Facebook
Twitterhttp://opendatacommons.org/licenses/dbcl/1.0/http://opendatacommons.org/licenses/dbcl/1.0/
This dataset was created by Joy Chakraborty
Released under Database: Open Database, Contents: Database Contents
It contains the following files:
Facebook
Twitter• 200K+ Seller Leads • Seller Type: Brand/PL Seller, 1P/Amazon Vendor Central and 3P Sellers • Selling Platforms: Amazon USA, UK, EU, CA, AU • C-Suite/Marketing/Sales Contacts • FBA/FBM Sellers • Filter your leads by revenue, categories, location, SKU's and 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 specialize in getting valid 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
Facebook
TwitterTap into the power of verified Amazon sellers with our Amazon Sellers Email List, designed to help businesses connect with top eCommerce merchants. Access crucial details like Seller Name, Business Name, Contact Email, Phone Number, Revenue Size, Employee Size, and more. Enhance your marketing campaigns with highly targeted Amazon seller data, ensuring accurate outreach and increased conversions. Whether you're looking to partner with high-volume Amazon sellers or drive B2B sales, this list provides the right data to meet your goals. Key Highlights: ✅ 250K+ Amazon Sellers Worldwide ✅ Direct Contact Info for Amazon Store Owners ✅ 40+ Data Points ✅ Lifetime Access ✅ 10+ Data Segmentations ✅ FREE Sample Data
Facebook
TwitterThese 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
Facebook
TwitterDownload seller's data & convert sellers into leads into potential clients for your business. Amazon sellers' data including their addresses, brands, ASINs, phone, and more. Amazon US, UK, India, Canada, Mexico, and Italy country data available All data went through QA process We are updating data every 6 months
Facebook
TwitterAttribution-ShareAlike 4.0 (CC BY-SA 4.0)https://creativecommons.org/licenses/by-sa/4.0/
License information was derived automatically
You will get an active email list for real and active buyers who make regular purchases through Amazon and other e-commerce sites. This email list contains 100% original email address. You can also use these emails to increase visits to your website, blog, or YouTube channel. I offer you now, a great treasure to use whenever you want.
So don't waste your time and start boosting your ecommerce business online.
The buyers will be from:
United States of America Canada Europe Union
$ There are no duplicate emails $ No fake IDs $ Audiences ready to buy
Markets
market,emails,email ma,list,buyer
70150
$90.00
Facebook
Twitterhttps://brightdata.com/licensehttps://brightdata.com/license
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
Facebook
Twitterhttps://brightdata.com/licensehttps://brightdata.com/license
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.
Facebook
TwitterThis 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:
New reviews:
Metadata: - We have added transaction metadata for each review shown on the review page.
If you publish articles based on this dataset, please cite the following paper:
Facebook
TwitterDo you want to learn more about your brand's audience? Or perhaps you competitors?
With our Amazon User Profile API, you can get a list of verified past purchases of any user on Amazon with their profile URL. Our Online Reviews API can be used to extract customer reviews for any product on Amazon, including the author's profile URL. These URLs can in turn be used to retrieve some of the past purchases of these reviewers and can give you a clearer picture of the preferences of your target audience.
This data can be used to track customer loyalty and target audience for any brand that distributes using internet retail.
Facebook
TwitterNote: This dataset contains the 'Apparel' data from many of the datasets previously made available by Amazon for academic research purposes. The original source links are provided below: Dataset Readme, provided by Amazon: https://s3.amazonaws.com/amazon-reviews-pds/readme.html All Customer Review Datasets by Amazon: https://s3.amazonaws.com/amazon-reviews-pds/tsv/index.txt
Amazon Customer Reviews Dataset Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazon’s 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.
Content marketplace - Country code of the marketplace where the review was written customer_id - ID of the customer reviewed the product review_id - The unique ID of the review product_id - The unique ID of the product product_parent - ID of the parent category product_title - Title of the product product_category - Broad product category, here only 'Apparel' data is available 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 - The review was written as part of the Vine program or not 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
License By accessing the Amazon Customer Reviews Library ("Reviews Library"), you agree that the Reviews Library is an Amazon Service subject to the Amazon.com Conditions of Use (https://www.amazon.com/gp/help/customer/display.html/ref=footer_cou?ie=UTF8&nodeId=508088) and you agree to be bound by them, with the following additional conditions:
In addition to the license rights granted under the Conditions of Use, Amazon or its content providers grant you a limited, non-exclusive, non-transferable, non-sublicensable, revocable license to access and use the Reviews Library for purposes of academic research. You may not resell, republish, or make any commercial use of the Reviews Library or its contents, including use of the Reviews Library for commercial research, such as research related to a funding or consultancy contract, internship, or other relationship in which the results are provided for a fee or delivered to a for-profit organization. You may not (a) link or associate content in the Reviews Library with any personal information (including Amazon customer accounts), or (b) attempt to determine the identity of the author of any content in the Reviews Library. If you violate any of the foregoing conditions, your license to access and use the Reviews Library will automatically terminate without prejudice to any of the other rights or remedies Amazon may have. https://s3.amazonaws.com/amazon-reviews-pds/license.txt
Useful Links Provided by Amazon: https://s3.amazonaws.com/amazon-reviews-pds/readme.html Amazon Customer Review Available Datasets: https://s3.amazonaws.com/amazon-reviews-pds/tsv/index.txt
NOTE: This dataset is made available in Kaggle as the above links are no longer accessible
Facebook
TwitterSimple pricing, pay per successful result only. Say goodbye to being charged for failed requests.
