Target products dataset
target.com · CSV
The Target Products Dataset is a robust collection in CSV format, featuring 1.3 million product records sourced from Target's online platform. This dataset contains rich details on a wide range of products, including product titles, URLs, pricing, availability, and more. It is an ideal resource for businesses, researchers, and data scientists interested in analyzing retail trends, product availability, and pricing strategies.
Key Data Fields:
- Title: Name of the product.
- URL: Direct link to the product page.
- Brand: The brand associated with the product.
- Main Image: URL of the main product image.
- SKU: Unique Stock Keeping Unit identifier.
- Description: A structured product description.
- Raw Description: The original product description before any processing.
- GTIN13: Global Trade Item Number (GTIN) in 13-digit format.
- Currency: The currency in which the product is priced.
- Price: Price of the product.
- Availability: Availability status of the product (e.g., in stock, out of stock).
- Available Delivery Method: Methods through which the product can be delivered.
- Available Branch: Information on availability at specific store locations.
- Primary Category: The main category to which the product belongs.
- Sub Category 1, 2, 3: Further sub-categorization of the product.
- Images: URLs to additional product images.
- Raw Specifications: Unprocessed specifications of the product.
- Specifications: Structured product specifications.
- Highlights: Key highlights and features of the product.
- Raw Highlights: Unstructured highlights before processing.
- Uniq ID: A unique identifier for each product.
- Scraped At: The timestamp indicating when the data was collected.
- Retail Analytics: Analyze pricing trends, brand popularity, and product availability across categories.
- Product Categorization: Study the classification of products into primary and sub-categories.
- E-commerce Analysis: Use this dataset for consumer behavior studies, inventory management, or competitive analysis.
- Recommendation Systems: Build product recommendation engines using product features, pricing, and availability data.
Fields
title, url, brand, main_image, sku, description, raw_description, gtin13, currency, price, availability, availableDeliveryMethod, available_branch, primary_category, sub_category_1, sub_category_2, sub_category_3, images, raw_specifications, specifications, highlights, raw_highlights, uniq_id, scraped_at