66 datasets found
  1. b

    Amazon Statistics (2025)

    • businessofapps.com
    Updated Jul 20, 2025
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    Business of Apps (2025). Amazon Statistics (2025) [Dataset]. https://www.businessofapps.com/data/amazon-statistics/
    Explore at:
    Dataset updated
    Jul 20, 2025
    Dataset authored and provided by
    Business of Apps
    License

    Attribution-NonCommercial-NoDerivs 4.0 (CC BY-NC-ND 4.0)https://creativecommons.org/licenses/by-nc-nd/4.0/
    License information was derived automatically

    Description

    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,...

  2. amazon

    • kaggle.com
    Updated Sep 12, 2021
    + more versions
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    Abhilash Datta (2021). amazon [Dataset]. https://www.kaggle.com/datasets/abhilashdatta/amazon/data
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Sep 12, 2021
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Abhilash Datta
    Description

    Dataset

    This dataset was created by Abhilash Datta

    Contents

  3. b

    Amazon reviews Dataset

    • brightdata.com
    .json, .csv, .xlsx
    Updated Mar 21, 2023
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    Bright Data (2023). Amazon reviews Dataset [Dataset]. https://brightdata.com/products/datasets/amazon/reviews
    Explore at:
    .json, .csv, .xlsxAvailable download formats
    Dataset updated
    Mar 21, 2023
    Dataset authored and provided by
    Bright Data
    License

    https://brightdata.com/licensehttps://brightdata.com/license

    Area covered
    Worldwide
    Description

    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.

  4. amazon

    • kaggle.com
    Updated May 13, 2025
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    Sümeyra (2025). amazon [Dataset]. https://www.kaggle.com/datasets/smeyra/amazon
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    May 13, 2025
    Dataset provided by
    Kaggle
    Authors
    Sümeyra
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    Dataset

    This dataset was created by Sümeyra

    Released under MIT

    Contents

  5. Product searches on Amazon vs. Google in selected European markets 2022

    • statista.com
    Updated Jun 26, 2025
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    Statista (2025). Product searches on Amazon vs. Google in selected European markets 2022 [Dataset]. https://www.statista.com/statistics/1368305/amazon-vs-google-product-searches-europe/
    Explore at:
    Dataset updated
    Jun 26, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jul 2022
    Area covered
    France, Germany, United Kingdom, Italy, Spain
    Description

    In most cases, online product search doesn't start on Google. In 2022, only ** percent of Italian shoppers reported to have looked for a product on the search engine. The remaining ** percent browsed on Amazon. Likewise, ** percent of Spanish shoppers looked for products on Amazon website and ** percent of German respondents did the same.

  6. Amazon

    • kaggle.com
    Updated Apr 21, 2023
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    Narendran Saravanan (2023). Amazon [Dataset]. https://www.kaggle.com/datasets/narendransaravanan/amazon
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Apr 21, 2023
    Dataset provided by
    Kaggle
    Authors
    Narendran Saravanan
    Description

    Dataset

    This dataset was created by Narendran Saravanan

    Contents

  7. Number of U.S. Amazon Prime subscribers 2013-2019

    • statista.com
    Updated Jul 10, 2025
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    Statista (2025). Number of U.S. Amazon Prime subscribers 2013-2019 [Dataset]. https://www.statista.com/statistics/546894/number-of-amazon-prime-paying-members/
    Explore at:
    Dataset updated
    Jul 10, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Dec 2013 - Dec 2019
    Area covered
    United States
    Description

    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.

  8. Buy Now, Pay Later (BNPL) purchases on Amazon Prime Day in the U.S....

    • statista.com
    Updated Jul 15, 2025
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    Statista (2025). Buy Now, Pay Later (BNPL) purchases on Amazon Prime Day in the U.S. 2022-2025 [Dataset]. https://www.statista.com/statistics/1400479/bnpl-purchases-on-amazon-prime-day-united-states/
    Explore at:
    Dataset updated
    Jul 15, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In 2025, more U.S. shoppers purchased discounted products with Buy Now, Pay Later (BNPL) options during Amazon Prime Days. Data regarding the 2025 edition of the sale event indicated that BNPL orders had a value of nearly *** billion U.S. dollars.

  9. Datasets for Sentiment Analysis

    • zenodo.org
    csv
    Updated Dec 10, 2023
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    Julie R. Repository creator - Campos Arias; Julie R. Repository creator - Campos Arias (2023). Datasets for Sentiment Analysis [Dataset]. http://doi.org/10.5281/zenodo.10157504
    Explore at:
    csvAvailable download formats
    Dataset updated
    Dec 10, 2023
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Julie R. Repository creator - Campos Arias; Julie R. Repository creator - Campos Arias
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    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)

  10. Amazon ML

    • kaggle.com
    Updated Apr 22, 2023
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    Gaurav Srivastava (2023). Amazon ML [Dataset]. https://www.kaggle.com/datasets/scipygaurav/amazon-ml
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Apr 22, 2023
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Gaurav Srivastava
    Description

