In late 2020, Hispanic and African American consumers each accounted for nearly a tenth all Amazon retail spending in the United States. Meanwhile, white consumers led the list, representing over ** percent of the e-commerce platform's consumer spending share.

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 was rolled out in India in July 2016 and within a year, India became its largest and fastest-growing market. As of **********, there were over ** million unique male visitors that accessed the platform via mobile devices. Out of this, a majority of visitors fell in the 25 to 34 year old age demographic, pointing out Amazon's popularity amongst young adults in the country.

Dataset

This dataset was created by Harsh Soni

Contents

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.

In the United Kingdom (UK), data from November 2024 based on geolocalized users showed that more than half of Amazon's mobile audience comprises people aged between 25 and 34. Younger adults from 18 to 24 years old account for the second-biggest group of mobile users in the UK, with nearly ** percent.

In the United States, consumers aged over 65 represented the biggest demographic group (** percent) of Amazon Prime services, a survey from 2025 revealed. ** percent of Amazon Prime subscribers were 55 to 64 years old.

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

Comprehensive dataset analyzing Amazon Subscribe & Save adoption rates, customer usage patterns, and category-specific statistics based on CIRP and Jungle Scout research

This dataset contains longitudinal purchases data from 5027 Amazon.com users in the US, spanning 2018 through 2022: amazon-purchases.csv It also includes demographic data and other consumer level variables for each user with data in the dataset. These consumer level variables were collected through an online survey and are included in survey.csv fields.csv describes the columns in the survey.csv file, where fields/survey columns correspond to survey questions. The dataset also contains the survey instrument used to collect the data. More details about the survey questions and possible responses, and the format in which they were presented can be found by viewing the survey instrument. A 'Survey ResponseID' column is present in both the amazon-purchases.csv and survey.csv files. It links a user's survey responses to their Amazon.com purchases. The 'Survey ResponseID' was randomly generated at the time of data collection. amazon-purchases.csv Each row in this file corresponds to an Amazon order. Each such row has the following columns: Survey ResponseID Order date Shipping address state Purchase price per unit Quantity ASIN/ISBN (Product Code) Title Category The data were exported by the Amazon users from Amazon.com and shared by users with their informed consent. PII and other information not listed above were stripped from the data. This processing occurred on users' machines before sharing with researchers.

The American Customer Satisfaction Index (ACSI) score of the e-commerce website of Amazon.com has fluctuated since 2000. In 2025, the customer satisfaction score of the online retailer was 83 out of 100 ASCI points. Popularity contest Amazon is one of the most popular marketplaces worldwide. In April 2024, the U.S. domain for Amazon ranked the most visited e-commerce and shopping website by share of online visits, with around 13 percent. Ebay came in second with roughly three percent of the visit share, and the Japanese site amazon.co.jp came in third with 2.66 percent. In the same month, global online shoppers visited amazon.com around 2.2 billion times. Why Amazon? Amazon.com is the most used e-commerce website in the world, and in the U.S., the website is far ahead of its competitors. With a significant difference in website visitors of almost 45 percent, ebay.com is second to amazon.com. Furthermore, the retail giant Walmart trails behind with an online visit share of roughly six percent. Amazon is used for various reasons by its customers. For example, the online marketplace is ranked as the leading platform for product research in the U.S., surpassing even search engines in popularity. Low shipping costs, fast deliveries, and affordable product prices are the main reasons for shopping on Amazon.

These 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

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

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

Comprehensive dataset tracking Amazon Prime member spending patterns from 2019-2024, including comparison with non-Prime customers and demographic breakdowns

This database contains images from Amazon and Atlantic Forest brazilian biomes used for training a fully convolutional neural network for the semantic segmentation of forested areas in images from the Sentinel-2 Level 2A Satellite.

The images refer to the composition of bands 4, 3, 2 and 8. Each band was converted to a byte type (0-255).

The images are still divided into three main sets: training, validation and testing:

Training dataset: it contains 499 and 485 GeoTIFF images (Amazon and Atlantic Forest, respectively) with 512x512 pixels and associated PNG masks (forest indicated in white and background in black color).

Validation dataset: it contains 100 GeoTIFF images for each biome with 512x512 pixels and associated PNG masks used for validation step.

Test dataset: it contains 20 GeoTIFF images for each biome with 512x512 pixels for testing.

This statistic illustrates the share of people who shopped at Amazon in the United States in the last 12 months as of 2022. The results were sorted by age. In 2022, ** percent of respondents aged 18 to 29 years stated they shopped at Amazon in the last 12 months. The Statista Global Consumer Survey offers a global perspective on consumption and media usage, covering the offline und online world of the consumer.

Amazon Market Outlook

The global Amazon market is poised for significant growth over the forecast period, with the market size expected to increase from $260 billion in 2023 to nearly $700 billion by 2032, growing at a compound annual growth rate (CAGR) of 11.5%. This robust expansion is driven by the increasing penetration of e-commerce, diversified product offerings, and innovative service models that Amazon continues to adopt and expand upon.

