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.

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.

Amazon revenue for the twelve months ending March 31, 2025 was $650.313B, a 10.08% increase year-over-year. Amazon annual revenue for 2024 was $637.959B, a 10.99% increase from 2023. Amazon annual revenue for 2023 was $574.785B, a 11.83% increase from 2022. Amazon annual revenue for 2022 was $513.983B, a 9.4% increase from 2021.

According to forecasts, net sales of electrical products on Amazon are forecast at over *** billion U.S. dollars. With a compound annual growth rate of **** percent, this figure is expected to exceed *** billion dollars by 2026. Yet, the category expected to grow the strongest on the e-commerce platform is health and beauty.

In 2024, Amazon's total consolidated net sales revenue amounted to *** billion U.S. dollars, *** billion U.S. dollars of which were generated through international revenue channels. North America was the biggest operations segment, accumulating nearly *** billion U.S. dollars in net sales during the year. Sales activities Amazon appeals because it sells a wide range of products. Its departments include beauty, clothing, electronics, games and even wine, along with digital products and subscription services. In 2022, Amazon's largest revenue segment was online retail product sales with roughly *** billion U.S. dollars in global net sales. Retail third-party seller services ranked second with nearly *** billion U.S. dollars in sales. A weak spot Faster and more efficient delivery services come with a price. Data from the company's financial reports showed that Amazon's worldwide shipping costs amounted to a staggering **** billion U.S. dollars, up from **** billion U.S. dollars in 2021. Amazon's annual fulfillment expenses have also risen steadily, from **** billion U.S. dollars in 2021 to over ** billion U.S. dollars in 2022.

Amazon Products dataset to explore detailed product listings, pricing, reviews, and sales data. Popular use cases include competitive analysis, market trend forecasting, and e-commerce strategy optimization.

Use our Amazon Products dataset to explore detailed information on products across various categories, including pricing, reviews, ratings, and sales data. This dataset is ideal for e-commerce professionals, market analysts, and product managers looking to analyze market trends, optimize product listings, and refine competitive strategies.

Leverage this dataset to track pricing trends, assess customer feedback, and uncover popular product categories. Whether you're conducting competitive analysis, performing market research, or optimizing product strategies, the Amazon Products dataset provides key insights to stay ahead in the e-commerce landscape.

Dataset Features

• Title: The name or title of the product.
• seller_name: The name of the seller offering the product.
• Brand: The brand associated with the product.
• Description: A detailed description of the product, including key features.
• initial_price: The original price of the product before any discounts.
• final_price: The current price of the product after discounts.
• Currency: The currency in which the product is priced (e.g., GBP, USD).
• Availability: The stock status (e.g., in stock, out of stock).
• reviews_count: The total number of customer reviews.
• Categories: The specific category the product belongs to.
• asin: Amazon Standard Identification Number.
• buybox_seller: The seller currently winning the Amazon Buy Box.
• number_of_sellers: The number of sellers offering this product.
• root_bs_rank: The overall ranking of the product in the Amazon best-sellers list.
• answered_questions: The number of questions answered in the product Q&A section.
• domain: The website domain where the product is being sold.
• images_count: The number of images available for the product.
• URL: The link to the product page on Amazon.
• video_count: The number of videos available for the product.
• image_url: The URL of the primary image associated with the product.
• item_weight: The weight of the product.
• Rating: The average rating of the product based on customer reviews.
• product_dimensions: The dimensions of the product (e.g., length, width, height) and weight.
• seller_id: The unique identifier for the seller.
• date_first_available: The date when the product was first made available on Amazon.
• discount: Any discount applied to the product.
• model_number: The model number of the product.
• manufacturer: The company that manufactures the product.
• department: The department under which the product is categorized (e.g., Health & Household).
• plus_content: A flag indicating if the product has Amazon’s “Plus Content” (additional marketing content).
• upc: The Universal Product Code (UPC) associated with the product.
• video: URL(s) of any video content associated with the product.
• top_review: A summary or excerpt from the top customer review.
• variations: Different product variations (e.g., different sizes or flavors).
• delivery: Information on the delivery options (e.g., free delivery or Prime delivery).
• features: Key features or highlights of the product.
• format: The format of the product (e.g., powder, liquid).
• buybox_prices: Pricing details for the product, including the base and tiered prices.
• parent_asin: The ASIN of the parent product (if the product is part of a larger group of similar products).
• input_asin: The ASIN of the product as input for Amazon searches.
• ingredients: List of ingredients in the product (if applicable).
• origin_url: The source URL for product-related information or ingredients.
• bought_past_month: A flag indicating if the product was bought in the past month.
• is_available: Availability status of the product (True/False).
• root_bs_category: The broad product category (e.g., Health & Household).
• bs_category: The specific subcategory the product belongs to.
• bs_rank: The rank of the product in its specific subcategory.
• badge: Any badge or label the product has earned (e.g., Amazon's Choice).
• subcategory_rank: The rank of the product within its subcategory.
• amazon_choice: A flag indicating if the product has been selected as Amazon’s Choice.
• images: A list of URLs for additional product images.
• product_details: Detailed product specifications and features.
• prices_breakdown: A breakdown of the price, including any discounts or promotions.
• country_of_origin: The country where the product is made.
• from_the_brand: Information from the brand or manufact

