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

Explore our extensive Amazon Product Dataset, featuring detailed information on prices, ratings, sales volume, and more.

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

• 500K+ Active Amazon Stores • 200K+ Seller Leads • Platforms USA, Germany, UK, Italy, France, Spain, CA • C-Suite/Marketing/Sales Contacts • FBA/Non-FBA Sellers • 15+ data points available for each prospect • Filter your leads by store size, niche, location, and many more • 100% manually researched and verified.

For over a decade, we have been manually collecting Amazon seller data from various data sources such as Amazon, Linkedin, Google, and others. We are specialized to get valid, and potential data so you may conduct ads and begin selling without hesitation.

We designed our data packages for all types of organizations, thus they are reasonably priced. We are always trying to reduce our prices to better suit all of your requirements.

So, if you’re looking to reach out to your targeted Amazon sellers, now is the greatest time to do so and offer your goods, services, and promotions. You can get your targeted Amazon Sellers List with seller contact information.

Alternatively, if you provide Amazon Seller Names or IDs, we will conduct Custom Research and deliver the customized list to you.

Data Points Available:

Full Name Linkedin URL Direct Email Generic Phone Number Business Name and Address Company Website Seller IDs and URLs Revenue Seller Review Count Niche FBA/Non-FBA Country and More

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.

Gain insights into Amazon’s beauty and personal care market with this comprehensive Amazon Beauty Products Dataset. Covering 47,000 records across skincare, haircare, and makeup, this dataset provides full ingredient lists, product descriptions, pricing, and availability. Ideal for researchers and businesses focused on ingredient transparency, beauty trend analysis, and competitive market insights. Perfect for applications in ingredient research, product development, and e-commerce analysis.

Access a rich Amazon Beauty & Cosmetics dataset with over 200,000+ product records, including detailed ingredients.
Explore more on our Beauty & Cosmetics Data page or view the full Amazon Beauty Dataset

Walmart product dataset featuring detailed ingredient information across categories like beauty, food, personal care, and more.
View Dataset →

The dataset includes the following fields:

• ASIN: Unique Amazon product identifier.
• Product Name and Description: Full titles and descriptions of each product.
• Price and Availability: Current pricing and stock status.
• Categories: Product type classification (e.g., skincare, haircare, makeup).
• Ingredients: Complete ingredient lists, ensuring transparency about product composition.
• Images: High-quality product images.
• Brand and Manufacturer Information: Details of the brand and manufacturer.
• Customer Ratings and Reviews: User-generated content for understanding product popularity and performance.

This dataset is invaluable for:

• Ingredient Analysis: Understanding popular ingredients in beauty products.
• Market Research: Analyzing trends in beauty products, such as ingredient types and product categories.
• Competitive Analysis: Assessing product offerings by brand, price, and ingredients.

Whether you’re focused on skincare, haircare, makeup, or other beauty categories, this dataset provides in-depth information for deep analysis. For any custom requirements or additional data needs, please feel free to reach out.

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.

**# 📌 Dataset Description for Kaggle: Amazon Best Sellers Data

**📖 Overview

This dataset contains real-time Amazon Best Sellers data across multiple countries and categories, specifically focusing on Software products. The data is collected via an API and includes details such as product titles, prices, star ratings, number of reviews, and rank changes.

With this dataset, you can analyze trending products, pricing strategies, and customer preferences across different regions. It is useful for market analysis, competitor research, and e-commerce insights.

📊 Dataset Contents

Each row in this dataset represents a top-selling software product on Amazon for a specific country. The dataset includes the following columns:

product_title 🏷️ – Name of the product product_price 💰 – Price of the product in the respective country’s currency product_star_rating ⭐ – Average star rating of the product product_num_ratings 📝 – Total number of customer reviews rank 🔢 – Current ranking of the product in the Best Sellers list country 🌍 – The country where the ranking is recorded

🎯 Potential Use Cases

✅ E-commerce Market Analysis – Identify top-selling software products in different regions. ✅ Pricing Strategy Optimization – Compare prices across markets and track fluctuations. ✅ Customer Sentiment Analysis – Analyze customer ratings and review trends. ✅ Competitor Research – Understand how products rank in different countries. ✅ Trend Forecasting – Observe rank changes and predict upcoming best-sellers.

Get the needed Amazon product review data right from the data extractor! Collect Amazon review information from 19 Amazon countries from the following domains: - amazon.com - amazon.com.au - amazon.com.br - amazon.ca - amazon.cn - amazon.fr - amazon.de - amazon.in - amazon.it - amazon.com.mx - amazon.nl - amazon.sg - amazon.es - amazon.com.tr

Request Ecommerce Product Review dataset by: - keyword - category - seller - product ID (ASIN)

Amazon E-commerce Reviews Data datasets gathered by keyword, seller, category, or ASIN contain: - Product ID (can be extended to the full product information) - Review content and rating - Review metadata

Amazon extraction results can be delivered by schedule or API request, so the data can be extracted in real-time.

