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Wish Product Ratings & Sales Data
Product Reviews & Feedback
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"No reviews yet"
Free
About
This dataset focuses on the sales performance of summer clothing products on the Wish e-commerce platform. It provides insights into top-selling products, including their ratings and sales data, which is often not available in other datasets. The primary purpose is to enable users to explore correlations and patterns related to product success. This preview dataset can help in understanding factors that drive sales, such as price, product quality, and seller performance, thereby facilitating the study of e-commerce trends and consumer behaviour.
Columns
The dataset contains 13 columns, offering detailed metrics on product listings, ratings, and sales:
- merchantid: A unique identifier for each merchant.
- listedproducts: The number of products listed by a merchant, typically ranging from 1 to 15. The average is around 1.64.
- totalunitssold: The total number of units sold by a merchant, with values ranging from 100 to 120,000. The average is approximately 7,120 units.
- meanunitssoldperproduct: The average units sold per product, with values typically between 100 and 100,000. The average is around 4,410 units.
- rating: The average rating of a merchant's products, ranging from 2.33 to 5.00, with an average of 4.04.
- merchantratingscount: The total number of ratings a merchant has received, from 0 to over 2 million. The average is 22,000 ratings.
- meanproductprices: The average price of products, generally ranging from £1 to £49, with an average of £8.63.
- meanretailprices: The average original retail price of products, with values up to £252. The average is £24.8.
- averagediscount: The average discount applied to products, expressed as a percentage, ranging from -18% to 97%. The average discount is 28.7%.
- meandiscount: Identical to averagediscount in content.
- meanproductratingscount: The average number of ratings per product, ranging from 0 to over 20,000. The average is 923 ratings.
- totalurgencycount: This column indicates an urgency count, but has a significant number of missing values (59% missing). For valid entries, values range from 1 to 6.
- urgencytextrate: This column shows an urgency text rate, also with 59% missing values. For valid entries, values range from 14% to 100%.
Additionally, the dataset includes
title and title_orig columns. The title column may contain non-ASCII Latin characters due to the data being scraped with French settings. The title_orig column holds the original, base title of the product.Distribution
The dataset is provided as a CSV file (
computed_insight_success_of_active_sellers.csv) with a size of 78.85 kB. It contains 958 records across 13 columns.Usage
This dataset is ideal for:
- Validating marketing hypotheses: For example, studying the impact of price drops (discounted price versus original retail price) on sales.
- Identifying top product categories: Discovering which categories sell best on the Wish platform.
- Analysing product quality and success: Investigating the relationship between product ratings and sales performance.
- Understanding price influence: Examining how pricing strategies affect product success.
- E-commerce research: Looking for patterns and correlations within e-commerce sales data.
Coverage
The data was collected from the Wish platform, specifically focusing on products displayed when searching for "summer" items. The data collection was performed with French language settings, which explains the presence of non-ASCII characters in some titles. The dataset's expected update frequency is quarterly. There are no specific notes on geographic or demographic scope beyond the French localisation.
License
The dataset is provided under the Attribution 4.0 International (CC BY 4.0) license. A direct URL for this license is not provided in the source material.
Who Can Use It
This dataset is suitable for:
- E-commerce Analysts: To identify best-selling products and understand sales drivers.
- Data Scientists: For building models to predict product success or analyse pricing strategies.
- Market Researchers: To study consumer behaviour and the impact of discounts and ratings.
- Business Strategists: To inform decisions on product listings and pricing.
Dataset Name Suggestions
- Wish E-commerce Summer Sales Performance
- Wish Product Ratings & Sales Data
- Summer Clothing E-commerce Insights
- Wish Platform Product Success Metrics
- Top-Selling Summer Products on Wish
Attributes
Original Data Source:Wish Product Ratings & Sales Data
QUALITY