E-commerce data for retailers & marketplaces

If you resell other people’s products, your margin lives and dies on two questions: am I carrying the right assortment, and am I priced to win? ShopAPIS answers both. It returns price, availability, seller, buy_box_seller and full title/category for the same SKUs across 70+ marketplaces in 30+ countries, so a retailer or marketplace operator can match a rival’s price within the hour and spot the products competitors stock that you don’t.

A retailer competes on price and assortment — and both are knowable, because every competitor’s catalog and every competitor’s price is published on a page you can read as data.

The retailer’s two jobs-to-be-done

• Stay price-competitive. Track what named competitors charge for your overlapping SKUs and detect the moment they move. That feeds price monitoring, which streams price, was_price and availability on a schedule so your pricing team or rules engine reacts to a competitor markdown the same day instead of next week.
• Benchmark and grow assortment. Map a competitor’s full category catalog to find gaps — products they carry that you don’t, and where they have stockouts you can win. That is competitive intelligence: catalog-wide coverage of a category, not a single SKU lookup.

Why retailers buy data instead of scraping

Assortment work is broad, not deep — you need every SKU in a category across several competitors, refreshed often enough to catch promotions. Doing that in-house means maintaining parsers for each marketplace and absorbing block rates that commonly exceed 50% on price-sensitive targets — bots already make up 42% of all web traffic, two-thirds of it malicious, per Akamai  — then re-fixing everything on the next layout change. ShopAPIS normalizes price, currency, and availability across all of them, so your team compares apples to apples instead of reconciling a dozen scraper formats. Pricing analysts get a clean competitive feed; merchandisers get a category map.

Example: a competitive price gap

You query a category and ShopAPIS returns your competitors’ live offers, normalized:

{
  "query": "4k-monitor-27-inch",
  "category": "Monitors",
  "currency": "USD",
  "offers": [
    { "competitor": "BigBoxElectro", "marketplace": "walmart-marketplace",
      "price": 289.99, "was_price": 329.99, "availability": "in_stock" },
    { "competitor": "TechMart", "marketplace": "amazon",
      "price": 274.50, "buy_box_seller": "TechMart", "availability": "in_stock" },
    { "competitor": "ScreenHub", "marketplace": "ebay",
      "price": 312.00, "availability": "low_stock" }
  ],
  "your_price": 309.99,
  "lowest_competitor": 274.50,
  "fetched_at": "2026-06-05T08:30:00Z"
}

You are 35 dollars above the lowest competitor, one rival is on a markdown, and one is low on stock — a same-day pricing and inventory decision from a single record.

Marketplace operators have the same need, inverted

If you run a marketplace rather than sell on one, the job flips: you need to know how your sellers’ prices and assortment compare to the rest of the market so you can recruit the right merchants and keep your catalog competitive. The same normalized feed tells you where your platform is under-assorted in a category, which competing marketplaces undercut you on a popular SKU, and which sellers are pricing out of line — the supply-side view of the exact data a single retailer uses on the demand side. One feed, two vantage points on the same competitive surface.

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