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

Amazon reported $155.7B in Sales Revenues for its fiscal quarter ending in March of 2025. Data for Amazon | AMZN - Sales Revenues including historical, tables and charts were last updated by Trading Economics this last July in 2025.

• 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

Amazon-Products Analysis: Description: This dashboard provides a comprehensive analysis of product performance, enabling data-driven insights to improve revenue growth, identify top-selling products, and optimize pricing strategies. It leverages data from Product Categories, Subcategories, Actual Price, Discount Price, ratings,Discount to visualize key metrics and trends.

Objective: The dashboard aims to empower stakeholders with actionable insights to make informed decisions related to sales strategy, pricing optimization, and product performance. By visualizing key metrics and trends, it facilitates data-driven actions to enhance revenue, customer satisfaction, and overall business success.

During the first quarter 2025, Amazon generated total net sales of nearly *** billion U.S. dollars, surpassing the *** billion U.S. dollars in the same quarter of 2024. From books to billions Launched in 1995 in the United States as an online bookshop, Amazon has since grown into an international e-commerce giant. In April 2023 worldwide visits to amazon.com amounted to over *** billion considering both desktop and mobile traffic. Prime time in the U.S. Although a global company, Amazon truly thrives in the United States where the company is the leading e-commerce platform by sales value. In the North American country, the number of subscribers using Amazon Prime services has been growing steadily over the last several years and is forecast to reach new heights in 2024.

This repository was created for my Master's thesis in Computational Intelligence and Internet of Things at the University of Córdoba, Spain. The purpose of this repository is to store the datasets found that were used in some of the studies that served as research material for this Master's thesis. Also, the datasets used in the experimental part of this work are included.

Below are the datasets specified, along with the details of their references, authors, and download sources.

----------- STS-Gold Dataset ----------------

The dataset consists of 2026 tweets. The file consists of 3 columns: id, polarity, and tweet. The three columns denote the unique id, polarity index of the text and the tweet text respectively.

Reference: Saif, H., Fernandez, M., He, Y., & Alani, H. (2013). Evaluation datasets for Twitter sentiment analysis: a survey and a new dataset, the STS-Gold.

File name: sts_gold_tweet.csv

----------- Amazon Sales Dataset ----------------

This dataset is having the data of 1K+ Amazon Product's Ratings and Reviews as per their details listed on the official website of Amazon. The data was scraped in the month of January 2023 from the Official Website of Amazon.

