Wildberries Scraper — Product Data, Prices & Supplier Info from Russia's #1 Marketplace

Extract structured product data from Wildberries.ru — Russia's largest online marketplace — by keyword, with no login and no coding. This Wildberries scraper searches any term (Russian or English), auto-paginates the catalog, and returns clean records with product name, brand, base & discounted prices in RUB, calculated discount, rating, review counts, supplier name/ID/rating, stock, delivery times, color and size variants, image URL, and the direct product link. Use it to scrape Wildberries for competitive intelligence, price monitoring, supplier discovery, and marketplace research.

Export every result to JSON, CSV, Excel, or API.

Built for e-commerce analysts, pricing teams, sourcing & wholesale buyers, dropshippers, brand managers, and market researchers who need reliable Wildberries data at scale.

⚠️ Access note (read first): Wildberries protects its catalog/search API with an in-house anti-bot system (wbaas). The API now returns HTTP 403 to datacenter and non-Russian IPs. For results you must use a Residential proxy with a Russian (RU) exit — set this in proxyConfiguration (see Input). See the Access & reliability section for the current status.

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🔎 Why scrape Wildberries?

Wildberries is the dominant e-commerce platform in Russia and the wider CIS region, with hundreds of millions of product listings across tens of thousands of brands and suppliers. It is the single best window into Russian online retail: what sells, at what price, from which supplier, with what ratings and delivery promises.

That data is extremely valuable for pricing, sourcing, and market-entry decisions — but Wildberries offers no public bulk export, and the catalog is served through an internal, parameter-heavy JSON API protected by an in-house anti-bot layer. Copying products by hand is slow and error-prone, and the raw API response is dense and awkward to parse. This Wildberries scraper does the hard part for you: it talks to the same catalog endpoint the website uses, flattens every useful field into a clean row, paginates automatically, and de-duplicates by product ID — handing you an analysis-ready dataset.

Common reasons people scrape Wildberries:

• Price & discount monitoring — track base vs. discounted prices and discount depth across competitors and categories.
• Supplier & manufacturer discovery — pull supplier name, ID, and rating for every product to build sourcing and B2B lead lists.
• Competitive assortment analysis — see which brands and products dominate a keyword or category.
• Market research & category sizing — analyze rating distributions, review volumes, and pricing bands before entering the Russian market.
• Product feed enrichment — refresh your own catalog with current Wildberries prices, ratings, and review counts.
• Review & reputation benchmarking — compare ratings and feedback counts across sellers and products.
• Dropshipping & resale research — find high-rating, high-stock products and the suppliers behind them.

✨ What this Wildberries scraper does

• ✅ Keyword search — enter any number of search terms (Russian or English, e.g. ноутбук, платье, наушники); each keyword is scraped independently.
• ✅ Automatic pagination — walks the catalog page by page (up to 100 products per page) until your limit is reached or results are exhausted, returning hundreds to thousands of products per keyword.
• ✅ De-duplication — products are de-duplicated by Wildberries product ID across pages, so you never get the same item twice.
• ✅ Rich product fields — captures identity (id, name, productUrl, mainImage), brand (brand, brandId, siteBrandId), pricing in RUB (priceBasicRub, priceProductRub, priceLogisticsRub, priceReturnRub, discountPercent), ratings & reviews (rating, feedbacks, reviewRating, nmFeedbacks, nmReviewRating), inventory (totalQuantity, soldQuantity), supplier (supplier, supplierId, supplierRating, supplierFlags), category taxonomy (root, kindId, subjectId, subjectParentId, semanticId), variants (colors, sizeVariants with per-size pricing and delivery) and delivery (deliveryDaysMin, deliveryDaysMax).
• ✅ Discount calculation — discountPercent is computed automatically from base vs. product price.
• ✅ Sort control — order results by most popular, highest rated, price ascending, price descending, or newest first.
• ✅ Language option — return native Russian product names or English translations where available.
• ✅ Export anywhere — download as JSON, CSV, or Excel, or pull via the Apify API and webhooks.
• ✅ Resilient by design — session rotation and automatic retries on soft blocks (HTTP 403/429/498) keep large jobs running when the catalog API is reachable.

