Wildberries Scraper — Product Data, Prices & Suppliers

Wildberries Scraper 🛍️🇷🇺 — Product Data, Prices, Ratings & Supplier Intelligence

Extract structured product and merchant data from Wildberries.ru — the largest online marketplace in Russia and the CIS region — with zero login and zero coding. This Wildberries scraper accepts search keywords, product IDs (nmId), or product URLs, paginates automatically up to 1,000+ products per query, and outputs clean records with product ID, name, brand, prices in RUB, calculated discount %, star rating, verified review counts, supplier name, supplier legal entity & INN tax ID, supplier ID, category taxonomy, product specifications, color & size variants, delivery times, and high-resolution image URLs.

Export your Wildberries data in bulk to JSON, CSV, Excel, XML, or via the Apify API for competitive pricing analysis, B2B supplier discovery, and CIS marketplace research.

Built for e-commerce analysts, pricing & revenue teams, wholesale & sourcing buyers, B2B lead-generation agencies harvesting verified Russian merchant contacts (supplierFullName + supplierInn), brand protection teams, and marketplace intelligence researchers.

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⚡ At a glance

Feature	Details
Target marketplace	Wildberries.ru — Russia & CIS e-commerce across fashion, electronics, home, beauty, kids & grocery
Targeting modes	Search keywords (queries), direct Wildberries product IDs (nmId) / product URLs, or automatic multi-category sample
Core data extracted	Product id (nmId), name, brand, productUrl, mainImage, RUB prices & discount %, rating, reviewRating, feedbacks, supplier, supplierId, supplierFullName, supplierInn, trademark, category IDs, colors, sizeVariants, options specs
Pagination & 1,000+ scale	Automatic multi-page catalog pagination + resilient CDN card/seller/feedback extraction supporting 1,000+ products per query
De-duplication	100% unique products per run — keyed globally on Wildberries article ID (id)
Speed & reliability	~50–100 products in 15–30 seconds; built-in dual-path extraction ensures results even when regional WAF challenges active search endpoints
Export formats	JSON, CSV, Excel (XLSX), HTML, XML, RSS, and live REST API / webhooks

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🔎 Why scrape Wildberries?

Wildberries is the dominant e-commerce ecosystem across Russia, Belarus, Kazakhstan, Armenia, Kyrgyzstan, and Uzbekistan, processing millions of daily orders across hundreds of millions of SKUs and hundreds of thousands of third-party merchants. Every product listing on Wildberries exposes two high-value layers of commercial intelligence:

1. Product, catalog & review intelligence — product title, brand, category hierarchy (entity, subjectId, subjectParentId), star rating, weighted review rating (reviewRating), verified feedback count (feedbacks), color/size variants, physical weight, and structured technical specifications (options).
2. Verified B2B merchant & supplier identity — unlike many Western marketplaces that hide seller identities, Wildberries publishes the merchant's store name (supplier), internal supplierId, registered legal entity name (supplierFullName, e.g. LLC / ООО or Individual Entrepreneur / ИП), taxpayer identification number (supplierInn), and registered trademark.

Collecting this data manually across thousands of product cards is slow and impractical. This Wildberries data extractor automates the entire process — paginating through catalog results, normalizing product specifications and merchant records into flat JSON rows, deduplicating by article ID, and exporting directly to Excel, CSV, or your analytics pipeline.

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✨ What this Wildberries scraper does

• ✅ Keyword, Product ID & URL targeting: Pass any number of search keywords (Russian or English, e.g. ноутбук, платье, наушники), numeric Wildberries article IDs (176765992), or product URLs (https://www.wildberries.ru/catalog/176765992/detail.aspx).
• ✅ Unlocked 1,000+ pagination per query: Automatically paginates until your maxItemsPerQuery target is reached (supporting 1000+ items per keyword or 0 for unlimited collection) without artificial 100-item clamps.
• ✅ Resilient dual-channel architecture: Combines live search pagination with automatic fallback to Wildberries' product card, seller registry, and feedback channels — ensuring reliable product, specification, rating, and supplier extraction even when Wildberries' regional anti-bot (wbaas) restricts search queries on non-RU IPs.
• ✅ Complete B2B supplier enrichment: Extracts supplier, supplierId, supplierRating, supplierFullName, supplierInn (Russian tax ID), and trademark for B2B lead generation and counterparty verification.
• ✅ Structured product specifications: Captures vendorCode, full description, weight, pics count, colors, sizeVariants, and key-value attribute options (material, country of origin, dimensions, compatibility).
• ✅ Sort & language controls: Order search results by popularity (popular), rating (rate), price ascending (priceup), price descending (pricedown), or newest arrivals (newly), and choose Russian (ru) or English (en) product labels.

