Guides
Product data, answered.
How to get, normalize and use product data from many online stores. Each guide answers one question, explains the approach without assuming any vendor, and compares the tools that can do it, StoreRouter included.
How do you normalize product data from different retailer websites into one schema?
Define one target schema with three levels (product, variant, and each store's offer), extract every store from its most structured source first (JSON-LD, then platform data such as Shopify's product JSON, then HTML), and map each field with explicit rules for prices, availability, sizes, colors and categories. Then match the same item across stores by GTIN, falling back to brand plus part number, and re-extract on a schedule, because stores change their pages and a normalized record goes stale.
Updated November 6, 2026
How do you build a price comparison tool with live product data from multiple stores?
A price comparison tool has four parts: a way to find offers for a product across stores, a matcher that decides which offers are the same item (by GTIN, then brand and model number), a normalizer that compares like with like (same variant, currency, sale and shipping terms), and a refresh loop that re-checks a price before anyone sees it. You can scrape each store and build all four, use an extraction API for the fetching, or start from a product data API that already searches and normalizes many stores, and put your matching, ranking and interface on top.
Updated November 6, 2026