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,...

Amazon Prime is constantly growing in the United States: as of December 2019, there were an estimated *** million U.S. Amazon Prime subscribers, up from ** million in June 2018. On average, Amazon Prime members spent ***** U.S. dollars on the e-retail platform per year. March 2019 data also states that non-Prime members only spent *** U.S. dollars annually. Amazon Prime Amazon Prime is a paid subscription service offered by online retail platform Amazon. The subscription includes services such as music and video streaming, free two-day (or faster) shipping, as well as many other benefits. The program was launched in 2005 and is available internationally. In 2019, Amazon generated ***** billion U.S. dollars in revenues through its subscription services segment. Subscription services do not only include Amazon Prime revenues, but also audiobook, e-book, digital video, digital music and other non-AWS subscription services. Prime shoppers The most popular product categories purchased by Amazon Prime shoppers in the United States were electronics, apparel, and home and kitchen goods. Amazon Prime shoppers are more engaged that non-members: during a February 2019 survey, 20 percent of Amazon Prime members stated that they shopped on Amazon a few times per week, with ***** percent saying that they did so on an (almost) daily basis.

Key Amazon statistics for 2025 tailored to ecommerce and print-on-demand founders, covering users, revenue growth, Prime reach, seller mix, and mobile demand.

The online marketplace Amazon.eg registered a total of **** million visits in February 2025. The number of monthly visits dropped compared to the previous month. Amazon.eg is among Africa's leading e-commerce platforms and is only available in Egypt. The platform was previously known as souq.com. It changed to Amazon.eg in the second half of 2021 after being acquired by the e-commerce giant Amazon previously.

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.

In fiscal year 2025, the total number of employees at Amazon.com was 1,556,000. The employee count increasedby 31,000 from 1,525,000 (in 2024) to 1,556,000 (in 2025). It represents a 2.03% year-over-year growth in employee count.

Amazon Prime’s growth is what has been most impressive. They have managed to convert millions of customers into loyal subscribers at a very fast rate.

Amazon made $40.2 billion from memberships and subscriptions in 2023.

In 2011, Amazon launched its operations in Brazil and has since established ten fulfillment centers, with an estimated *** delivery stations as of 2025. Brazilian customers can subscribe to Amazon Prime for a monthly fee of **** reals (approximately four U.S. dollars). This membership offers exclusive benefits, including free shipping, unlimited movie and TV show streaming, and early access to selected special deals.

Comprehensive dataset analyzing Amazon product review counts across categories, including 40 reviews average, category-specific benchmarks, and reviews-to-sales ratios based on analysis of 31,900 brands and 12 million product reviews.

Amazon reported 1.56M in Employees for its fiscal year ending in December of 2024. Data for Amazon | AMZN - Employees Total Number including historical, tables and charts were last updated by Trading Economics this last December in 2025.

Context: The "Amazon Books Dataset" is a meticulously curated collection of data related to books available on the Amazon platform, with a primary focus on computer science literature. This dataset holds significant importance for researchers, industry experts, and enthusiasts who are interested in gaining profound insights into the world of computer science literature, publishing trends, and the broader book market. Computer science is at the forefront of technological innovation and is a driving force in shaping the modern world. Understanding the dynamics of the Amazon book market, particularly in the realm of computer science, is essential for various stakeholders in the publishing, technology, and retail industries.

Data Source: The data for this dataset has been meticulously sourced and compiled from Amazon's extensive catalog of books, with a specific emphasis on books related to computer science. The information is current as of the dataset's creation date and may continue to evolve as new books are published and existing ones undergo changes in attributes such as ratings and prices.

Content: The "Amazon Books Catalog Dataset" provides a rich and comprehensive array of data points for each book listed on Amazon, with a primary focus on computer science literature. These data points empower users to conduct in-depth analyses and uncover valuable insights. Here are the key columns included in this dataset:

1. Title: The title of the book, represents its core identity.
2. Description: A concise yet informative overview of the book's content and themes.
3. Author: The name(s) of the author(s) responsible for creating the literary work.
4. ISBN-10: The International Standard Book Number in the 10-digit format, aiding in precise identification.
5. ISBN-13: The International Standard Book Number in the 13-digit format, enhancing global recognition.
6. Publish Date: The date on which the book was officially published, marking its entry into the literary world.
7. Edition: Information about the edition of the book, if applicable, providing insights into its various releases.
8. Best Seller: A binary indicator (1 or 0) signifying whether the book has achieved best-seller status.
9. Top Rated: A binary indicator (1 or 0) highlighting whether the book has received high ratings and acclaim from readers.
10. Rating: The average rating awarded to the book by Amazon customers, offering an assessment of its quality.
11. Review Count: The total number of user reviews posted for the book, reflecting reader engagement and feedback.
12. Price: The current price of the book on the Amazon platform, influences purchase decisions.

Potential Use Cases: This dataset, with its focus on computer science literature, presents a unique opportunity for research and analysis in fields such as:

• Technology Trends: Analyzing emerging trends in computer science literature, including topics, technologies, and subfields.
• Educational Insights: Investigating the popularity of computer science textbooks and learning materials.
• Author Impact: Assessing the influence and contributions of authors within the computer science domain.
• Market Analysis: Understanding pricing dynamics and factors influencing the success of computer science books.

Researchers, analysts, and computer science enthusiasts can leverage this dataset to explore the intricate world of computer science literature, uncover market trends, and contribute to a deeper understanding of the evolving landscape of technology and knowledge dissemination on one of the world's largest online marketplaces.

