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Womens Fashion E-commerce Product Data
Fashion & Apparel Trends
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About
E-commerce data from the ASOS platform, one of the biggest fashion platforms in the USA, offers a large-scale view into a multi-category retail environment. This collection of information, with over 60,000 data points, has been gathered from various online stores spanning multiple product categories. It provides valuable details on products, including names, pricing, and categories, making it a significant resource for understanding consumer trends in the fashion e-commerce sector.
Columns
- product_id: A unique identifier assigned to each product on Asos.com.
- brand_name: The name under which a specific product is marketed, such as "French Connection" or "ASOS DESIGN".
- title: The specific name of the product.
- current_price: The most recent price of the product, listed in USD.
- previous_price: The original price of the product before any discounts. This column has missing values for 67% of the entries.
- colour: The colour of the product. All data is missing for this column.
- currency: The currency used for pricing, which is consistently USD.
- rrp: The recommended retail price. This column has missing values for 21% of the entries.
- productCode: An identifier for the product.
- productType: The classification of the entry, such as "Product" or "MixMatchGroup".
Distribution
The data is available in a single tabular CSV file named
AsosWomenfashion.csv, with a size of 4.68 MB. The dataset contains 10 columns and approximately 43,600 valid records. It is not expected to be updated in the future.Usage
This dataset is well-suited for analysing consumer behaviour and identifying trends across various product categories. It can be used to train machine learning models for applications such as building product recommendation systems, forecasting demand, and optimising pricing strategies.
Coverage
The data originates from the ASOS e-commerce platform, which is described as the biggest fashion platform in the USA. The dataset focuses on the Asian market and includes a variety of categories such as electronics, fashion, home and garden, and sports.
License
CC0: Public Domain
Who Can Use It
- Data Scientists and Analysts: Can analyse consumer trends, purchasing patterns, and price sensitivity.
- Machine Learning Engineers: Can use the data to develop and train models for product recommendations or demand forecasting.
- Business Strategists: Can gain insights into the e-commerce fashion market to inform business decisions and pricing strategies.
- Academic Researchers: Can study e-commerce dynamics and consumer behaviour in online retail environments.
Dataset Name Suggestions
- ASOS Multi-Category E-commerce Data
- Women's Fashion E-commerce Product Data
- ASOS Product Catalogue and Pricing Analysis
- Retail Fashion Sales and Product Information
Attributes
Original Data Source: Womens Fashion E-commerce Product Data
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