Every field above is produced directly from the live Wildberries catalog response — this scraper only claims what it actually extracts.

🎯 Use cases

• E-commerce pricing teams — monitor competitor prices and discount strategy across Russia's #1 marketplace.
• Sourcing & wholesale buyers — discover suppliers and manufacturers by category, with supplier IDs and ratings.
• Dropshippers & resellers — find high-rating, in-stock products and the sellers behind them.
• Brand & MAP managers — detect resellers undercutting your minimum advertised price.
• Market researchers & analysts — size categories by price band, rating, and review volume.
• Data teams — enrich internal product feeds with fresh Wildberries prices, stock, and ratings.
• B2B lead generation — build merchant lists from supplier data for logistics, marketing, or fintech outreach.

📥 Input

Configure the run in the Apify Console UI or pass a JSON input via the API. Only the search keywords matter for most runs — everything else has sensible defaults. Set a Russian Residential proxy for results (see the access note above).

Field	Type	Description
queries	array of strings	Search keywords, exactly as you would type them on Wildberries (Russian or English both work). Leave empty to get a ready-made mixed sample of popular products across categories.
sort	string (enum)	Result order: popular (default), rate (highest rated), priceup (cheapest first), pricedown (most expensive first), newly (newest first).
language	string (enum)	Product-name language: ru (native Russian, default) or en (English translations where available).
maxItemsPerQuery	integer	Maximum products collected per keyword. Pagination runs until this cap is hit. Default 0 = unlimited (collect everything available). Max 10000.
proxyConfiguration	object	Apify Proxy settings. For results, use a Residential proxy with a Russian (RU) exit — Wildberries' anti-bot blocks datacenter and non-RU traffic on the catalog API.

Example input

{
  "queries": ["ноутбук", "платье", "наушники"],
  "sort": "popular",
  "language": "ru",
  "maxItemsPerQuery": 500,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": ["RESIDENTIAL"],
    "apifyProxyCountry": "RU"
  }
}

📤 Output

Each product becomes one clean, flat dataset record. Below is the exact shape produced by the scraper — one representative item (field values are illustrative of the structure the actor emits for every product):

{
  "id": 176765992,
  "name": "Платье женское летнее",
  "productUrl": "https://www.wildberries.ru/catalog/176765992/detail.aspx",
  "mainImage": "https://basket-01.wbbasket.ru/vol176/part17676/176765992/images/big/1.webp",
  "brand": "FASHION BRAND",
  "brandId": 312269064,
  "siteBrandId": 0,
  "priceBasicRub": 4000,
  "priceProductRub": 3036,
  "priceLogisticsRub": 0,
  "priceReturnRub": 0,
  "discountPercent": 24,
  "rating": 5,
  "feedbacks": 136,
  "reviewRating": 4.8,
  "nmFeedbacks": 136,
  "nmReviewRating": 4.8,
  "totalQuantity": 120762,
  "soldQuantity": null,
  "supplier": "FASHION BRAND",
  "supplierId": 250088821,
  "supplierRating": 5,
  "supplierFlags": 0,
  "root": 800442163,
  "kindId": 0,
  "subjectId": 654,
  "subjectParentId": 9214,
  "semanticId": null,
  "volume": 34,
  "weight": null,
  "pics": 12,
  "colors": [{ "name": "blue", "id": 16761035 }],
  "sizeVariants": [
    {
      "name": "S",
      "origName": "42",
      "priceBasic": 4000,
      "priceProduct": 3036,
      "warehouseId": 123,
      "deliveryDaysMin": 2,
      "deliveryDaysMax": 19,
      "optionId": 1139194125
    }
  ],
  "deliveryDaysMin": 2,
  "deliveryDaysMax": 19,
  "entity": "dress",
  "matchId": 0,
  "dist": 0,
  "isNew": false,
  "viewFlags": 0,
  "dtype": 4,
  "wh": 123,
  "panelPromoId": null,
  "meta": { "sitemap": null },
  "searchQuery": "платье",
  "sortOrder": "popular",
  "scrapedAt": "2026-11-02T00:00:00.000Z"
}

Field reference (main fields)