For the first time since 2016, the number of Amazon Prime members has declined in the United States. In the first quarter of 2023, *** million users had a Prime account on Amazon, down by roughly ***** compared to the same quarter in 2022. In 2024, it picked up again, reaching *** million subscribers. Evolving subscription landscape The broader subscription retail market continues to evolve, with merchants adapting to consumer preferences. A 2023 survey found that **** percent of top merchants offering subscription-based retail provided options for customers to change their subscribed products and pause their subscriptions. Additionally, ** percent of merchants offered detailed product information, while ** percent allowed subscribers to pause their services. Advantages of subscription models For businesses, the subscription model is attractive due to higher customer lifetime value and retention rates compared to one-time transactions. From their side, consumers expect specific features such as free shipping and easy sign-outs, while valuing tailored discounts and sale promotions.

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 Prime’s global subscriber growth rate has accelerated over the last 5 years. Today Amazon currently has 200 million Amazon Prime members around the world.

About Dataset

This dataset contains detailed information about phones listed on Amazon, including product specifications, user reviews, ratings, and pricing. The dataset can be useful for analyzing product trends, consumer preferences, pricing strategies, and technical features of smartphones sold on the platform. It includes both new and Amazon-renewed phones.

Description

The dataset includes the following key features:

• Color: The available color of the phone.
• Image Links: URLs to the images of the products.
• Descriptions: Detailed descriptions of the phone, including specifications.
• Kind Product: The type or category of the product (smartphones, accessories, etc.).
• Ratings: User ratings (out of 5 stars).
• Number of Ratings: Total count of ratings the product has received.
• Status: Availability status (e.g., In Stock, Out of Stock).
• Number of Buyers Last Month More Than: Approximate number of buyers in the previous month.
• Typical Price: The regular price with usd of the phone without any discounts.
• Price: The current price with usd of the phone.
• You Save: The amount saved if the phone is on discount.
• Discount: The percentage discount offered on the product.
• Brand: The brand name of the phone (e.g., Apple, Samsung).
• OS: The operating system of the phone (e.g., Android, iOS).
• CPU Model: The model of the processor used in the phone.
• Resolution: The screen resolution of the phone.
• Name: The product name as listed on Amazon.
• Wireless Carrier: The supported wireless carrier (e.g., Verizon, AT&T).
• Cellular Technology: The cellular network technology (e.g., 4G, 5G).
• Dimensions: Physical dimensions of the phone.
• ASIN: Amazon Standard Identification Number, a unique product identifier.
• Model: The model number of the phone.
• Amazon Renewed: Indicates whether the product is part of the Amazon Renewed program (refurbished).
• Renewed Smartphones: Additional flag indicating if the phone is renewed.
• Battery Capacity: The capacity of the phone’s battery (in mAh).
• Battery Power: The power rating of the battery.
• Charging Time: Time taken to charge the phone fully.
• RAM: The amount of RAM in the phone.
• Storage: Internal storage capacity of the phone.
• Screen Size: Size of the display (in inches).
• Connectivity Technologies: Wireless technologies supported by the phone (e.g., Bluetooth, Wi-Fi).
• Wireless Network: Type of wireless networks supported (e.g., Wi-Fi 6).
• CPU Speed: The speed of the phone’s CPU (in GHz).
• Reviews USA: User reviews originating from the USA.
• Reviews Other: User reviews from countries other than the USA.

Detail

This dataset includes a comprehensive range of variables, offering insight into both the technical aspects and customer perceptions of various smartphones sold on Amazon. The dataset allows for:

• Product Comparisons: Comparison of specifications like RAM, CPU, storage, battery life, screen size, etc.
• Pricing Analysis: Understanding pricing trends, discounts, and price fluctuations across different brands and models.
• Consumer Insights: Analysis of consumer behavior through ratings, reviews, and the number of buyers over time.
• Product Availability: Insights into stock availability and how often certain products are sold or renewed.

Usage

The dataset can be used for several purposes, including but not limited to:

1. Market Research: Analyze product popularity and trends in smartphone sales on Amazon.
2. Sentiment Analysis: Perform sentiment analysis on reviews (USA and other countries) to understand customer satisfaction.
3. Price Forecasting: Build models to forecast price changes or identify the best time to buy based on historical data.
4. Product Recommendations: Develop recommendation systems based on user reviews, ratings, and product features.
5. Competitive Analysis: Compare different brands and models to identify strengths and weaknesses of various smartphones.
6. Feature Engineering for ML Models: Use product specifications like RAM, CPU speed, and battery power to create features for predictive machine learning models.

Summary

This Amazon product phones dataset provides an in-depth look at smartphones sold on Amazon, covering everything from technical specifications to user reviews and pricing. It is ideal for anyone looking to analyze trends in the smartphone market, consumer preferences, or technical specifications. The data can be leveraged for a wide array of projects such as market analysis, machine learning, and competitive intelligence.

• 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

Content

In this dataset you'll find over 30,000 Amazon products and details about prices, reviews, item numbers, urls, images and more.

Acknowledgements

This data comes from https://data.world/promptcloud/amazon-product-details-usa-2020.

Overall the US accounts for about 74% of all paying Amazon Prime accounts globally.

According to the latest Amazon Prime statistics, about 81% of US internet users aged 18 to 34 have a paid Amazon Prime membership.