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🎯 Use cases

Persona	How they use Wildberries Scraper
B2B Lead Generation & Fintech Teams	Extract verified Wildberries sellers (supplierFullName, supplierInn, supplierId, trademark) to build B2B outreach lists for seller financing, fulfillment, SaaS, and wholesale services.
Marketplace Sellers & Brand Managers	Benchmark competitor product assortments, review velocity (feedbacks), weighted star ratings (reviewRating), and specification positioning.
Sourcing & Wholesale Buyers	Discover manufacturers and high-volume suppliers across apparel, footwear, electronics, and home goods, complete with vendor codes and country-of-origin specs.
E-Commerce & Pricing Analysts	Monitor category pricing (priceBasicRub, priceProductRub, discountPercent), brand share, and SKU depth across the CIS retail market.
Catalog & Data Engineering Teams	Enrich internal PIM/ERP databases by passing lists of Wildberries article IDs (nmId) in queries to pull normalized titles, images, brands, and attribute tables.

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📥 Input parameters

Every input field is optional. Running with default prefill (queries: ["ноутбук"], maxItemsPerQuery: 50) finishes in ~15–25 seconds. Leaving queries empty automatically collects a diverse 100-product sample across 8 popular categories.

Parameter	Type	Default / Prefill	Description
queries	array<string>	Prefill: ["ноутбук"]	Search keywords (e.g. "ноутбук", "платье", "наушники"), Wildberries article IDs ("176765992"), or product URLs. Leave empty for an automatic multi-category sample.
sort	string (select)	"popular"	Result ordering: "popular" (Most popular), "rate" (Highest rated), "priceup" (Price: low to high), "pricedown" (Price: high to low), or "newly" (Newest first).
language	string (select)	"ru"	Product name language: "ru" (Russian native) or "en" (English translated where available).
maxItemsPerQuery	integer	0 (Prefill: 50)	Maximum products to collect per keyword. Set 0 for unlimited collection, or 1000+ for deep catalog extraction.
proxyConfiguration	object	{ "useApifyProxy": true }	Apify Proxy settings. Works out of the box on default proxy via resilient product/seller extraction; configure a Russian (RU) Residential proxy when direct search-ranking order is required.

Example 1 — Multi-keyword marketplace & supplier scrape (1,000+ items)

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

Example 2 — Direct article ID (nmId) & product URL enrichment

{
  "queries": [
    "176765992",
    "150000100",
    "https://www.wildberries.ru/catalog/100000100/detail.aspx"
  ],
  "language": "ru",
  "maxItemsPerQuery": 50
}

Example 3 — High-volume CIS category & supplier audit (1,000+ products)

{
  "queries": ["кроссовки", "рюкзак", "смартфон", "кофе", "игрушки"],
  "sort": "rate",
  "language": "ru",
  "maxItemsPerQuery": 1000,
  "proxyConfiguration": {
    "useApifyProxy": true
  }
}

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🔌 Integrations & automated B2B workflows

Connect Wildberries Scraper directly to your BI, CRM, or analytics pipeline:

• CRM & B2B Outreach (HubSpot, Salesforce, Bitrix24, AmoCRM): Export deduplicated seller records (supplierFullName, supplierInn, supplierId, trademark) directly into your CRM to power merchant acquisition campaigns.
• Google Sheets & Excel: Sync daily category snapshots, review counts (feedbacks), and rating trends into shared spreadsheets.
• Make, Zapier & n8n: Build automated workflows that monitor specific Wildberries nmId lists and alert your team on Slack or Telegram when ratings, stock, or prices change.
• Data Warehouses (ClickHouse, PostgreSQL, BigQuery, Snowflake): Stream flat JSON records via the Apify Dataset API into your analytics warehouse on an hourly or daily schedule.

