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Amazon Dress Review Analysis Dataset
Product Reviews & Feedback
Tags and Keywords
Trusted By
"No reviews yet"
Free
About
This dataset presents 23,000 datapoints of Amazon customer reviews concerning women's dresses. Its primary purpose is to enable the analysis of customer feedback, allowing for the identification of patterns related to customer satisfaction. By scrutinising customer ratings and review texts, organisations can gain insights to continuously enhance their e-commerce operations and improve overall customer experience. The data aims to help platforms better understand and cater to customer needs by leveraging their shared experiences with purchased products.
Columns
s.no: A simple index for each record within the dataset.age: Represents the age of the customer who submitted the review.division_name: Specifies the broader division of the clothing item purchased by the customer (e.g., General, General Petite).department_name: Indicates the specific department the clothing item belongs to (e.g., Tops, Dresses).class_name: Details the particular class of the clothing item (e.g., Dresses, Knits).clothing_id: A unique identifier assigned to a specific type of product.title: The headline or title composed by customers for their review or feedback text.review_text: Contains the detailed textual review provided by the customer.alike_feedback_count: Shows the number of other customers who found the given feedback similar to their own experience.rating: The numerical rating or star value assigned by the customer to the product, typically on a scale (e.g., 1 to 5).recommend_index: A binary indicator specifying whether the customer would recommend the product (1 for Yes, 0 for No).
Distribution
The dataset is structured as a CSV (Comma Separated Values) file and has a file size of 8.51 MB. It contains approximately 23,500 valid records, providing a substantial amount of data for various analytical tasks.
Usage
This dataset is highly valuable for several applications:
- E-commerce platforms: To dissect customer feedback and refine product strategies.
- Retail businesses: To understand consumer preferences in women's apparel and inform purchasing decisions.
- Data scientists: For developing and training sentiment analysis models or recommendation engines based on customer reviews.
- Customer experience professionals: To identify key drivers of satisfaction and dissatisfaction, allowing for targeted service improvements.
- Market research: To uncover trends and insights into online shopping behaviour for women's fashion.
Coverage
The dataset focuses on feedback from women customers, with their ages ranging from 18 to 99 years. It covers various categories of clothing, categorised by division, department, and specific class names (such as dresses, tops, and knits). However, specific geographic regions or precise time ranges for the data collection are not detailed in the provided materials.
License
CC BY-SA 4.0
Who Can Use It
- E-commerce analysts: To optimise online product listings and improve customer conversion rates.
- Product managers: To gain direct customer insights for product design and feature enhancements in the fashion industry.
- Academic researchers: For studies on consumer behaviour, online review systems, and customer satisfaction in e-commerce.
- Business intelligence teams: To create dashboards and reports on customer sentiment and product performance.
Dataset Name Suggestions
- Women's E-commerce Dress Reviews
- Online Women's Apparel Customer Feedback
- Amazon Dress Review Analysis Dataset
- Female Customer Satisfaction in Dresses
- Retail Dress Review Data
Attributes
Original Data Source: Amazon Dress Review Analysis Dataset
QUALITY