Owner: Karkavelraja J., Postgraduate student at Puducherry Technological University (Puducherry, Puducherry, India)

Features:

• product_id - Product ID
• product_name - Name of the Product
• category - Category of the Product
• discounted_price - Discounted Price of the Product
• actual_price - Actual Price of the Product
• discount_percentage - Percentage of Discount for the Product
• rating - Rating of the Product
• rating_count - Number of people who voted for the Amazon rating
• about_product - Description about the Product
• user_id - ID of the user who wrote review for the Product
• user_name - Name of the user who wrote review for the Product
• review_id - ID of the user review
• review_title - Short review
• review_content - Long review
• img_link - Image Link of the Product
• product_link - Official Website Link of the Product

License: CC BY-NC-SA 4.0

File name: amazon.csv

----------- Rotten Tomatoes Reviews Dataset ----------------

This rating inference dataset is a sentiment classification dataset, containing 5,331 positive and 5,331 negative processed sentences from Rotten Tomatoes movie reviews. On average, these reviews consist of 21 words. The first 5331 rows contains only negative samples and the last 5331 rows contain only positive samples, thus the data should be shuffled before usage.

This data is collected from https://www.cs.cornell.edu/people/pabo/movie-review-data/ as a txt file and converted into a csv file. The file consists of 2 columns: reviews and labels (1 for fresh (good) and 0 for rotten (bad)).

Reference: Bo Pang and Lillian Lee. Seeing stars: Exploiting class relationships for sentiment categorization with respect to rating scales. In Proceedings of the 43rd Annual Meeting of the Association for Computational Linguistics (ACL'05), pages 115–124, Ann Arbor, Michigan, June 2005. Association for Computational Linguistics

File name: data_rt.csv

----------- Preprocessed Dataset Sentiment Analysis ----------------

Preprocessed amazon product review data of Gen3EcoDot (Alexa) scrapped entirely from amazon.in
Stemmed and lemmatized using nltk.
Sentiment labels are generated using TextBlob polarity scores.

The file consists of 4 columns: index, review (stemmed and lemmatized review using nltk), polarity (score) and division (categorical label generated using polarity score).

DOI: 10.34740/kaggle/dsv/3877817

Citation: @misc{pradeesh arumadi_2022, title={Preprocessed Dataset Sentiment Analysis}, url={https://www.kaggle.com/dsv/3877817}, DOI={10.34740/KAGGLE/DSV/3877817}, publisher={Kaggle}, author={Pradeesh Arumadi}, year={2022} }

This dataset was used in the experimental phase of my research.

File name: EcoPreprocessed.csv

----------- Amazon Earphones Reviews ----------------

This dataset consists of a 9930 Amazon reviews, star ratings, for 10 latest (as of mid-2019) bluetooth earphone devices for learning how to train Machine for sentiment analysis.

This dataset was employed in the experimental phase of my research. To align it with the objectives of my study, certain reviews were excluded from the original dataset, and an additional column was incorporated into this dataset.

The file consists of 5 columns: ReviewTitle, ReviewBody, ReviewStar, Product and division (manually added - categorical label generated using ReviewStar score)

License: U.S. Government Works

Source: www.amazon.in

File name (original): AllProductReviews.csv (contains 14337 reviews)

File name (edited - used for my research) : AllProductReviews2.csv (contains 9930 reviews)

----------- Amazon Musical Instruments Reviews ----------------

This dataset contains 7137 comments/reviews of different musical instruments coming from Amazon.

This dataset was employed in the experimental phase of my research. To align it with the objectives of my study, certain reviews were excluded from the original dataset, and an additional column was incorporated into this dataset.

The file consists of 10 columns: reviewerID, asin (ID of the product), reviewerName, helpful (helpfulness rating of the review), reviewText, overall (rating of the product), summary (summary of the review), unixReviewTime (time of the review - unix time), reviewTime (time of the review (raw) and division (manually added - categorical label generated using overall score).

Source: http://jmcauley.ucsd.edu/data/amazon/

File name (original): Musical_instruments_reviews.csv (contains 10261 reviews)

File name (edited - used for my research) : Musical_instruments_reviews2.csv (contains 7137 reviews)

This Excel-based dashboard visualizes Amazon sales performance using KPIs such as Total Sales, Profit, and Quantity Sold. Built with Pivot Tables, Slicers, and Charts, the dashboard includes regional breakdowns, product performance, and trend analysis. Suitable for beginners learning Sales Operations and Excel Dashboarding.