Field	Description
id	Wildberries product ID (unique; used for de-duplication).
name	Product name (Russian or English per the language input).
productUrl	Direct link to the product page on wildberries.ru.
mainImage	URL of the main product image on the Wildberries CDN.
brand / brandId / siteBrandId	Brand name and Wildberries brand identifiers.
priceBasicRub	Base (pre-discount) price in rubles.
priceProductRub	Final discounted price in rubles.
priceLogisticsRub / priceReturnRub	Logistics and return cost in rubles.
discountPercent	Discount %, computed from base vs. product price.
rating / feedbacks	Star rating and number of reviews.
reviewRating / nmFeedbacks / nmReviewRating	Weighted review rating and per-article review metrics.
totalQuantity / soldQuantity	Available stock and sold quantity (sold count present when provided).
supplier / supplierId / supplierRating / supplierFlags	Supplier (merchant) name, ID, rating, and flags.
root / kindId / subjectId / subjectParentId / semanticId	Category and taxonomy identifiers.
volume / weight / pics	Packaging volume, weight (when available), and image count.
colors	Array of available colors (name, id).
sizeVariants	Array of size options with per-size pricing, warehouse, delivery days, and option ID.
deliveryDaysMin / deliveryDaysMax	Minimum and maximum delivery days for the first variant.
entity / matchId / dist / isNew / viewFlags / dtype / wh / panelPromoId	Additional catalog metadata flags from the search response.
searchQuery	The keyword that produced this record.
sortOrder	The sort order used for the run.
scrapedAt	ISO timestamp of extraction.

Some fields populate only when Wildberries provides them for a given product (for example soldQuantity, weight, semanticId, and some supplier flags), so they may be null on part of the records — this is expected and reflects the source data, not a scraping error.

🔐 Access & reliability

Please read before running. Wildberries' in-house anti-bot (wbaas) now gates the catalog/search API hosts (search.wb.ru, u-search.wb.ru, catalog.wb.ru, card.wb.ru) behind a WAF challenge. As of the latest verification, those endpoints return a bare HTTP 403 to plain HTTP requests — from datacenter and non-Russian residential IPs alike — while the HTML front-end at www.wildberries.ru is served behind a JavaScript challenge page (HTTP 498).

What this means in practice:

• Use a Russian Residential proxy. A RU exit is the baseline requirement; datacenter IPs are blocked outright.
• Runs may return 0 items when the WAF is actively challenging the API. This is a Wildberries-side protection change, not a misconfiguration on your end. The actor logs this clearly and sets a descriptive run status so you can tell a block apart from a genuinely empty result set.
• If the API stays blocked for your proxy pool, the catalog can still be collected with a browser-based collector that solves the WAF challenge and reads the authenticated search response — a heavier, browser-driven approach than this pure-HTTP actor. Contact the author if you need that mode for your use case.

The scraper itself is correct and up to date: it targets the same catalog endpoint the website uses, converts kopeks to rubles, computes discounts, de-duplicates by ID, and paginates automatically. Throughput and success rate depend on Wildberries' current anti-bot behavior and the quality of your Russian residential proxy.

🔁 Pagination & scale

The scraper paginates the Wildberries catalog using the API's page parameter. For each keyword it requests page 1, extracts the products, then automatically advances to the next page as long as (a) the page returned a full batch (up to 100 products), (b) you have not yet hit your maxItemsPerQuery cap, and (c) it has not reached the internal safety ceiling of 100 pages. That means a single keyword can return up to ~10,000 de-duplicated products. Pagination stops cleanly when a page comes back short or empty (end of results). Set maxItemsPerQuery to 0 for unlimited collection, or to a specific number to cap each keyword. De-duplication by product id runs across all pages so results never repeat.

⚙️ How to use

1. Open the actor on the Apify Console and click Try for free (or Start).
2. Enter one or more keywords in queries (Russian or English).
3. Pick a sort order and language, and set maxItemsPerQuery (or leave 0 for everything).
4. Under proxyConfiguration, choose Residential proxy with country RU — this is required for the catalog API to respond.
5. Click Save & Run. Watch progress in the log; products stream into the dataset. If the log shows repeated HTTP 403/498, Wildberries' WAF is blocking your proxy pool (see Access & reliability).
6. When it finishes, export as JSON, CSV, or Excel, or fetch via the Apify API.
7. Automate it: run on a schedule, trigger via API, or push results to Make, Zapier, Google Sheets, or a webhook.

