890 posts · page 8 of 75.
"EU AI Act compliance for AI search ranking" sells a problem you mostly do not have. The Act regulates AI systems, not your store's visibility in them. Here are the real merchant duties, which are narrow.
An AI that says you have stock you sold out of sends customers to a dead end; one that says you are sold out when you are not loses sales you never see. Both trace to availability data that nobody wired to the truth.
Subscribe-and-save gives every product two true prices, and chatbots keep quoting the wrong one: the subscription rate as the one-time price, or a launch promo that died last spring. The fix is making both prices explicit, everywhere, as data.
You cannot force a language model to say anything, but you can make your real return policy the easiest, most corroborated fact in the room. For fashion brands, where returns decide the purchase, that is conversion infrastructure.
Une attaque d'avis coordonnée ou quelques pages parasites suffisent à faire basculer ce que les moteurs d'IA disent d'une marque, et le trafic suit. La défense se joue dans les citations : diagnostic, contre-preuve datée, signalement.
Quatre familles de stratégies SGE dominent le terrain européen : data-first, contenu expert, RP d'évidence et hybride instrumenté. Aucune ne gagne partout, et le vrai palmarès se lit dans les critères, pas dans les logos d'agences.
Quand un LLM répète qu'un tissu "bouloche" ou qu'un cuir est "synthétique", il cite ce qu'il trouve, vieux avis, fiche imprécise, supposition de catégorie. La correction passe par des faits matériaux vérifiables publiés là où la machine lit.
Gemini, Google Lens, and Circle to Search pull fragrance recommendations from Google's Shopping Graph, not from poetic copy. Here is the exact data layer a Shopify perfume or wine brand needs to get matched, cited, and recommended.
Merchants want AI engines to know every use case a product serves without cluttering the page design. There is a safe, designed channel for that and a spam violation that looks deceptively similar. This is the line, drawn precisely.
High-AOV purchases are researched across multiple sessions and engines before anyone clicks buy. The brands winning that research phase publish comparison depth, financing math, and risk-reversal evidence that AI engines can quote at every stage.
When ChatGPT designs a living room, it builds a shopping list from products whose dimensions, materials, and style it can actually read. Home decor brands win those list slots with structured data, not with prettier photography.
French AI answers are built from French sources. A brand targeting France with English pages and machine translation is invisible exactly where the queries happen, and the fix is a market build, not a language toggle.