It’s Amazon’s world, and we’re just living in it. At least, that’s what it feels like most days. Just look at the stats: There are 2.3 million active sellers on Amazon this year Amazon Prime has 126 million members in the US alone Amazon’s sales revenue was $75.5 billion – just in the first quarter […]

In 2024, Amazon Web Services (AWS) generated ****** billion US dollars with its cloud services. From 2013 until today, the annual revenue of AWS cloud computing and hosting solutions continually increased.

Amazon—additional information Amazon.com went online in 1995, initially as a book store, and achieved almost immediate success. In 1998, the store expanded to include a music and video store and different other products, such as apparel and consumer electronics, in the following years. The company is the undisputed leader of the e-retail market in the United States, ranking ahead of walmart.com and apple.com in terms of revenue. Amazon Web Services In 2006, AWS launched as a cloud computing platform to provide online services. Amazon Elastic Compute Cloud and Amazon S3, which provide large virtual computing capacity, are the most well-known of these services. The company has dozens of locations in ** different regions across the world and is continually expanding its global infrastructure to ensure low latency through proximity to the user. From these data centers, Amazon is offering more than *** fully featured services to its global customer base. Video streaming service Netflix is one of AWS’s largest customers, using Amazon’s services to store their content on servers throughout the world. Among its more than *********** active users, AWS also lists other well-known organizations from various industries, such as Disney, the UK Ministry of Justice, Kellogg’s, Guardian News and Media, and the European Space Agency.

Tap 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

In 2025, Amazon Prime Day sales were estimated to have reached nearly ** billion U.S. dollars in the United States, as the latest edition of the sale event lasted **** days instead of ***. Originally launched in July 2015 as an anniversary celebration of Amazon's founding, the annual event has become one of the biggest online shopping days worldwide. While in 2020 Prime Day was moved to October due to the coronavirus pandemic, in 2021 the celebration was held in the month of June. On both occasions the event lasted ** consecutive hours.

