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Amazon Customer Feedback Data
Product Reviews & Feedback
Tags and Keywords
Trusted By
"No reviews yet"
Free
About
This dataset provides detailed information on over a thousand Amazon products, including their ratings and customer reviews. It serves as a valuable resource for understanding e-commerce dynamics, product performance, and consumer feedback on Amazon. This data can be utilised for various analytical purposes, such as exploring product trends and building recommendation systems. The dataset was created to enable people to engage with and analyse Amazon's vast product and review information. Amazon itself is an American multinational technology company with significant interests in e-commerce, managing inventory, shipping, pricing, customer service, and returns.
Columns
- product_id: A unique identifier for each product. There are 1351 distinct product IDs across 1465 valid entries.
- product_name: The name of the product. There are 1337 distinct product names across 1465 valid entries.
- category: The category to which the product belongs. There are 211 distinct categories across 1465 valid entries, with "Computers&Accessories|Accessories&Peripherals|Cables&Accessories|Cables|USBCables" being the most frequent (16%).
- discounted_price: The selling price of the product after any discounts. There are 550 unique discounted prices across 1465 valid entries, with ₹199 being the most common (4%).
- actual_price: The original price of the product before any discounts. There are 449 unique actual prices across 1465 valid entries, with ₹999 being the most common (8%).
- discount_percentage: The percentage of discount applied to the product. There are 92 unique discount percentages across 1465 valid entries, with 50% and 60% being frequent (each 4%).
- rating: The average rating given to the product. Ratings range from 2.00 to 5.00, with a mean of 4.1 and a standard deviation of 0.29 across 1464 valid entries.
- rating_count: The total number of people who voted for the product's Amazon rating. There are 1463 valid entries with 2 missing values. The mean rating count is 18.3 thousand, with a standard deviation of 42.7 thousand. The maximum rating count observed is 427 thousand.
- about_product: A description detailing the product's features and characteristics. There are 1293 unique product descriptions across 1465 valid entries.
- user_id: A unique identifier for the user who wrote a review. There are 1194 unique user IDs across 1465 valid entries.
- user_name: The name of the user who wrote the review. There are 1194 unique user names across 1465 valid entries.
- review_id: A unique identifier for the user's review. There are 1194 unique review IDs across 1465 valid entries.
- review_title: A short summary or title of the user's review. There are 1194 unique review titles across 1465 valid entries.
- review_content: The detailed, longer content of the user's review. There are 1212 unique review contents across 1465 valid entries.
- img_link: A link to the product's image. There are 1412 unique image links across 1465 valid entries.
- product_link: The official website link to the product on Amazon. There are 1465 unique product links, with all 1465 entries being valid.
Distribution
The dataset is provided in a CSV format and is approximately 4.74 MB in size. It contains data for over 1000 Amazon products, with most fields having 1465 records. All 16 columns are present and accounted for. There are minor discrepancies in valid entry counts for
rating (1464 entries) and rating_count (1463 entries with 2 missing).Usage
This dataset is ideal for:
- Data Preprocessing exercises.
- Exploratory Data Analysis to uncover patterns and insights.
- Data Visualisation to represent product performance and customer sentiment.
- Building and evaluating Recommendation Systems for e-commerce platforms.
- Analysing pricing strategies, discount effectiveness, and product categorisation.
Coverage
The dataset focuses on products and reviews from Amazon, an American multinational company. The product links observed, such as those leading to
amazon.in, suggest a focus on the Indian market. The data includes details on individual user IDs and names but does not contain explicit demographic information about the users. A specific time range for the collected data is not specified within the available information.License
CC BY-NC-SA 4.0
Who Can Use It
This dataset is suitable for:
- Data scientists and analysts for machine learning models and statistical analysis.
- Researchers studying e-commerce trends, consumer behaviour, and product reviews.
- Students learning about data cleaning, visualisation, and recommendation algorithms.
- Anyone interested in analysing product performance, customer satisfaction, and market dynamics on Amazon.
Dataset Name Suggestions
- Amazon Product Insights Data
- E-commerce Product Review Dataset
- Amazon Customer Feedback Data
- Product Ratings and Reviews Collection
Attributes
Original Data Source: Amazon Customer Feedback Data
QUALITY