One of the primary growth factors for the Amazon market is the rapid shift of consumers towards online shopping. The convenience of shopping from home, coupled with a vast array of products and competitive pricing, has made e-commerce platforms like Amazon highly attractive. The COVID-19 pandemic further accelerated this trend, as lockdowns and social distancing measures pushed more consumers to shop online. This behavioral shift is expected to persist post-pandemic, solidifying Amazon's market position.

Another significant driver is Amazon's extensive investment in logistics and supply chain infrastructure. The company has heavily invested in technologies and facilities that enhance delivery speed and efficiency, such as automated warehouses, drone delivery systems, and an expanding network of fulfillment centers worldwide. These advancements have enabled Amazon to offer expedited delivery options, such as same-day or next-day delivery, which are critical factors in maintaining customer satisfaction and loyalty.

Furthermore, Amazon's diversification into various service offerings has substantially contributed to its growth. Services like Amazon Prime, Amazon Web Services (AWS), and Amazon Fresh have not only increased its revenue streams but also deepened customer engagement and loyalty. Amazon Prime, for instance, provides subscribers with benefits such as free shipping, access to exclusive content on Prime Video, and other perks, fostering a more engaged and loyal customer base. AWS, on the other hand, has established itself as a leader in the cloud computing industry, driving significant revenue and supporting the growth of other Amazon services.

Regionally, North America remains Amazon's largest market, accounting for a substantial share of its revenue. However, notable growth is expected in emerging markets within the Asia Pacific and Latin America regions. These regions are experiencing rapid internet penetration and a burgeoning middle class with increasing disposable incomes, making them ripe for e-commerce expansion. Amazon has been focusing on localizing its strategies to cater to the unique preferences and needs of these markets to capitalize on this potential.

Product Category Analysis

The electronics segment constitutes a significant portion of Amazon's product category, driven by a high demand for gadgets, home appliances, and other electronic items. Amazon's competitive pricing, extensive product range, and user-friendly return policies make it a preferred platform for purchasing electronics. Additionally, the seamless integration of customer reviews and ratings helps consumers make informed decisions, further boosting sales within this category. With continuous technological advancements and a steady stream of new product launches, the electronics segment is expected to maintain its growth trajectory.

Books were Amazon's original product category, and despite expanding into numerous other areas, books remain a core component of its offerings. The introduction of Kindle and e-books revolutionized the way consumers read, providing a boost to this segment. Amazon's extensive library of books, ranging from bestsellers to niche genres, caters to a wide audience. The convenience of purchasing and downloading books instantly, coupled with competitive pricing, continues to attract readers globally. The book segment is expected to see steady growth, supported by an increasing number of readers opting for e-books and audiobooks.

The clothing segment has seen substantial growth, driven by a diverse range of apparel and accessories for all ages and genders. Amazon's fashion segment includes both well-known brands and independent labels, providing a wide array of choices for consumers. The introduction of features like "Try Before You Buy" and personalized recommendations based on browsing history have enhanced the shopping experience, leading to higher conversion rates. As consumers become more comfortable with purchasing clothing online, this segment is expected to grow significantly.

Comprehensive analysis of Amazon marketplace average order values across categories, customer types, and promotional periods. Includes Prime vs non-Prime comparisons and category-specific AOV ranges.

This dataset comprises customer reviews for Amazon, an online retail giant, featuring insights into customer experiences, including ratings, review titles, texts, and metadata. It is valuable for analyzing customer satisfaction, sentiment, and trends.

Column Descriptions:

Reviewer Name: Identifies the reviewer. Profile Link: Links to the reviewer's profile for additional insights. Country: Indicates the reviewer's location. Review Count: Number of reviews by the same user, showing engagement level. Review Date: When the review was posted, useful for time analysis. Rating: Numerical satisfaction measure. Review Title: Summarizes the review sentiment. Review Text: Detailed customer feedback. Date of Experience: When the service/product was experienced.

Prospective applications:

Sentiment Analysis: Analyze review texts and titles to assess overall customer sentiment toward products, enabling the identification of strengths and weaknesses. Customer Satisfaction Tracking: Track and visualize rating trends over time to understand fluctuations in customer satisfaction. Product Improvement: Identify common themes in reviews to highlight areas for product enhancement or development. Market Segmentation: Use country and demographic information to customize marketing strategies and gain insights into regional preferences. Competitor Analysis: Evaluate customer feedback on Amazon products in comparison to competitors to determine market positioning. Recommendation Systems: Leverage review data to enhance recommendation algorithms, improving personalized shopping experiences. Trend Analysis: Investigate temporal patterns in reviews to link sentiment changes with marketing efforts or product launches.

This extensive dataset serves as a valuable asset for various analyses focused on enhancing customer engagement and refining business strategies.