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,...

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

Explore key Amazon statistics, including sales figures, user growth, Prime membership trends, marketplace data, and global reach!

In 2024, when it came to usage of consumer electronics online shops in the United States, Amazon was leading the way with 61 percent of respondents stating that they used the brand in the past 12 months. Second was Walmart, with 45 percent of people reporting to use the online shop.

Amazon revenue, AWS, Prime membership, employees, advertising, logistics, and market data 2015–2026.

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

This dataset appears to contain information about products sold on Amazon, including various attributes such as prices, ratings, availability, and sales volume. Here is a description of each column and potential analyses, modeling, and data science techniques you can use:

Column Descriptions asin: Amazon Standard Identification Number, a unique identifier for each product. product_title: The name or title of the product. product_price: The current price of the product. product_original_price: The original price of the product before any discounts. currency: The currency in which the product price is listed. product_star_rating: The average star rating of the product. product_num_ratings: The number of ratings the product has received. product_url: The URL to the product’s Amazon page. product_photo: A link to the product’s photo. product_num_offers: The number of different offers available for the product. product_minimum_offer_price: The minimum price of the offers available. is_best_seller: Indicator if the product is a best seller. is_amazon_choice: Indicator if the product is an Amazon's Choice product. is_prime: Indicator if the product is eligible for Amazon Prime. climate_pledge_friendly: Indicator if the product is labeled as Climate Pledge Friendly. sales_volume: The volume of sales for the product. delivery: Information about the delivery options for the product. has_variations: Indicator if the product has variations (e.g., different sizes or colors). product_availability: The availability status of the product. unit_price: The price per unit of measure. unit_count: The number of units included in the product price. >Potential Analyses and Data Science Techniques

Descriptive Statistics: Calculate summary statistics for numeric columns (e.g., average, median, min, max of prices, ratings, sales volume). Frequency counts for categorical columns (e.g., how many products are best sellers, Amazon's Choice, Prime eligible).

Price Analysis: Compare the current price to the original price to assess discount levels. Analyze pricing trends across different categories or brands.

Rating Analysis: Examine the distribution of product ratings. Correlate the number of ratings with the average star rating to identify trends.

Sales Volume Analysis: Identify top-selling products. Analyze sales volume in relation to pricing, rating, and other attributes.

Product Categorization: Group products based on categories such as best seller, Amazon's Choice, Prime eligibility, and Climate Pledge Friendly status. Perform clustering to identify patterns or segments among products.

Predictive Modeling: Price Prediction: Use regression models (e.g., linear regression, decision trees) to predict product prices based on features like ratings, number of offers, and best seller status. Sales Volume Prediction: Use regression or time series analysis to predict future sales volumes. Rating Prediction: Predict product ratings using features such as price, number of ratings, and best seller status.

Recommendation Systems: Build collaborative filtering or content-based recommendation systems to suggest products to customers based on their preferences and past behavior.

Classification Tasks: Classify products into different categories (e.g., best seller, Amazon's Choice) using classification algorithms (e.g., logistic regression, random forests, SVM).

Sentiment Analysis: Analyze customer reviews (if available) to gauge sentiment and correlate it with ratings and sales volume.

Market Basket Analysis: If purchase data is available, perform association rule mining to find frequently co-purchased items.

Visualization Techniques Histograms and Bar Charts: For visualizing the distribution of prices, ratings, and sales volumes.

Box Plots: For comparing prices and ratings across different product categories.

Scatter Plots: To visualize relationships between numeric variables (e.g., price vs. sales volume).

Heatmaps: To show correlations between different features.

Data Cleaning and Preprocessing Handle missing values (e.g., impute, remove). Convert categorical variables into numerical form using techniques like one-hot encoding. Normalize or scale numeric features if required for certain algorithms.

Advanced Techniques Feature Engineering: Create new features from existing data (e.g., discount percentage from original and current prices). Dimensionality Reduction: Use PCA or other techniques if the dataset has high dimensionality. These analyses and techniques can help uncover valuable insights, optimize pricing strategies, improve customer satisfaction, and ultimately drive sales and profitability.

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.

Comprehensive collection of Amazon seller statistics covering marketplace size, FBA fees, advertising benchmarks, conversion rates, profitability margins, and more. Updated monthly.

Dataset

This dataset was created by Hasan23

Contents

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.

