Wildberries product data API

ShopAPIS returns structured Wildberries product data — current and pre-discount price in RUB, brand, full category tree, size and color variants, per-warehouse stock, supplier ID, rating and review count, and the WB article (SKU) — as normalized JSON. Wildberries is the single largest Russian-language data asset in the region: a massive SKU catalog with rich attributes spanning fashion, FMCG and electronics. ShopAPIS reads its public catalog and supplements the official seller API  into one schema.

Why Wildberries data is hard to get

Wildberries ships an official seller API, but it has no SDK and exposes only the merchant’s own catalog. The official WB API  uses read/write tokens for a seller to manage their own listings, prices and stock — it does not return a rival brand’s price history or competitor warehouse stock. Building a market-wide dataset means parsing the public catalog, which runs medium-to-high anti-bot difficulty with header and session checks (community parsers do work against it). The Wildberries-specific challenge is the discount stack and the size matrix: WB applies aggressive layered discounts (supplier discount plus the WB wallet discount), and a single apparel article fans out into many sizes, each with its own stock state across multiple regional warehouses. A naive scrape that reads one price and one stock flag loses both the true paid price and which sizes are actually buyable. ShopAPIS unpacks the full size/color variant matrix, the layered discount, and warehouse-level stock.

Data fields returned

• Pricing — base price, discounted price, WB wallet price, currency (RUB), discount %.
• Variants — size and color variants, each with its own stock state and SKU.
• Availability — total stock plus per-warehouse buckets.
• Seller/supplier — supplier name and ID, supplier rating.
• Catalog — title, brand, full category tree, structured characteristics.
• Social proof — average rating and review count.
• Identifiers — WB article (nm ID / SKU), barcode, product URL.
• Images — full gallery URLs.

Sample response

{
  "marketplace": "wildberries",
  "domain": "wildberries.ru",
  "country": "RU",
  "sku": "184729361",
  "title": "Кроссовки кожаные демисезонные",
  "brand": "RESTIME",
  "category": ["Обувь", "Женщинам", "Кроссовки"],
  "price": { "base": 6890, "discounted": 3445, "wb_wallet": 3273, "currency": "RUB", "discount_pct": 50 },
  "supplier": { "name": "ООО Рестайм", "id": "92841", "rating": 4.7 },
  "rating": 4.6,
  "review_count": 8420,
  "variants": [
    { "size": "37", "color": "Чёрный", "stock": "in_stock" },
    { "size": "38", "color": "Чёрный", "stock": "low" },
    { "size": "39", "color": "Чёрный", "stock": "out_of_stock" }
  ],
  "warehouses": { "Коледино": "high", "Электросталь": "low" },
  "images": ["https://basket-12.wbbasket.ru/vol1847/part184729/184729361/images/big/1.webp"],
  "url": "https://www.wildberries.ru/catalog/184729361/detail.aspx",
  "fetched_at": "2026-06-05T10:18:00Z"
}

Markets and domains covered

Use cases

• Apparel sell-out tracking — read the size matrix to see which sizes are selling out across warehouses as a demand signal. See inventory tracking.
• True-discount monitoring — separate WB wallet price from headline discount to track real paid price. See price monitoring.
• Brand and assortment intelligence — benchmark a brand’s WB catalog against Ozon and Yandex Market. See competitive intelligence.
• Review analytics — aggregate ratings and review counts across the largest RU catalog. See review analytics.

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