The momentum of Databricks (not yet public) and Snowflake to re-write the reality of data in the Cloud truly is a sight to behold. Snowflake fell in extended trading on Wednesday after the company released third-quarter results that beat estimates but offered light product revenue guidance. However its stock price later bounced back even stronger. Go figure? A lot of hype… SNOW Up 10%, it’s really in a league of its own for growth in the Cloud. With a market cap close to $50 billion (data taken from its stock price in Excel), it’s hard to evaluate the business fundamentals away from the hype. The promise of unified data is very tantalizing indeed, yet when Databricks goes public, I don’t see Snowflake dominating like it has been in recent times. The Company’s platform enables customers to consolidate data into a single source to drive business insights, build data-driven applications and share data. Snowflake said it anticipates product revenue will be between $535 and $540 million in its fourth quarter, short of the $553 million expected by analysts estimates according to StreetAccount. Yet investors don’t seem to mind. Snowflake Inc. Shares have lost about 59.7% since the beginning of the year versus the S&P 500's decline of -17%. The recent low was $119 in June, 2022. You can read their Earnings here. Snowflake Earnings Product revenue of $522.8 million in the third quarter, representing 67% year-over-year growth Remaining performance obligations of $3.0 billion, representing 66% year-over-year growth 7,292 total customers Net revenue retention rate of 165% 287 customers with trailing 12-month product revenue greater than $1 million Revenue for the quarter was $557.0 million, representing 67% year-over-year growth. I can see why Snowflake is so popular though. Snowflake is Wildly Popular Currently Snowflake is wildly popular as one of the best growth stocks, . Snowflake provides an end to end data warehousing solution. There is practically no limit to the amount of databases and warehouses you can create (Ofcourse, you need Snowflake credits for creating and using warehouses). It's a highly scalable solution that adheres to all the data security best practices. I do believe Databricks is the better company in the end, but time will tell. Why would this company have a market cap of $50 billion already? They have 5,000 employees, lose money at a good clip and will experience significant competition in the coming years. Net Loss is Concerning Snowflake may not respond well to the significant slowdown in spending we are likely to see in 2023. It needs to significantly reset to be tempting. It does have 287 customers with trailing 12-month product revenue greater than $1 million which is encouraging. It’s growth in the 45-50% range is still very impressive for a company of its size. After 2023 we’ll have a much better idea of the real momentum of Snowflake. Snowflake reported 34% year-over-year growth in the number of customers, reaching 7,292 in the reported quarter. The company added 28 Forbes Global 2000 customers in the reported quarter. Snowflake signed 14 new customers with $1 million in trailing 12-month product revenues in the reported quarter. The real question is how much will it slow down in 2023. The Data Cloud is still Nascent While it’s appealing to invest in first-movers like Snowflake or later Databricks, how will competition and the Data cloud continue to evolve? It’s fairly hard to predict. Snowflake is not a traditional SaaS model, it’s pay as you go consumption based. It’s not yet clear if this is the right business model for optimal profitability. 93% of revenue is consumption-based Revenue recognized only as consumption occurs In many cases, rollover of unused capacity permitted, generally on the purchase of additional capacity Contract durations increasing along with larger customer commitments Primarily billed annually in advance with some on-demand in arrears If you are uncertain of Snowflake’s growth you can visit their visual Earnings PDF. The TAM of the Data Cloud is big enough for room for a lot of different kinds of companies and competitors. In our opinion, Snowflake is in a prime position to compete with AMD, one of the best value stocks. To read more about other Cloud Computing companies, check out: Apple Fair Value Apple P/E Apple EV/EBITDA Microsoft Fair Value Microsoft P/E Microsoft EV/EBITDA Tesla Fair Value Tesla P/E Tesla EV/EBITDA Amazon Fair Value Amazon P/E Amazon EV/EBITDA Netflix Fair Value Netflix P/E Netflix EV/EBITDA

E-commerce companies sell various goods and associated services through online portals, either on websites, mobile applications or integrated into social media platforms. Internet access across Europe is rapidly accelerating, with the vast majority of countries boasting usage rates of over 80% of the population. The spread of fast broadband and mobile data has enabled rising numbers of Europeans to engage in e-shopping. Over the five years through 2024, e-commerce revenue in Europe is forecast to climb at a compound annual rate of 2.9% to reach €324.9 billion. E-tailers benefit from lower overhead costs than brick-and-mortar stores, enabling them to offer highly competitive prices to their customers and draw sales away from traditionally popular establishments like department stores. E-tailers have taken off by leveraging these cost advantages to appeal to an increasingly price-conscious consumer base. The expansion of value-added services like ‘Buy now, pay later’ and fast, flexible delivery options have contributed to some hefty industry growth. Sky-high inflation across much of Europe has severely dented Europeans’ spending power, with drops in sales volumes affecting many online stores in 2023. Despite this, revenue continues on an upwards trajectory as inflation swamps the drop in volume sales, with an estimated 1.1% growth rate in 2024. Looking forward, internet penetration will continue to provide a growing market for e-tailers, driving revenue upwards at a projected compound annual rate of 7.2% to reach €686.4 billion over the five years through 2029. E-tailers will continue to adapt their business practises and product selections to reflect the ever-growing level of environmental awareness. Delivery fleets will become fully electrified for many companies, while increasingly stringent waste regulations will force companies to adopt biodegradable or recyclable packaging in the coming years. The integration of AI and data analytics will transform business operations, making them more efficient and help to lower wage costs, supporting profitability.

In 2019, Amazon's retail e-commerce sales in the United States amounted to ***** billion U.S. dollars and are projected to surpass *** billion U.S. dollars in 2021. The platform is the biggest e-retailer in the United States, ahead of brick-and-mortar-based competitors Walmart and Target.