Context

This Dataset is an updated version of the Amazon review dataset released in 2014. As in the previous version, this dataset includes reviews (ratings, text, helpfulness votes), product metadata (descriptions, category information, price, brand, and image features), and links (also viewed/also bought graphs). In addition, this version provides the following features:

• More reviews:

  • The total number of reviews is 233.1 million (142.8 million in 2014).

• New reviews:

  • Current data includes reviews in the range May 1996 - Oct 2018.

• Metadata: - We have added transaction metadata for each review shown on the review page.

  • Added more detailed metadata of the product landing page.

Acknowledgements

If you publish articles based on this dataset, please cite the following paper:

• Jianmo Ni, Jiacheng Li, Julian McAuley. Justifying recommendations using distantly-labeled reviews and fined-grained aspects. EMNLP, 2019.

Gain extensive insights with our Amazon datasets, encompassing detailed product information including pricing, reviews, ratings, brand names, product categories, sellers, ASINs, images, and much more. Ideal for market researchers, data analysts, and eCommerce professionals looking to excel in the competitive online marketplace. Over 425M records available Price starts at $250/100K records Data formats are available in JSON, NDJSON, CSV, XLSX and Parquet. 100% ethical and compliant data collection Included datapoints:

Title Asin Main Image Brand Name Description Availability Subcategory Categories Parent Asin Type Product Type Name Model Number Manufacturer Color Size Date First Available Released Model Year Item Model Number Part Number Price Total Reviews Total Ratings Average Rating Features Best Sellers Rank Subcategory Buybox Buybox Seller Id Buybox Is Amazon Images Product URL And more

Amazon Sales Dataset Description This dataset contains 250 records of Amazon sales transactions, including details about the products sold, customers, payment methods, and order statuses.

Columns Description: Order ID - Unique identifier for each order (e.g., ORD0001).

Date - Date of the order.

Product - Name of the product purchased.

Category - Product category (Electronics, Clothing, Home Appliances, etc.).

Price - Price of a single unit of the product.

Quantity - Number of units purchased in the order.

Total Sales - Total revenue from the order (Price × Quantity).

Customer Name - Name of the customer.

Customer Location - City where the customer is based.

Payment Method - Mode of payment (Credit Card, Debit Card, PayPal, etc.).

Status - Order status (Completed, Pending, or Cancelled).

This dataset can be used for sales analysis, customer behavior insights, and revenue trends visualization. 🚀

Buy Amazon datasets and get access to over 300 million records from any Amazon domain. Get insights on Amazon products, sellers, and reviews.

Utilize our Amazon reviews dataset for diverse applications to enrich business strategies and market insights. Analyzing this dataset can aid in understanding customer behavior, product performance, and market trends, empowering organizations to refine their product and marketing strategies. Access the entire dataset or tailor a subset to fit your requirements. Popular use cases include: Product Performance Analysis: Analyze Amazon reviews to assess product performance, uncovering customer satisfaction levels, common issues, and highly praised features to inform product improvements and marketing messages. Customer Behavior Insights: Gain insights into customer behavior, purchasing patterns, and preferences, enabling more personalized marketing and product recommendations. Demand Forecasting: Leverage Amazon reviews to predict future product demand by analyzing historical review data and identifying trends, helping to optimize inventory management and sales strategies. Accessing and analyzing the Amazon reviews dataset supports market strategy optimization by leveraging insights to analyze key market trends and customer preferences, enhancing overall business decision-making.

https://www.kaggle.com/code/mithilesh9/amazon-sales-data-analysis-using-python

Dataset Description This dataset contains a 100 rows of sales data for Amazon, including the region, country, item type, sales channel, order priority, order date, order ID, ship date, units sold, unit price, unit cost, total revenue, total cost, and total profit.

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F19501062%2F5d10a624d07eefb2240c474ca00114b6%2FScreenshot%202024-06-25%20135139.png?generation=1719303822906805&alt=media" alt="">

We present a collection of Amazon reviews specifically designed to aid research in multilingual text classification. The dataset contains reviews in English, Japanese, German, French, Chinese and Spanish, collected between November 1, 2015 and November 1, 2019. Each record in the dataset contains the review text, the review title, the star rating, an anonymized reviewer ID, an anonymized product ID and the coarse-grained product category (e.g. 'books', 'appliances', etc.)