💡 Tips

• Always use a Russian Residential proxy. Wildberries' wbaas anti-bot blocks datacenter and non-RU IPs on the catalog API — a Russian residential exit is the only reliable path.
• Use Russian keywords for the most complete catalog coverage; English works but may return fewer matches.
• Sort by rate to surface the highest-rated products first, or pricedown / priceup to inspect premium vs. budget segments of a category.
• Cap large jobs with maxItemsPerQuery to control cost and runtime; leave it 0 only when you truly want the full result set.
• Watch the run log. A clean run logs products=N per page; a blocked run logs HTTP 403/HTTP 498 — that distinction tells you immediately whether it is a WAF block or an empty query.
• Combine keywords in one run to cover an entire category cluster in a single dataset.

❓ FAQ

Is scraping Wildberries legal? This Wildberries scraper collects only publicly available product listings — names, prices, ratings, supplier info, and delivery data that anyone can see on the site. It does not collect private or personal data. You are responsible for complying with Wildberries' Terms of Service and applicable laws (including GDPR and Russian Federal Law No. 152-FZ). Use the data for research, pricing, and sourcing, not for abuse.

Why did my run return zero products? Almost always Wildberries' anti-bot (wbaas) blocking the catalog API for your IP. First, switch proxyConfiguration to Residential with country RU — datacenter and non-Russian IPs are blocked. If the log shows repeated HTTP 403/HTTP 498, the WAF is actively challenging the API; this is a site-side protection change, not a bug in the actor. See Access & reliability.

Do I need proxies or a login? No login is ever required. Proxies are mandatory in practice: Wildberries blocks datacenter and non-Russian traffic on the catalog API, so a Residential proxy with a Russian (RU) exit is required for results. Configure this in proxyConfiguration.

How many products can it return, and how fast? When the catalog API is reachable, each keyword paginates up to ~10,000 de-duplicated products (100 per page, up to 100 pages), or until your maxItemsPerQuery cap. Throughput depends mostly on proxy quality and the marketplace's current anti-bot behavior.

Does Wildberries have a public API? There is no official public bulk product API. This scraper reads the same internal catalog endpoint the website itself uses and converts the dense JSON into clean, flat records — effectively a usable Wildberries API for product data when the endpoint is reachable.

What export formats are supported? JSON, CSV, and Excel downloads, plus programmatic access via the Apify API, dataset endpoints, and webhooks for integration with Make, Zapier, Google Sheets, or your own pipeline.

Can I filter or sort the results? Yes — use sort (popular, rate, priceup, pricedown, newly), language (ru/en), and maxItemsPerQuery. You can also post-filter the exported dataset by brand, supplier, price, rating, or category ID.

How fresh is the data? Every run fetches live data at request time, so prices, stock, ratings, and discounts reflect the marketplace at the moment the scraper runs — when the catalog API responds. Schedule recurring runs to keep a fresh feed.

Prices look off — are they in rubles? Yes. The source returns prices in kopeks; the scraper converts them to whole rubles (priceBasicRub, priceProductRub, etc.) and computes discountPercent for you.

Why are some fields empty? Fields like soldQuantity, weight, or semanticId are only present when Wildberries exposes them for a product. Empty values there are a property of the source data, not a bug.

🔗 Related scrapers

Building a cross-marketplace or retail price-intelligence pipeline? Pair this Wildberries scraper with:

• Tokopedia Scraper — Indonesia's leading marketplace.
• Lelong.my Scraper — Malaysian marketplace product data.
• AliExpress Product Scraper — global cross-border e-commerce.
• Oscaro Product Scraper — auto parts catalog data.
• Flipp Scraper — retail flyers and weekly deals.
• Zalando Scraper — European fashion catalog and pricing.

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Ready to pull live Wildberries product data? Set your keywords, choose a Russian residential proxy, and click Run — then export clean prices, suppliers, ratings, and variants as JSON, CSV, or Excel.