DATAANT uses the in-house web scraping service with no concurrency limitations, so unlimited data extractions can be performed simultaneously.

Output can and attributes can be customized to fit your particular needs.

Amazon.com, Inc. engages in the retail sale of consumer products, advertising, and subscriptions service through online and physical stores in North America and internationally. The company operates through three segments: North America, International, and Amazon Web Services (AWS). It also manufactures and sells electronic devices, including Kindle, Fire tablets, Fire TVs, Echo, Ring, Blink, and eero; and develops and produces media content. In addition, the company offers programs that enable sellers to sell their products in its stores; and programs that allow authors, independent publishers, musicians, filmmakers, Twitch streamers, skill and app developers, and others to publish and sell content. Further, it provides compute, storage, database, analytics, machine learning, and other services, as well as advertising services through programs, such as sponsored ads, display, and video advertising. Additionally, the company offers Amazon Prime, a membership program. The company's products offered through its stores include merchandise and content purchased for resale and products offered by third-party sellers. It serves consumers, sellers, developers, enterprises, content creators, advertisers, and employees. Amazon.com, Inc. was incorporated in 1994 and is headquartered in Seattle, Washington.

Features 1. Stock Data: Open, High, Low, Close, Volume 2. Date: The specific trading date. 3. Closing Price: The price at which the stock closed on a given day.

Source Free API Provider

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.

Unlock powerful insights with the Amazon Prime dataset, offering access to millions of records from any Amazon domain. This dataset provides comprehensive data points such as product titles, descriptions, exclusive Prime discounts, brand details, pricing (initial and discounted), availability, customer ratings, reviews, and product categories. Additionally, it includes unique identifiers like ASINs, images, and seller information, allowing you to analyze Prime offerings, trends, and customer preferences with precision. Use this dataset to optimize your eCommerce strategies by analyzing Prime-exclusive pricing strategies, identifying top-performing brands and products, and tracking customer sentiment through reviews and ratings. Gain valuable insights into consumer demand, seasonal trends, and the impact of Prime discounts to make data-driven decisions that enhance your inventory management, marketing campaigns, and pricing strategies. Whether you’re a retailer, marketer, data analyst, or researcher, the Amazon Prime dataset empowers you with the data needed to stay competitive in the dynamic eCommerce landscape. Available in various formats such as JSON, CSV, and Parquet, and delivered via flexible options like API, S3, or email, this dataset ensures seamless integration into your workflows.

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,...

From 2004 to 2024, the net revenue of Amazon e-commerce and service sales has increased tremendously. In the fiscal year ending December 31, the multinational e-commerce company's net revenue was almost *** billion U.S. dollars, up from *** billion U.S. dollars in 2023.Amazon.com, a U.S. e-commerce company originally founded in 1994, is the world’s largest online retailer of books, clothing, electronics, music, and many more goods. As of 2024, the company generates the majority of it's net revenues through online retail product sales, followed by third-party retail seller services, cloud computing services, and retail subscription services including Amazon Prime. From seller to digital environment Through Amazon, consumers are able to purchase goods at a rather discounted price from both small and large companies as well as from other users. Both new and used goods are sold on the website. Due to the wide variety of goods available at prices which often undercut local brick-and-mortar retail offerings, Amazon has dominated the retailer market. As of 2024, Amazon’s brand worth amounts to over *** billion U.S. dollars, topping the likes of companies such as Walmart, Ikea, as well as digital competitors Alibaba and eBay. One of Amazon's first forays into the world of hardware was its e-reader Kindle, one of the most popular e-book readers worldwide. More recently, Amazon has also released several series of own-branded products and a voice-controlled virtual assistant, Alexa. Headquartered in North America Due to its location, Amazon offers more services in North America than worldwide. As a result, the majority of the company’s net revenue in 2023 was actually earned in the United States, Canada, and Mexico. In 2023, approximately *** billion U.S. dollars was earned in North America compared to only roughly *** billion U.S. dollars internationally.

Amazon Product Reviews

18 Years of Customer Ratings and Experiences

By Huggingface Hub [source]

About this dataset

The Amazon Reviews Polarity Dataset discloses eighteen years of customers' ratings and reviews from Amazon.com, offering an unparalleled trove of insight and knowledge. Drawing from the immense pool of over 35 million customer reviews, this dataset presents a broad spectrum of customer opinions on products they have bought or used. This invaluable data is a gold mine for improving products and services as it contains comprehensive information regarding customers' experiences with a product including ratings, titles, and plaintext content. At the same time, this dataset contains both customer-specific data along with product information which encourages deep analytics that could lead to great advances in providing tailored solutions for customers. Has your product been favored by the majority? Are there any aspects that need extra care? Use Amazon Reviews Polarity to gain deeper insights into what your customers want - explore now!

