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Global Beauty Product Ratings
Reviews & Ratings
Tags and Keywords
Trusted By
"No reviews yet"
Free
About
This dataset provides customer reviews and ratings for cosmetics and beauty products, offering insights into consumer sentiment and product performance. It includes reviews for 295 unique product IDs, with duplicate entries for product variants removed to ensure data integrity. This dataset is ideal for Natural Language Processing (NLP) tasks, analysis of e-commerce services, and understanding market trends within the make-up and cosmetics industry.
Columns
- product_id: The SKU or unique product identifier.
- brand_name: The name of the brand associated with the product.
- review_id: A unique identifier for each review.
- review_title: The headline or title of the customer review.
- review_text: The full textual content of the review.
- author: The name of the individual who submitted the review.
- review_date: The date on which the review was posted.
- review_rating: The numerical rating provided by the author for the product.
- is_a_buyer: A boolean indicator showing whether the reviewer purchased the product.
- pro_user: A boolean indicator showing whether the reviewer is a 'pro' user.
Distribution
The dataset is typically provided in a CSV file format. It features reviews of 295 distinct product IDs. While the exact number of rows is not specified, it contains over 60,000 individual review records. Reviews from product variants that duplicated parent product reviews have been systematically removed to maintain data uniqueness. The dataset was listed on 08/06/2025.
Usage
This dataset can be used for a variety of applications, including:
- Sentiment analysis on product reviews using NLP techniques.
- Enhancing e-commerce recommendation systems and customer service.
- Market research to identify popular products and consumer preferences in the beauty sector.
- Analysing trends in make-up and cosmetics.
- Developing and testing text classification models.
Coverage
The dataset covers a global region. The reviews span a time period from 20 May 2013 to 23 October 2022. Key brands represented in the dataset include Nykaa Cosmetics (29%), Kay Beauty (22%), and a wide range of other brands (49%).
License
CCO
Who Can Use It
- Data Scientists and Machine Learning Engineers for developing NLP models and sentiment analysis tools.
- E-commerce Businesses and Retailers for product development, customer feedback analysis, and marketing strategies.
- Market Analysts and Consultants for industry trend forecasting and competitive intelligence in the beauty sector.
- Academic Researchers for studies on consumer behaviour, online reviews, and textual analysis.
Dataset Name Suggestions
- Cosmetics Product Reviews and Ratings
- Beauty Industry Consumer Feedback
- E-commerce Beauty Reviews Dataset
- Nykaa Product Review Data
- Global Beauty Product Ratings
Attributes
Original Data Source: Cosmetics and Beauty Products Reviews - Top Brands
QUALITY