Online Shoe Consumer Feedback
Reviews & Ratings
Tags and Keywords
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"No reviews yet"
Free
About
This dataset provides a detailed collection of shoe prices, reviews, and ratings gathered from a major online retail platform. Its primary purpose is to offer insights into consumer feedback and product performance within the footwear market. The data is highly valuable for conducting sentiment analysis, identifying product strengths and weaknesses, and understanding customer preferences through topic modelling and word-cloud formation. It can help pinpoint specific issues with products, often referred to as "potholes," based on user ratings and comments.
Columns
- title: The title of the product listing.
- price: The monetary value of the shoe.
- Shoe_Name: The given name of the shoe product.
- rating: The overall average rating awarded to the product, typically out of 5 stars.
- total_reviews: The total count of reviews a particular product has received.
- product_description: A textual explanation of the shoe's features and benefits.
- reviews: Up to 10 individual customer reviews for the shoe, separated by a delimiter '|| '.
- reviews_rating: The corresponding star ratings for each of the individual reviews, also separated by '|| '.
- Shoe Type: Categorisation indicating whether the shoe is for 'Men' or 'Women'.
Distribution
The dataset is typically provided in a CSV file format. While specific total row counts are not detailed, it contains various unique values across its columns, such as different shoe names, prices, and product descriptions. It includes numerous entries related to footwear products listed on Amazon.
Usage
This dataset is ideal for various analytical applications, including:
- Performing sentiment analysis to gauge public opinion on specific shoe models.
- Conducting topic modelling to uncover key themes and recurring issues in customer reviews.
- Generating word clouds to visually represent frequently used terms in feedback.
- Identifying "potholes" or areas for product improvement based on negative feedback patterns.
- Market research to understand consumer preferences and trends in footwear.
Coverage
The dataset's scope is global, encompassing various products listed on the platform. Demographically, it includes footwear primarily for Men (approximately 70%) and Women (approximately 30%). No specific time range for data collection is detailed within the available information.
License
CC0
Who Can Use It
This dataset is suitable for:
- Data Scientists and Analysts: For developing predictive models, performing natural language processing (NLP) tasks, and extracting insights from unstructured text data.
- E-commerce Businesses: To monitor customer satisfaction, improve product offerings, and devise targeted marketing strategies.
- Retail Strategists: To understand market demand, identify best-selling attributes, and forecast trends in the footwear sector.
- Academic Researchers: For studies on consumer behaviour, online reviews, and product-market fit.
Dataset Name Suggestions
- Amazon Footwear Reviews & Ratings
- Online Shoe Consumer Feedback
- E-commerce Shoe Product Analysis Data
- Men and Women's Shoe Reviews Dataset
Attributes
Original Data Source: Men_Women_Shoes_Reviews