Nike Products Dataset – Product Info & Prices

Fashion dataset from nike

Looking for a comprehensive Nike products dataset? The Nike Products Dataset offers 9,600 verified product records from Nike.com — covering footwear, apparel, and accessories. It delivers a ready-to-use fashion ecommerce data CSV including product name, brand, model, SKU, color, price, availability, ratings, and images. Ideal for market research, price tracking, ecommerce analytics, or feeding into machine-learning and recommendation systems.

Key Features

• Rich Product Metadata: Each record includes url, name, brand, sku/model, color, price, currency, product_details, gender, product_type, category, availability, avg_rating, review_count, images, country, style_code, and unique identifiers like uniq_id, scraped_at. 
• CSV Format: Ready to use instantly, downloadable and easy to integrate into data pipelines without extra cleaning. 
• Large-Scale Coverage: Nearly 10,000 items covering multiple categories — footwear, apparel, accessories — giving broad insight into Nike’s catalog. 
• Includes Reviews & Ratings: A Subset of records comes with reviews and ratings, helpful for sentiment analysis or user-feedback research. 

Use Cases

• E-commerce Market Analysis: Track pricing, availability, and product mix over time to map Nike’s catalog strategy.
• Price & Competitor Monitoring: Use the dataset to compare pricing, styles, and availability across categories or seasons.
• Machine Learning & Recommendation Engines: Feed structured product data to build recommendation models, classification systems, or retail analytics tools.
• Fashion & Retail Research: Researchers and analysts studying consumer trends or clothing/footwear market segmentation.
• Business & Marketing Teams: Use data for catalog audits, inventory analysis, or content generation (e.g. blog posts, trend reports).

Who Benefits?

• E-commerce analysts & retail strategists reviewing product mix, pricing, category trends.
• Data scientists & ML engineers building recommendation engines, inventory prediction, and consumer behaviour models.
• Market researchers & fashion industry analysts studying trends in footwear/apparel, brand performance, and catalog breadth.
• Content creators & bloggers want product metadata to enrich articles about sneakers, fashion trends, or retail analysis.
• Students & academic researchers need a clean, real-world fashion dataset for study or project work.

Why Choose This Dataset Instead of Manual Scraping?

• Saves time — no need for complex scrapers or handling IP-blocks.
• Pre-cleaned data with verified metadata and consistent format — saves hours of cleaning.
• Comprehensive catalog snapshot — thousands of records, multiple categories, structured schema.
• Legal and technical ease — avoid scraping risks, rate-limits, and maintenance overhead.
• Quick setup — immediately usable CSV, perfect for rapid prototyping, research, or analytics

Country: US

Complexity: Medium

Dataset analytics:

Total records: 9600

Records with reviews: 1800

Total reviews count: 3700

Records with price: 6400

Records with color: 6400

Data points:

url, name, sub_title, brand, model, sku, color, price, currency, product_details, gender, product_type, tags, category, availability, avg_rating, review_count, country, product_style_code, recommended_count, reviews, images, uniq_id, scraped_at