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📤 Output & field reference

Each product is returned as a rich, flat JSON object. Below is a representative output record showing the unified schema:

{
  "id": 176765992,
  "name": "Чехол на Xiaomi Redmi 9A (Редми 9А)",
  "productUrl": "https://www.wildberries.ru/catalog/176765992/detail.aspx",
  "mainImage": "https://basket-12.wbbasket.ru/vol1767/part176765/176765992/images/big/1.webp",
  "brand": "Case M&A",
  "brandId": "8AAA959CF56F1FCE",
  "siteBrandId": null,
  "priceBasicRub": 4000,
  "priceProductRub": 3036,
  "priceLogisticsRub": 0,
  "priceReturnRub": 0,
  "discountPercent": 24,
  "rating": 5,
  "feedbacks": 136,
  "reviewRating": 4.9,
  "nmFeedbacks": 136,
  "nmReviewRating": 4.9,
  "totalQuantity": 120,
  "soldQuantity": null,
  "supplier": "ИП Крейтор М. О.",
  "supplierId": 1278369,
  "supplierRating": 4.9,
  "supplierFlags": 0,
  "supplierFullName": "Индивидуальный предприниматель Крейтор Михаил Олегович",
  "supplierInn": "673205522660",
  "trademark": "M&A Shop",
  "root": 207231123,
  "kindId": null,
  "subjectId": 390,
  "subjectParentId": 6258,
  "semanticId": null,
  "volume": null,
  "weight": 0.032,
  "pics": 3,
  "colors": [
    { "name": "черный", "id": null }
  ],
  "sizeVariants": [
    {
      "name": "0",
      "origName": "0",
      "priceBasic": 4000,
      "priceProduct": 3036,
      "warehouseId": 123,
      "deliveryDaysMin": 1,
      "deliveryDaysMax": 5,
      "optionId": 292731982
    }
  ],
  "deliveryDaysMin": 1,
  "deliveryDaysMax": 5,
  "entity": "Чехлы для телефонов",
  "matchId": 207231123,
  "dist": null,
  "isNew": false,
  "viewFlags": null,
  "dtype": null,
  "wh": null,
  "panelPromoId": null,
  "vendorCode": "CASE_6_REDMI9A_034",
  "description": "Этот чехол для Xiaomi Redmi 9A - истинная находка...",
  "options": [
    { "name": "Тип чехлов", "value": "Бампер защитный" },
    { "name": "Совместимость", "value": "Xiaomi Redmi 9A" },
    { "name": "Страна производства", "value": "Россия" }
  ],
  "meta": { "sitemap": null },
  "searchQuery": "ноутбук",
  "sortOrder": "popular",
  "scrapedAt": "2026-11-10T03:00:00.000Z"
}

🆔 Product identity, brand & media fields

Field	Type	Coverage	Description
id	integer	🟢 High (100%)	Unique Wildberries article number (nmId). Used as the global de-duplication key.
name	string	🟢 High (100%)	Product title in Russian or English.
productUrl	string	🟢 High (100%)	Direct link to the product detail page on Wildberries.ru.
mainImage	string	🟢 High (100%)	High-resolution WebP product image URL.
pics	integer	🟢 High (100%)	Total number of product gallery photos.
brand	string	🟢 High (~98%)	Brand or trademark name.
brandId / siteBrandId	string|integer	🟢 High (~95%)	Internal Wildberries brand identifier / hash.
vendorCode	string	🟢 High (~90%)	Seller's internal SKU / manufacturer part number (vendor_code).
description	string	🟢 High (~90%)	Product description text (up to 600 chars).

🏢 Supplier & B2B legal entity fields

Field	Type	Coverage	Description
supplier	string	🟢 High (100%)	Merchant / seller short display name (e.g. ИП Крейтор М. О. or ООО ...).
supplierId	integer	🟢 High (100%)	Unique Wildberries seller ID.
supplierFullName	string	🟢 High (~95%)	Full registered legal entity name of the merchant.
supplierInn	string	🟢 High (~95%)	Official Russian taxpayer identification number (ИНН) of the seller.
trademark	string	🟢 High (~90%)	Registered storefront trademark associated with the supplier.
supplierRating	number	🟡 Conditional	Seller or product family rating score.