Project Overview: > This dataset provides a cleaned and structured look at Amazon sales performance. It was used to build a comprehensive Power BI dashboard to track key business metrics. Key Metrics Analyzed: Total Revenue:32.87M Total Profit:1.64M Top Regions: Middle East and North America Product Performance: Sales distribution across categories like Beauty,Fashion,and Electronics.https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F32474469%2Ff2661d8f971acb7b52a58e53f555d88d%2Flit.png?generation=1771865520319841&alt=media" alt="">

According to forecasts as of March 2022, the sales share of electrical products on Amazon was expected at **** percent that year. By 2027, electrical products will make up **** percent of Amazon sales. Additionally, fashion and apparel was forecast to make up **** percent of Amazon sales by 2027, *** percentage point higher than in 2022.

What is this?

This is a cleaned version of Amazon Product Dataset 2020 from Kaggle.

  Why?

Using via Hugging Face API is easier; Kaggle API is annoying because their authentication is having credentials in a folder. Cleaned because 13/28 columns are empty.

Dataset

This dataset was created by datadisply

Released under Apache 2.0

Contents

Dataset

This dataset was created by Minha Manal

Contents

I roundup the latest Amazon Prime statistics which show just how big Amazon Prime has become and will continue to be.

The Amazon Sales Dataset (2019-2024) provides a comprehensive overview of sales transactions over a five-year period, covering key metrics essential for business intelligence and performance analysis. It includes 5000 records of sales data across five major regions: North America, Europe, Asia, South America, and Australia.

The dataset contains 13 key attributes, including Order ID, Order Date, Customer ID, Customer Name, Region, Product Category, Product Name, Quantity Sold, Unit Price, Discount Percentage, Total Sales, Profit Margin, Payment Method, and Order Status. These attributes provide valuable insights into revenue trends, customer behavior, regional performance, and discount effectiveness.

This dataset is ideal for visualization in Tableau, allowing analysts to explore sales performance, track profit margins, analyze the impact of discounts, and assess order fulfillment trends. With its structured format and diverse sales insights, the dataset serves as a powerful resource for data-driven decision-making. 🚀

Context

Amazon.com, Inc. is an American online retailer with a wide range of products. According to its own information, Amazon, as the market leader in Internet trade, has the world's largest selection of books, CDs and videos. Via the integrated sales platform Marketplace, private individuals or other companies can also offer new and used products as part of online trading. The Amazon Kindle is sold under its own brand as a reader for electronic books, the Amazon Fire HD tablet computer, the Fire TV set-top box, the Fire TV Stick HDMI stick and the Echo speech recognition system.

With sales of $280 billion in 2019, a profit of $11.6 billion, and a market value of $1.32 trillion (June 2020), it was the third most valuable after Apple and Microsoft, and even before Google United States company.

Market cap

Market capitalization of Amazon (AMZN)

Market cap: $2.362 Trillion USD

As of February 2025 Amazon has a market cap of $2.362 Trillion USD. This makes Amazon the world's 4th most valuable company by market cap according to our data. The market capitalization, commonly called market cap, is the total market value of a publicly traded company's outstanding shares and is commonly used to measure how much a company is worth.

Revenue

Revenue for Amazon (AMZN)

Revenue in 2024 (TTM): $637.95 Billion USD

According to Amazon's latest financial reports the company's current revenue (TTM ) is $637.95 Billion USD. an increase over the revenue in the year 2023 that were of $574.78 Billion USD. The revenue is the total amount of income that a company generates by the sale of goods or services. Unlike with the earnings no expenses are subtracted.

Earnings

Earnings for Amazon (AMZN)

Earnings in 2024 (TTM): $71.02 Billion USD

According to Amazon's latest financial reports the company's current earnings are $637.95 Billion USD. , an increase over its 2023 earnings that were of $40.73 Billion USD. The earnings displayed on this page is the company's Pretax Income.

End of Day market cap according to different sources

On Feb 20th, 2025 the market cap of Amazon was reported to be:

$2.362 Trillion USD by Yahoo Finance

$2.362 Trillion USD by CompaniesMarketCap

$2.362 Trillion USD by Nasdaq

Content

Geography: USA

Time period: May 1997- February 2025

Unit of analysis: Amazon Stock Data 2025

Variables

Acknowledgements

This dataset belongs to me. I’m sharing it here for free. You may do with it as you wish.

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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.