Dataset Card for "amazon-product-data-filter"

  Dataset Summary

The Amazon Product Dataset contains product listing data from the Amazon US website. It can be used for various NLP and classification tasks, such as text generation, product type classification, attribute extraction, image recognition and more. NOTICE: This is a sample of the full Amazon Product Dataset, which contains 1K examples. Follow the link to gain access to the full dataset.

  Languages… See the full description on the dataset page: https://huggingface.co/datasets/iarbel/amazon-product-data-sample.

These datasets contain 1.48 million question and answer pairs about products from Amazon.

Metadata includes

• question and answer text

• is the question binary (yes/no), and if so does it have a yes/no answer?

• timestamps

• product ID (to reference the review dataset)

Basic Statistics:

• Questions: 1.48 million

• Answers: 4,019,744

• Labeled yes/no questions: 309,419

• Number of unique products with questions: 191,185

Don't forget to Upvote the Dataset🙏.

This Data is a Amazon Product Sales. This Dataset about Amazon Sales Contain 3204 Rows and 9 Columns. You Can Apply Various thing you can make DashBoard and perform Analysis many more..

Column Description:

Order Date - Order_Date.

Ship Date - Shipping Date.

Email_ID - Email_ID of Users

Geography - Location of Orders by Users.

Category - Product Category

Product Name - Product Name of Amazon

Sales - Amazon Product Sales

Quantity - how many units of a particular product are available.

Profit - Amazon Sales Profit

Dataset Card for "Amazon-QA"

  Dataset Summary

This dataset contains Question and Answer data from Amazon. Disclaimer: The team releasing Amazon-QA did not upload the dataset to the Hub and did not write a dataset card. These steps were done by the Hugging Face team.

  Supported Tasks

Sentence Transformers training; useful for semantic search and sentence similarity.

  Languages

English.

  Dataset Structure

Each example in the dataset… See the full description on the dataset page: https://huggingface.co/datasets/embedding-data/Amazon-QA.

This dataset provides comprehensive real-time data from Amazon's global marketplaces. It includes detailed product information, reviews, seller profiles, best sellers, deals, influencers, and more across all Amazon domains worldwide. The data covers product attributes like pricing, availability, specifications, reviews and ratings, as well as seller information including profiles, contact details, and performance metrics. Users can leverage this dataset for price monitoring, competitive analysis, market research, and building e-commerce applications. The API enables real-time access to Amazon's vast product catalog and marketplace data, helping businesses make data-driven decisions about pricing, inventory, and market positioning. Whether you're conducting market analysis, tracking competitors, or building e-commerce tools, this dataset provides current and reliable Amazon marketplace data. The dataset is delivered in a JSON format via REST API.

About the Dataset:

Amazon is one of the biggest online retailers in the UK. With this dataset, you can get an in-depth idea of what products sell best, which SEO titles generate the most sales, the best price range for a product in a given category, and much more.

It took a lot of time and energy to prepare this original dataset, so don't forget to hit the upvote button! 😊💝

Similar Datasets:

Amazon Canada Products

Amazon India Products

Amazon USA Products

Interesting Task Ideas:

1. Uncover trending product categories and their sales performance.
2. Analyze customer ratings to find top-rated products.
3. Train a product title generator that can generate sales-worthy product titles based on products with the most sales.
4. Gain insight into the best price for any given product based on sales data and competition.
5. Identify which niches are the easiest to make sales in.
6. Gain insights into the general spending habits of online shoppers.
7. Use as a seed dataset for practicing database management and performance optimization.
8. Train (or learn to train) an AI-based search model to recommend Amazon products.

Checkout my other datasets

USA Unemployment Rates by Demographics & Race

USA Hispanic-White Wage Gap Dataset

Median and Avg Hourly Wages in the USA

Health Insurance Coverage in the USA

Black-White Wage Gap in the USA Dataset

Photo by Canonicalized

Gain access to a structured dataset featuring thousands of products listed on Amazon India. This dataset is ideal for e-commerce analytics, competitor research, pricing strategies, and market trend analysis.

