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Global Customer Product Feedback Dataset
Data Science and Analytics
Tags and Keywords
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"No reviews yet"
Free
About
This dataset features 171,000 product reviews, meticulously labelled with sentiment indicators. It includes associated metadata such as product names and prices. The core purpose of this dataset is to facilitate sentiment analysis of product reviews, allowing for the automatic classification of textual content into positive, negative, or neutral sentiments. This resource is invaluable for understanding customer perception and informing business strategies or consumer purchasing decisions.
Columns
- product_name: The name of the product being reviewed (e.g., "Bumtum Baby Pull-Up Diaper Pants Combo Pack").
- product_price: The price of the product at the time of review. Price ranges in the dataset span from 59.00 to 65257.25, with some outliers up to 86990.00.
- Rate: The numerical rating given by the reviewer. Ratings in the dataset primarily fall within ranges such as 1.00-1.20, 2.00-2.20, 3.00-3.20, 4.00-4.20, and 4.80-5.00.
- Review: The full text of the customer review. Examples include reviews described as 'good' or 'ok'.
- Summary: A concise summary of the review, often including 'Nan' (Not a Number) or 'Other' categories for some entries.
- Sentiment: The assigned sentiment label, indicating whether the review is positive, negative, or neutral. The dataset shows an approximate distribution of 34% positive, 34% neutral, and 33% other (likely negative) sentiments.
Distribution
The dataset comprises approximately 171,000 product reviews. It typically exists in a tabular structure, often suitable for formats like CSV. The price data exhibits a wide range, with a significant number of entries between 59.00 and 4405.55. Review ratings are distributed across the scale, with notable counts for ratings between 4.80-5.00 and 1.00-1.20. Sentiment labels are well-distributed across positive, neutral, and negative categories.
Usage
This dataset is ideal for:
- Developing and training machine learning algorithms for sentiment analysis.
- Automating the classification of product reviews by sentiment.
- Tracking customer sentiment trends over time for specific products or brands.
- Identifying product strengths and areas for improvement based on customer feedback.
- Empowering consumers to make informed purchasing decisions by aggregating sentiment.
Coverage
The dataset's region of coverage is global. No specific time range for the reviews themselves is specified within the available information, though the dataset was listed on 17/06/2025. No specific demographic scope is provided.
License
CC0
Who Can Use It
- Businesses and product managers: To monitor and understand customer sentiment for their offerings, identify product improvements, and gauge market reception.
- Data scientists and machine learning engineers: For training and validating natural language processing (NLP) models focused on sentiment classification.
- Market researchers: To analyse broad trends in consumer opinion and behaviour related to products.
- Consumers: To inform their purchasing choices by reviewing aggregated sentiment.
- Academics and researchers: For studies on consumer behaviour, text analysis, and sentiment modelling.
Dataset Name Suggestions
- Product Review Sentiment Dataset
- E-commerce Product Review Sentiment Data
- Global Customer Product Feedback Dataset
- Sentiment Labelled Product Reviews
Attributes
Original Data Source: 171k product review with Sentiment Dataset
QUALITY