Wildberries Dataset
Use our Wildberries dataset to access product data from the Russian online marketplace, covering clothing, shoes, electronics, home goods, beauty, and groceries from thousands of sellers. Records include product names, brands, breadcrumbs, initial and final prices, membership prices, ratings, review counts, product variations, product details, and delivery options. Ideal for brands, marketplace sellers, and pricing analysts tracking ecommerce in Russia.
Available Wildberries Datasets
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Need real time Wildberries data? Use our Wildberries Scraper API
Wildberries Datasets Pricing
- Clean and validated
- Refreshed monthly
- JSON/CSV/Parquet
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Smart data updates
Access only "New Records" or "Updated Records," ensuring you pay only for what you need".
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Gain greater value by purchasing two or more datasets together, with exclusive discounts.
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Enriched Datasets
Save time and resources with pre-built datasets that combine multiple sources into one clean dataset.
Wildberries dataset sample
The dataset from Wildberries.ru comprises information about various products available on the e-commerce platform. Each entry includes details such as the product URL, unique identifier (SKU), category breadcrumbs for navigation, product name, average customer rating, number of reviews, image URL, brand, original and discounted prices, and a lot more.
Power AI Agents Instantly
Our Wildberries datasets are AI/LLM-optimized: clearly structured, well-documented, with code and recipes for easy LLM/chatbot integration.
Structured & Clean
Pre-processed data with consistent schemas, perfect for AI model training and inference.
Code Examples
Ready-to-use Python, Node.js, cURL, PHP, Go, Java, and Ruby snippets for easy integration with AI workflows.
Documentation
curl --request GET
--url https://api.brightdata.com/datasets/snapshots/{id}/download
--header 'Authorization: Bearer '
import requests
url = "https://api.brightdata.com/datasets/snapshots/{id}/download"
headers = {"Authorization": "Bearer "}
response = requests.get(url, headers=headers)
print(response.json())
const url = 'https://api.brightdata.com/datasets/snapshots/{id}/download';
const options = {method: 'GET', headers: {Authorization: 'Bearer '}, body: undefined};
try {
const response = await fetch(url, options);
const data = await response.json();
console.log(data);
} catch (error) {
console.error(error);
}
HttpResponse response = Unirest.get("https://api.brightdata.com/datasets/snapshots/{id}/download")
.header("Authorization", "Bearer ")
.asString();
require 'uri'
require 'net/http'
url = URI("https://api.brightdata.com/datasets/snapshots/{id}/download")
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Get.new(url)
request["Authorization"] = 'Bearer '
response = http.request(request)
puts response.read_body
Wildberries datasets tailored to your needs
Data subscription
Subscribe to access datasets at a significantly reduced cost.
File output formats
JSON, NDJSON, JSON Lines, CSV, Parquet. Optional .gz compression.
Flexible delivery
Snowflake, Amazon S3 bucket, Google Cloud, Azure, and SFTP.
Scalable data
Scale without worrying about infra, proxy servers, or blocks.
Cost savings
Customize any dataset using filters and formatting options.
Code maintenance
Datasets are maintained based on website structure changes.
Simplified integrations
Benefit from integrations with Snowflake and AWS.
24/7 support
A dedicated team of data professionals is here to help.
Leaders in compliance
Data is ethically obtained and compliant with all privacy laws.
Get structured and reliable Wildberries data
We’ll provide the data while you focus on the rest
High-volume web data
With our unblocking capabilities and round-the-clock IP rotation we ensure access to all data points on a website.
Data for immediate use
Every aspect of the data collection process is thoroughly validated as part of our robust data validation process.
Automated data flow
Create custom schedules to automate data delivery and watch the data flow seamlessly into your storage.
Wildberries dataset use cases
Product inventory
Pricing optimization
Continue improving
Brand and seller analysis
Wildberries Dataset FAQs
What data is included in the Wildberries dataset?
The dataset from Wildberries.ru comprises information about various products available on the e-commerce platform. Each entry includes details such as the product URL, unique identifier (SKU), category breadcrumbs for navigation, product name, average customer rating, number of reviews, image URL, brand, original and discounted prices, and a lot more.
Can I get updates for my purchased Wildberries dataset?
Yes, you can get updates to your Wildberries dataset on a daily, weekly, monthly, or custom basis.
Can I purchase a subset of the Wildberries dataset?
Yes, you can purchase a Wildberries subset that will include only the data points you need. By purchasing a subset, cost is reduced substantially.
In what format will I receive the Wildberries dataset?
You can choose one of the following formats: JSON, ndJSON, CSV, or XLSX.
Can I scrape Wildberries public data by myself?
If you don’t want to purchase a dataset, you can start scraping Wildberries data using our web scraping tool.
Can I get a data sample?
Yes, you can request sample data to evaluate the quality and relevance of the information provided. This is a great way to ensure it meets your needs before committing to a full dataset.
Can I request specific data points from the Wildberries dataset?
Yes, you can request specific data points from the Wildberries dataset tailored to your unique needs, ensuring you receive precisely the information you require for your projects.
Is it possible to integrate the Wildberries dataset directly into my existing systems?
Absolutely, the Wildberries dataset offers seamless API integration, allowing you to effortlessly integrate the data into your CRM, analytics tools, or any other systems you use, streamlining your operations.
How Wildberries datasets can help me?
Leverage our Wildberries dataset for diverse applications to enhance business strategies and market insights. Analyzing this dataset can facilitate an understanding of consumer preferences and trends within the e-commerce and online retail industry, empowering organizations to refine product offerings and marketing strategies. Access the entire dataset or customize a subset to align with your specific needs.
Popular use cases include conducting competitor analysis to understand market positioning, monitoring brand reputation through consumer feedback, and performing consumer market analysis to identify and predict emerging trends in e-commerce and online retail.