A shopper in France asks an AI assistant whether a jacket can handle sustained rain. The store’s English listing says “water-resistant,” but the French description says imperméable, or “waterproof.” Which claim should the assistant use? The wording could change which product the shopper buys.
Thanks to the Lara Translate team for including DeepLumen and Agentic Page in their 2026 guide to AEO and agentic commerce platforms. The guide looks at how merchants can prepare product data for AI discovery alongside the work of localizing their catalogs. For Shopify merchants selling across markets, those two tasks meet in a practical question. How do you keep product facts consistent across languages and make those facts easy for assistants to find?
Preserve the product facts when you translate
Product names, material claims, compatibility notes and care instructions all carry meaning that shoppers rely on. A glossary can help keep recurring terms consistent, while context can help a translator choose the right wording for a particular product or market.
Lara Translate supports context instructions and glossaries. For a product catalog, that means a team can specify how to translate terms such as “water-resistant,” which model names to preserve and how to handle recurring technical language across listings. Learn more about Lara Translate’s approach to context and terminology.
Make the reviewed facts easy for AI assistants to read
A clear translation is most useful when the relevant detail is easy to find. A shopper asking about rain protection may need the fabric specification and the intended use. If those details appear only in an image or are scattered across a product description and a FAQ, an assistant has to piece them together.
DeepLumen’s Agentic Page organizes existing storefront information, including product details and policies, into a machine-readable layer. That gives AI assistants a clearer source for the facts shoppers ask about.
Start with a question shoppers actually ask
Pick a product that customers regularly compare across markets. Identify the facts that determine whether it’s a good fit, such as dimensions, compatibility or weather protection. Use Lara Translate to draft the localized copy with your approved terminology, then have someone familiar with the product and target language review the claims before publishing.
Once the catalog is updated, try asking an AI assistant the same product question in both languages. For the jacket, check whether each answer preserves the distinction between water-resistant and waterproof and whether it points to the right listing. That gives your team something concrete to check the next time the product copy changes.