Filter results by number of reviews, date
Review data includes meta data about customers such as avatar, location, profile url, etc.
Get page meta data like product price information, rating distribution, etc.
Facebook
TwitterIn 2024, Amazon was expected to generate roughly 53 billion U.S. dollars in retail media ad revenue, which would be an increase of 16 percent on its 2023 result. Alibaba, on the other hand, expected a growth rate of 1.4 percent year on year, which would put the Chinese platform at 42 billion dollars in retail media ad revenue in the same year.
Facebook
TwitterFirst of all, Amazon product datasets are indispensable for reverse engineering your rivals. For example, you can collect a list of keywords you already rank for or want to, and go through DataForSEO Amazon Products Database to find other sellers appearing as the top results for these terms.
Next, you can narrow down the scope of your contenders to those performing the best. To do so, you can filter out sellers who won the “Amazon’s Choice” and those whose products got listed multiple times on the first page.
Once you’ve compiled the final list of your challengers, Amazon Products Database will help you to quickly examine product titles, descriptions, prices, images, and other details that will let you grasp the main contributors to your competitors’ success. Once you’ve figured that out, you can start optimizing your product listings and pricing strategies to increase conversions.
However, the number of use cases for Amazon product data isn’t limited to competitor analysis. It can be applied to monitoring product rankings, running price comparisons, and more.
Facebook
TwitterApache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
License information was derived automatically
This dataset, 'Amazon Stock Data and Key Affiliated Companies,' provides comprehensive daily stock data for Amazon (AMZN) and several companies that have significantly contributed to Amazon's business growth and success. The dataset includes historical data for key players such as Intel (INTC), FedEx (FDX), United Parcel Service (UPS), Salesforce (CRM), NVIDIA (NVDA), Visa (V), and Mastercard (MA).
The stock data spans over various years, capturing important trading metrics like open, close, high, low, and volume. Amazon, a global leader in e-commerce, cloud computing, and AI, has thrived with the support of these affiliated companies. From Intel's processors powering Amazon Web Services (AWS) to Salesforce's CRM solutions used by Amazon, and the logistics support provided by FedEx and UPS, each company plays a critical role.
This dataset can be used for financial analysis, stock market prediction models, correlation studies between Amazon and its key partners, or any other research involving the financial performance of these major corporations. Whether you're interested in understanding Amazon's stock trends or the interdependency of companies in its ecosystem, this dataset provides valuable insights.
Facebook
TwitterA 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.
Facebook
TwitterAttribution-NonCommercial-NoDerivs 4.0 (CC BY-NC-ND 4.0)https://creativecommons.org/licenses/by-nc-nd/4.0/
License information was derived automatically
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,...
Facebook
TwitterThis 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.
Facebook
TwitterYouTube has emerged as the dominant social media platform for driving traffic to Amazon.com, accounting for over 60 percent of referrals to the e-commerce platform between July and September 2025. Facebook.com and Reddit.com followed, contributing about 13 and eight percent of social media referrals respectively, while Reddit and WhatsApp rounded out the top five sources. Amazon's dominance Amazon's position as the leading online retailer in the United States is evident in its traffic and sales figures. In December 2023, Amazon still recorded an impressive 2.7 billion combined visits. The company's financial performance remains strong, with a net income of approximately 13.5 billion U.S. dollars in the second quarter of 2024, up from the previous quarters. Mobile presence Amazon's mobile presence continues to grow, with its shopping app downloads reaching a nine-year peak in August 2022 at approximately 25 million. As of July 2024, the Amazon Shopping app reached over 18 million downloads across iOS and Android platforms. That month, Amazon’s shopping app was the most popular app published by the e-commerce and tech giant.
Facebook
Twitterhttps://brightdata.com/licensehttps://brightdata.com/license
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.
Facebook
Twitterhttp://opendatacommons.org/licenses/dbcl/1.0/http://opendatacommons.org/licenses/dbcl/1.0/
This dataset was created by Joy Chakraborty
Released under Database: Open Database, Contents: Database Contents
It contains the following files: