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Fashion E-commerce Trends Dataset
Fashion & Apparel Trends
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Free
About
This dataset contains product listings from two prominent online luxury fashion retailers, Net-a-Porter and Mr Porter. Net-a-Porter specialises in women's luxury fashion items, while Mr Porter focuses on men's designer fashion. The data was extracted directly from their websites and provides a current snapshot of prevailing trends, pricing structures, and product offerings within the luxury fashion e-commerce sector.
Columns
- brand: The name of the fashion brand or designer associated with the product. Key brands include Loro Piana and Tom Ford.
- description: A concise description of the product, highlighting its key features and characteristics.
- price_usd: The retail price of the product, presented in US dollars. Prices range from £14.00 to £170,000.00, with a majority of items priced below £8513.30.
- type: The category of the product, such as 'clothing', 'shoes', 'bags', or 'accessories'. Approximately 60% of products are 'clothing' and 21% are 'accessories'.
Distribution
The dataset comprises two CSV files. The Mr Porter CSV file contains 20,347 rows and 4 columns. The Net-a-Porter CSV file contains 23,161 rows and 4 columns. Each file represents distinct product listings, offering a substantial collection of luxury fashion items. The
brand column features 16,078 unique values.Usage
This dataset is ideal for various applications, including:
- Market Trends Analysis: Investigate prevailing trends in luxury fashion, including popular brands, product types, and price ranges.
- Brand Analysis: Explore the popularity and market presence of different luxury brands.
- Text Analysis: Utilise product descriptions for Natural Language Processing (NLP) tasks, such as sentiment analysis, feature extraction, or product recommendation systems.
Coverage
The dataset has a global regional coverage. It encompasses product data for both men's (Mr Porter) and women's (Net-a-Porter) luxury fashion segments, providing a broad demographic scope within the high-end retail market. The data provides a snapshot of current offerings, reflecting recent trends.
License
CC0
Who Can Use It
- Data Analysts and Researchers: For exploring market trends and consumer behaviour in luxury fashion.
- Machine Learning Engineers: For developing NLP models using product descriptions or predictive models for pricing and demand.
- E-commerce Businesses: For competitive analysis, product assortment planning, and understanding pricing strategies in the luxury segment.
- Fashion Industry Professionals: For insights into prevailing styles, brands, and product categories.
Dataset Name Suggestions
- Luxury Fashion Product Listings
- Net-a-Porter & Mr Porter E-commerce Data
- Designer Retail Product Insights
- Fashion E-commerce Trends Dataset
Attributes
Original Data Source: Net-a-Porter/Mr Porter Fashion Dataset
QUALITY