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For more datasets, click here.

Featured Notebooks

• 🚨 Your notebook can be here! 🚨!

How to use the dataset

• Analyze customer ratings to identify trends: Take a look at how many customers have rated the same product or service with the same score (e.g., 4 stars). You can use this information to identify what customers like or don’t like about it by examining common sentiment throughout the reviews. Identifying these patterns can help you make decisions on which features of your products or services to emphasize in order to boost sales and satisfaction rates.

2 Review content analysis: Analyzing review content is one of the best ways to gauge customer sentiment toward specific features or aspects of a product/service. Using natural language processing tools such as Word2Vec, Latent Dirichlet Allocation (LDA), or even simple keyword search algorithms can quickly reveal general topics that are discussed in relation to your product/service across multiple reviews - allowing you quickly pinpoint areas that may need improvement for particular items within your lines of business.

3 Track associated scores over time: By tracking customer ratings overtime, you may be able to better understand when there has been an issue with something specific related to your product/service - such as negative response toward a feature that was introduced but didn’t seem popular among customers and was removed shortly after introduction.. This can save time and money by identifying issues before they become widespread concerns with larger sets of consumers who invest their money in using your company's item(s).

4 Visualize sentiment data over time graphs : Utilizing visualizations such as bar graphs can help identify trends across different categories quicker than raw numbers alone; combining both numeric values along with color differences associated between different scores allows you spot anomalies easier - allowing faster resolution times when trying figure out why certain spikes occurred where other stayed stable (or vice-versa) when comparing similar data points through time-series based visualization models

Research Ideas

• Developing a customer sentiment analysis system that can be used to quickly analyze the sentiment of reviews and identify any potential areas of improvement.
• Building a product recommendation service that takes into account the ratings and reviews of customers when recommending similar products they may be interested in purchasing.
• Training a machine learning model to accurately predict customers’ ratings on new products they have not yet tried and leverage this for further product development optimization initiatives

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: train.csv | Column name | Description | |:--------------|:-------------------------------------------------------------------| | label | The sentiment of the review, either positive or negative. (String) | | title | The title of the review. (String) ...

Comprehensive dataset covering Amazon's 1.9 million active third-party sellers worldwide, including regional distribution, growth trends, and marketplace dynamics from 2000-2025.

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.

In 2024, Amazon's net revenue from subscription services segment amounted to 44.37 billion U.S. dollars. Subscription services include Amazon Prime, for which Amazon reported 200 million paying members worldwide at the end of 2020. The AWS category generated 107.56 billion U.S. dollars in annual sales. During the most recently reported fiscal year, the company’s net revenue amounted to 638 billion U.S. dollars. Amazon revenue segments Amazon is one of the biggest online companies worldwide. In 2019, the company’s revenue increased by 21 percent, compared to Google’s revenue growth during the same fiscal period, which was just 18 percent. The majority of Amazon’s net sales are generated through its North American business segment, which accounted for 236.3 billion U.S. dollars in 2020. The United States are the company’s leading market, followed by Germany and the United Kingdom. Business segment: Amazon Web Services Amazon Web Services, commonly referred to as AWS, is one of the strongest-growing business segments of Amazon. AWS is a cloud computing service that provides individuals, companies and governments with a wide range of computing, networking, storage, database, analytics and application services, among many others. As of the third quarter of 2020, AWS accounted for approximately 32 percent of the global cloud infrastructure services vendor market.

DES is publishing the Amazon spend for state agencies collected through the Washington State Amazon Business account. The data set only includes closed orders. Any orders that are still in process or have been cancelled are not included. This data is for Fiscal Year 20 (July 1, 2019 to June 30, 2020)

Unlock powerful insights with the Amazon Electronics dataset, offering access to millions of records from any Amazon domain. This dataset provides comprehensive data points such as product titles, descriptions, brand details, pricing (initial and discounted), availability, customer ratings, reviews, and product categories. Additionally, it includes unique identifiers like ASINs, images, and seller information, allowing you to analyze product listings, trends, and customer preferences with precision. Use this dataset to optimize your eCommerce strategies by benchmarking competitor pricing, identifying top-performing brands, and tracking customer sentiment through reviews and ratings. Gain valuable insights into consumer demand, seasonal trends, and market gaps to make data-driven decisions that enhance your inventory management, marketing campaigns, and pricing strategies. Whether you’re a retailer, marketer, data analyst, or researcher, the Amazon Electronics dataset empowers you with the data needed to stay competitive in the dynamic eCommerce landscape. Available in various formats such as JSON, CSV, and Parquet, and delivered via flexible options like API, S3, or email, this dataset ensures seamless integration into your workflows.