A Zalando dataset sample of over 1000 records. Dataset was extracted using the Bright Data API.
domain
: The domain or category to which the product belongscountry_code
: The country code associated with the producturl
: The URL or link to view the full details of the product onlinesku
: The Stock Keeping Unit, a unique identifier for the productcondition
: The condition of the productgender
: The target gender for the productproduct_name
: The name or title of the productbrand
: The brand of the productdescription
: A detailed description of the productmanufacturer
: The manufacturer or producer of the productbadges
: Any special badges or labels associated with the productinitial_price
: The initial (original) price of the productfinal_price
: The final (discounted) price of the productdiscount
: The discount percentage applied to the productcurrency
: The currency in which the prices are listedinventory
: Information about the available inventory of the productis_sale
: Indicates if the product is currently on sale
And a lot more.
This is a sample subset which is derived from the "Zalando products" dataset which includes more than 9.7M records.
Available dataset file formats: JSON, NDJSON, JSON Lines, CSV, or Parquet. Optionally, files can be compressed to .gz.
Dataset delivery type options: Email, API download, Webhook, Amazon S3, Google Cloud storage, Google Cloud PubSub, Microsoft Azure, Snowflake, SFTP.
Update frequency: Once, Daily, Weekly, Monthly, Quarterly, or Custom basis.
Data enrichment available as an addition to the data points extracted: Based on request.
Develop a pricing strategy and implement dynamic pricing models by comparing Zalando products and categories with those of competitors. To identify inventory gaps, track increased demand for specific products, and highlight trending items within Zalando's product range. Enhance market strategies by analyzing key trends and customer preferences using the Zalando dataset.The Bright Initiative offers access to Bright Data's Web Scraper APIs and ready-to-use datasets to leading academic faculties and researchers, NGOs and NPOs promoting various environmental and social causes. You can submit an application here.