⭐ Ratings, reviews & pricing fields

Field	Type	Coverage	Description
rating	integer	🟡 Conditional	Rounded star rating (1–5) for products with customer reviews.
reviewRating / nmReviewRating	number	🟡 Conditional	Exact decimal review valuation (e.g. 4.9) from verified buyers.
feedbacks / nmFeedbacks	integer	🟢 High (100%)	Total count of customer feedbacks/reviews on the product family.
priceBasicRub	integer	🟡 Conditional	Pre-discount base price in Russian Rubles (RUB).
priceProductRub	integer	🟡 Conditional	Final discounted selling price in Russian Rubles (RUB).
discountPercent	integer	🟡 Conditional	Calculated discount percentage (1 - priceProductRub / priceBasicRub).
totalQuantity / soldQuantity	integer	🟡 Conditional	Available warehouse stock and historical sold count when exposed.

🧩 Taxonomy, variants & specification fields

Field	Type	Coverage	Description
entity	string	🟢 High (100%)	Product category name (e.g. Чехлы для телефонов, Носки, Платья).
subjectId / subjectParentId	integer	🟢 High (100%)	Wildberries category and parent category IDs.
root / matchId	integer	🟢 High (100%)	Product family root ID (imt_id) linking color variants together.
weight	number	🟢 High (~80%)	Packaged product weight in kilograms (kg).
colors	array<object>	🟢 High (~85%)	Available color variants ({ name, id }).
sizeVariants	array<object>	🟢 High (~95%)	Size / option variants with optionId, name, and delivery day estimates.
options	array<object>	🟢 High (~95%)	Up to 15 structured product specification pairs ({ name, value }).
deliveryDaysMin / deliveryDaysMax	integer	🟢 High (100%)	Estimated minimum and maximum delivery days.
searchQuery / sortOrder / scrapedAt	string	🟢 High (100%)	Search provenance and ISO-8601 extraction timestamp.

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🔁 Pagination & 1,000+ scale

This Wildberries scraper is engineered to scale from quick 50-item checks to 1,000+ product extractions per run:

1. Unlocked maxItemsPerQuery: Set maxItemsPerQuery: 1000 (or 0 for unlimited) to collect 1,000+ unique products per keyword. Even when you run with empty queries (sample mode) and specify a custom maxItemsPerQuery (e.g. 1000), your explicit limit is honored in full.
2. Automatic sister-variant & multi-volume expansion: As products are collected, the scraper automatically discovers linked color/variant IDs in the same imt_id family and traverses active catalog volumes with 10× concurrent HTTP workers.
3. Strict article deduplication: Every product is deduplicated across all pages and queries by its numeric Wildberries id (nmId), guaranteeing 0 duplicates.

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⚙️ How to use

1. Open Wildberries Scraper in the Apify Console.
2. Enter your search keywords, numeric product IDs (nmId), or Wildberries URLs in queries (or leave empty for a mixed category sample).
3. Choose your preferred sort order and language (ru or en).
4. Set maxItemsPerQuery — e.g. 50 for a fast test run, 1000 for deep extraction, or 0 for unlimited.
5. Click Start, then export your dataset from Storage → Dataset as JSON, CSV, Excel, HTML, or XML.

Run via API (cURL, Node.js & Python)

cURL

curl -X POST "https://api.apify.com/v2/acts/haketa~wildberries-scraper/runs?token=YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "queries": ["ноутбук", "наушники"],
    "sort": "popular",
    "language": "ru",
    "maxItemsPerQuery": 500
  }'

JavaScript (Node.js)

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });
const run = await client.actor('haketa/wildberries-scraper').call({
    queries: ['платье', 'кроссовки'],
    maxItemsPerQuery: 500,
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(`Scraped ${items.length} unique Wildberries products`);

Python

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("haketa/wildberries-scraper").call(run_input={
    "queries": ["смартфон"],
    "maxItemsPerQuery": 500,
})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item["id"], item["name"], item.get("brand"), item.get("supplierInn"))

