A Zara products dataset sample of over 1000 records. Dataset was extracted using the Bright Data API.
category_id
: The identifier for the category to which the product belongsproduct_id
: A unique identifier or code associated with the productproduct_name
: The name or title of the Zara productprice
: The regular or original price of the productcurrency
: The currencycolour_code
: The color code associated with the productcolour
: The color or colors available for the productdescription
: A textual description of the productsize
: The size or sizes available for the productsection
: The section of the store or website where the product is locatedproduct_family
: The family or category to which the product belongsproduct_subfamily
: The subfamily or sub-category to which the product belongscare
: Information about the care or maintenance of the productmaterials_description
: A description of the materials used in the productmaterials
: Information about the materials used in the productdimension
: The dimensions or size measurements of the productlow_on_stock
: Indicates whether the product is low on stock (boolean: True/False)availability
: Indicates whether the product is currently available (boolean: True/False)image
: An image representing the Zara productsku
: The stock keeping unit or unique identifier associated with the producturl
: The URL or link to the product page
And a lot more.
This is a sample subset which is derived from the "Zara products" dataset which includes more than 999K 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.
Get the full Zara products dataset.
Create a pricing strategy and dynamic pricing models by comparing similar Zara products and categories with competitors. This will help optimize pricing and ensure competitiveness in the market. Identify inventory gaps in Zara's product range, track rising demand for specific items, and pinpoint products that are trending with consumers to better align stock levels with market needs. Utilize the Zara dataset to conduct market strategy analysis, uncovering key trends and customer preferences to inform decision-making and improve product offerings.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.