A Walmart dataset sample of over 1000 products. Dataset was extracted using the Bright Data API.
product_id
: The unique identifier of the producturl
: URL representing the product linkproduct_name
: The name of the productfinal_price
: Price of the productcurrency
: Currency used for the product pricesku
: Stock Keeping Unit (SKU) for product identificationimage_urls
: Array of URLs representing product imagesmain_image
: The main product imagerating_stars
: Object representing the distribution of ratings in stars, from one star to five starstop_reviews
: Object representing top reviews, including negative and positive reviews. Each review includes rating and review textavailable_for_delivery
: Boolean indicating product availability for deliveryavailable_for_pickup
: Boolean indicating product availability for pickupbrand
: Text representing the product branddescription
: Text representing the product descriptionspecifications
: Array of objects representing product specifications. Each object includes name and valuecategory_name
: The name of the category associated with the productcategory_url
: URL representing the category link associated with the productroot_category_name
: The name of the root category associated with the productroot_category_url
: URL link associated with the productrelated_pages
: Array of related pages associated with the productbreadcrumbs
: Array of objects representing breadcrumb links. Each object includes URL and name
And a lot more.
This is a sample subset which is derived from the "Walmart Products (public data)" dataset which includes more than 371,000,000 companies.
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.
Uncover inventory shortfalls, spikes in product demand, and emerging trends among consumers. Leveraging the Walmart dataset, businesses can make strategic decisions to optimize inventory management, streamline restocking processes, and improve overall supply chain effectiveness.
Craft effective pricing strategies and develop adaptive pricing models by comparing similar products and categories across competitors. The Walmart dataset offers key insights to identify optimal pricing, spot pricing discrepancies, and guide data-driven pricing strategies.
Evaluate product reviews and ratings to gauge consumer feedback and ensure that the commercial offerings align with market expectations. The Walmart dataset empowers companies to capture consumer sentiment on specific products or the brand as a whole, facilitating informed adjustments to marketing and sales strategies.
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