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💡 Pro tips

• Harvest verified B2B seller leads with supplierInn: Every record includes the merchant's official Russian taxpayer ID (supplierInn) and full legal name (supplierFullName). Deduplicate your exported Excel file on supplierInn to build an instant B2B registry of active Wildberries merchants.
• Look up exact SKUs by article number: You can paste a list of Wildberries article numbers (e.g. ["176765992", "150000100", "200000100"]) directly into queries — the scraper will fetch each exact product plus its sister color variants.
• Russian Residential proxy for live search rankings: While product cards, specifications, supplier legal records, and ratings work out of the box on default proxies, configuring a Russian (RU) Residential proxy in proxyConfiguration enables direct keyword-ranking pagination with live regional RUB checkout prices.

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⚠️ Limitations & notes

• Regional WAF on live search: Wildberries protects its dynamic search endpoint with an in-house regional WAF (wbaas) that blocks non-Russian and datacenter IPs (HTTP 403/498). When running without a Russian residential proxy, the actor automatically uses its resilient CDN catalog/seller/feedback extractor so your run still succeeds with rich product, specification, rating, and supplier records; in that mode, regional checkout price fields (priceBasicRub, priceProductRub) may be null because dynamic checkout pricing is region-gated.
• Product-dependent review scores: Products that have feedbacks: 0 naturally have rating: null and reviewRating: null.

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❓ FAQ

Do I need a Wildberries account or API key? No. All product, specification, rating, and supplier data is extracted from public Wildberries endpoints without logging in.

Will my run return data on default Apify Proxy? Yes! Unlike older scrapers that fail with 0 items when Wildberries' regional WAF (wbaas) blocks datacenter IPs, v1.2 automatically falls back to Wildberries' product card, seller legal registry, and feedback channels so every run delivers rich product and supplier data in seconds.

How many products can I collect in one run? You can set maxItemsPerQuery to 1000 (or 0 for unlimited) and pass multiple keywords to collect 1,000 to 10,000+ unique products in a single run.

Can I scrape by Wildberries article ID (nmId) or product URL? Yes. Put any 6–10 digit nmId or wildberries.ru/catalog/.../detail.aspx URL into queries, and the scraper will extract that product and its linked variants.

Are duplicate products removed? Yes. All records are deduplicated globally by numeric product id (nmId), ensuring 0 duplicates.

What export formats are supported? JSON, CSV, Excel (XLSX), HTML, XML, and RSS — available in the Apify Console or via the Apify REST API.

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🔗 Related scrapers

Expand your e-commerce and international marketplace data pipeline with these actors by haketa:

• Flipkart Scraper — Product prices, MRPs, discounts, ratings, and specs from India's leading marketplace.
• AliExpress Product Scraper — Global cross-border e-commerce products, prices, and seller ratings.
• Tokopedia Scraper — Indonesian marketplace product and merchant intelligence.
• Zalando Scraper — European fashion catalog, brand pricing, and discount tracking.

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📋 Changelog

v1.2 (2026-11)

• Unlocked 1,000+ deep pagination: Fixed sample-run limit clamping so explicit maxItemsPerQuery values (1000+) are always honored, removed the 10,000 schema ceiling, and scaled dynamic page limits.
• Resilient CDN product + seller + feedback extraction: Added automatic fallback to Wildberries' product card, legal seller registry (supplierFullName, supplierInn, trademark), and feedback channels when wbaas blocks search queries on non-RU IPs.
• Direct nmId & URL support: queries now accepts numeric Wildberries article IDs and product URLs in addition to keywords.
• Documentation upgrade: Added ⚡ At a glance table, emoji-grouped field tables with coverage indicators, and B2B seller enrichment documentation.

v1.1 (2026-10)

• Empty-input sample support: Added automatic 8-category seed queries when queries is left empty.
• Improved WAF status reporting: Added clear status messages and session rotation on HTTP 403/429/498 responses.

v1.0 (2026-07)

• Initial release with keyword search, RUB price conversion, supplier fields, and size/color variant mapping.

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⭐ Ready to extract Wildberries product and supplier data? Click Start and export clean JSON, CSV, or Excel datasets in seconds!