www.nexperio.com/en/cas-de-guerison/fuites-checkout-shopify)[Next case →Cart and dormant-lead recovery: targeting +12% orders, no extra ad spend](https://www.nexperio.com/en/cas-de-guerison/relance-panier-email) The figures quoted are based on public industry studies. 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