Dataset Features:

• Product Details: Name, Brand, Category, and Unique ID

• Pricing Information: Current Price, Discounted Price, and Currency

• Availability & Ratings: Stock Status, Customer Ratings, and Reviews

• Seller Information: Seller Name and Fulfillment Details

• Additional Attributes: Product Description, Specifications, and Images

Dataset Specifications:

• Format: CSV

• Number of Records: 50,000+

• Delivery Time: 3 Days

• Price: $149.00

• Availability: Immediate

This dataset provides structured and actionable insights to support e-commerce businesses, pricing strategies, and product optimization. If you're looking for more datasets for e-commerce analysis, explore our E-commerce datasets for a broader selection.

APISCRAPY's Amazon Data extraction is a sophisticated solution that leverages AI & web scraping skills to supply organizations with critical data from the Amazon platform. By scraping Amazon you get a product-related Amazon database, including product names, descriptions, pricing, ratings & reviews

The Amazon Question and Answer Data dataset is a compilation of queries and responses regarding products listed on Amazon, enhancing the understanding of consumer interactions and preferences. The dataset encompasses approximately 1.48 million questions and over 4 million answers, with a subset of 309,419 labeled yes/no questions linked to 191,185 unique products. This data is categorized by the text of the question and answer, the binary nature of the question (yes/no), the presence of a yes/no answer, timestamps, and the product ID which can be cross-referenced with the review dataset.

An exemplary entry from the dataset includes a product ID, the type of question (yes/no or open-ended), the type of answer (yes, no, or unsure), the timestamp of the answer, the text of the question, and the text of the answer. This dataset is further divided into per-category files for various product categories like appliances, electronics, beauty, and more, each file containing the respective questions and answers for that category. It's a vital resource for examining consumer behavior, product-related queries, and the subjective nature of product reviews.

The dataset can be utilized alongside the Amazon product review dataset by matching the respective ASINs (Amazon Standard Identification Numbers). Researchers are encouraged to cite the provided references if they employ this dataset in their work. The data can be accessed and downloaded from the Amazon Q/A Page, with additional information and instructions available for parsing the data and utilizing it for various analytical purposes.

Amazon data science challenge.

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns : marketplace - 2 letter country code of the marketplace where the review was written. customer_id - Random identifier that can be used to aggregate reviews written by a single author. review_id - The unique ID of the review. product_id - The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id. product_parent - Random identifier that can be used to aggregate reviews for the same product. product_title - Title of the product. product_category - Broad product category that can be used to group reviews (also used to group the dataset into coherent parts). star_rating - The 1-5 star rating of the review. helpful_votes - Number of helpful votes. total_votes - Number of total votes the review received. vine - Review was written as part of the Vine program. verified_purchase - The review is on a verified purchase. review_headline - The title of the review. review_body - The review text. review_date - The date the review was written.

To use this dataset:

import tensorflow_datasets as tfds

ds = tfds.load('amazon_us_reviews', split='train')
for ex in ds.take(4):
 print(ex)

See the guide for more informations on tensorflow_datasets.

A multidisciplinary repository of public data sets such as the Human Genome and US Census data that can be seamlessly integrated into AWS cloud-based applications. AWS is hosting the public data sets at no charge for the community. Anyone can access these data sets from their Amazon Elastic Compute Cloud (Amazon EC2) instances and start computing on the data within minutes. Users can also leverage the entire AWS ecosystem and easily collaborate with other AWS users. If you have a public domain or non-proprietary data set that you think is useful and interesting to the AWS community, please submit a request and the AWS team will review your submission and get back to you. Typically the data sets in the repository are between 1 GB to 1 TB in size (based on the Amazon EBS volume limit), but they can work with you to host larger data sets as well. You must have the right to make the data freely available.

Amazon is one of the most recognisable brands in the world, and the third largest by revenue. It was the fourth tech company to reach a $1 trillion market cap, and a market leader in e-commerce,...