Answered today by a language model from a live web search. Search results change, so a re-run can differ.
Asked of a language model without live browsing — what the model has absorbed about this market, not a search result fetched today.
Being listed on these puts you where an assistant reads before it answers. None of them does the work you do.
Put to a live web search — the pages an assistant reads before answering. Absent from these results it cannot cite you; present, it still might not.
The site’s Performance score of 89/100 shows it loads quickly, which is a clear advantage for visitors and conversions. However, the GSO score of 12/100 reveals a severe gap in AI-search readiness, meaning the site is unlikely to appear in AI-driven property searches. Implementing Offer schema to expose price and availability will directly improve GSO and unlock AI-driven traffic.
Ask it what a customer would ask you. It answers only with what is written on the pages of valmora-immobilier.fr.
Hello! I’m the assistant for Valmora Immobilier. What would you like to know?
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No Offer markup (price / availability) was detected. AI answers cite concrete price and in-stock facts.
Do: Include an Offer node (price, priceCurrency, availability) inside each Product.
No Organization or LocalBusiness markup was found. An AI answer will not recommend a shop it cannot identify as a business — this is the entity everything else hangs off.
Do: Add an Organization (or LocalBusiness, if you have a physical address) JSON-LD block to the homepage with name, url, logo, and your social profiles in sameAs.
Nothing on the page carries a date a machine can read. Generative engines prefer facts they can tell are current, and a store with no dates anywhere reads as undated rather than fresh.
Do: Add <time datetime="YYYY-MM-DD"> to new arrivals, restocks and journal posts, and dateModified to your Product and Article schema.
Main content is ~11 words — thin for AI-search coverage of what you sell.
Do: Add descriptive copy to collection/category pages covering materials, use-cases, sizing and buyer questions.
Automated snapshot generated by Tadaaah from public data. Re-run the audit for the latest version.