Commerce data guide / 2026
Ecommerce Product Data API for AI in 2026
Commerce pages use different names and layouts for the same concepts: title, description, price, variants, availability, images, and category. One semantic response makes cross-store research and product-aware agents considerably easier to build.
Quick answer
Normalize public product pages across storefronts.
Send a supported Amazon, Shopify, WooCommerce, App Store, or Google Play URL and receive a semantic product entity or catalog feed. Prices use integer minor units so downstream systems can compare values without floating-point errors.
curl --get 'https://extractor.sh/api/extract' \
--data-urlencode 'url=https://www.amazon.de/echo-dot-2022/dp/B09B8X9RGM' \
--data-urlencode 'format=json'Available data
What you can extract
- Public product titles, descriptions, URLs, and images
- Integer minor-unit prices with separate display text
- Variants, availability, ratings, and attributes when exposed
- Catalog or search feeds for supported storefront pages
AI workflows
Where normalized data helps
- Shopping and product research agents
- Cross-store catalog normalization
- Competitive assortment analysis
- Commerce RAG pipelines
AI-ready output
Markdown for models. JSON for systems.
Raw HTML consumes tokens on navigation, scripts, styling, and interface labels. Clean Markdown keeps the readable hierarchy for LLM prompts and RAG chunks. Normalized JSON is better when your application needs an explicit semantic type, source, author, publication date, media, attributes, and collection items.
Always retain the canonical URL from the response. AI-generated summaries should remain traceable to the public source, especially when the underlying page can change.
Boundaries
Public data only
- Only public catalog data is included.
- Checkout, customer, seller, order, and administrative data is unavailable.
- Availability and price can change after a response is cached.
extractor.sh does not bypass CAPTCHAs, login walls, paywalls, access controls, or regional restrictions. Review the source’s terms and applicable law before collecting or reusing data.