    Dataset

    This dataset was created by Gaurav Srivastava

    Contents

  11. Amazon Datasettt

    • kaggle.com
    Updated Sep 14, 2024
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    officialsiddartha (2024). Amazon Datasettt [Dataset]. https://www.kaggle.com/datasets/officialsiddartha/amazon-datasettt/code
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Sep 14, 2024
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    officialsiddartha
    Description

    Dataset

    This dataset was created by officialsiddartha

    Contents

  12. Premium eCommerce Leads | Target Shopify, Amazon, eBay Stores | Verified...

    • datacaptive.com
    Updated May 23, 2022
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    DataCaptive™ (2022). Premium eCommerce Leads | Target Shopify, Amazon, eBay Stores | Verified Owner Contacts | DataCaptive [Dataset]. https://www.datacaptive.com/technology-users-email-list/ecommerce-company-data/
    Explore at:
    Dataset updated
    May 23, 2022
    Dataset provided by
    DataCaptive
    Authors
    DataCaptive™
    Area covered
    Mexico, United Arab Emirates, Bahrain, Norway, Belgium, Romania, Spain, Netherlands, Switzerland, Germany
    Description

    Discover the unparalleled potential of our comprehensive eCommerce leads database, featuring essential data fields such as Store Name, Website, Contact First Name, Contact Last Name, Email Address, Physical Address, City, State, Country, Zip Code, Phone Number, Revenue Size, Employee Size, and more on demand.

    With a focus on Shopify, Amazon, eBay, and other global retail stores, this database equips you with accurate information for successful marketing campaigns. Supercharge your marketing efforts with our enriched contact and company database, providing real-time, verified data insights for strategic market assessments and effective buyer engagement across digital and traditional channels.

    • 4M+ eCommerce Companies • 40M+ Worldwide eCommerce Leads • Direct Contact Info for Shop Owners • 47+ eCommerce Platforms • 40+ Data Points • Lifetime Access • 10+ Data Segmentations • Sample Data"

  13. u

    Steam Video Game and Bundle Data

    • cseweb.ucsd.edu
    json
    + more versions
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    UCSD CSE Research Project, Steam Video Game and Bundle Data [Dataset]. https://cseweb.ucsd.edu/~jmcauley/datasets.html
    Explore at:
    jsonAvailable download formats
    Dataset authored and provided by
    UCSD CSE Research Project
    Description

    These datasets contain reviews from the Steam video game platform, and information about which games were bundled together.

    Metadata includes

    • reviews

    • purchases, plays, recommends (likes)

    • product bundles

    • pricing information

    Basic Statistics:

    • Reviews: 7,793,069

    • Users: 2,567,538

    • Items: 15,474

    • Bundles: 615

  14. 70,000 Active buyer email list from Amazon & ebay for #Email_marketing

    • dataandsons.com
    csv, zip
    Updated Dec 12, 2020
    + more versions
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    boobxff.blogspot.com (2020). 70,000 Active buyer email list from Amazon & ebay for #Email_marketing [Dataset]. https://www.dataandsons.com/categories/markets/70-000-active-buyer-email-list-from-amazon-and-ebay-for-email-marketing
    Explore at:
    zip, csvAvailable download formats
    Dataset updated
    Dec 12, 2020
    Dataset provided by
    Authors
    boobxff.blogspot.com
    License

    Attribution-ShareAlike 4.0 (CC BY-SA 4.0)https://creativecommons.org/licenses/by-sa/4.0/
    License information was derived automatically

    Description

    About this Dataset

    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

    Category

    Markets

    Keywords

    market,emails,email ma,list,buyer

    Row Count

    70150

    Price

    $90.00

  15. amazon best selling

    • kaggle.com
    Updated Apr 8, 2022
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    Raneem Oqaily (2022). amazon best selling [Dataset]. https://www.kaggle.com/raneemoqaily/amazon-best-selling/discussion
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Apr 8, 2022
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Raneem Oqaily
    Description

    Dataset

    This dataset was created by Raneem Oqaily

    Contents

  16. B

    B2C E-commerce Market Report

    • archivemarketresearch.com
    doc, pdf, ppt
    Updated Mar 31, 2025
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    Archive Market Research (2025). B2C E-commerce Market Report [Dataset]. https://www.archivemarketresearch.com/reports/b2c-e-commerce-market-4843
    Explore at:
    doc, pdf, pptAvailable download formats
    Dataset updated
    Mar 31, 2025
    Dataset authored and provided by
    Archive Market Research
    License

    https://www.archivemarketresearch.com/privacy-policyhttps://www.archivemarketresearch.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    global
    Variables measured
    Market Size
    Description

    The B2C E-commerce Market size was valued at USD 6.23 trillion in 2023 and is projected to reach USD 21.18 trillion by 2032, exhibiting a CAGR of 19.1 % during the forecasts period. The B2C e-commerce can be defined as the sale of commercial products or services through the internet between buyers and sellers. This market pertains to several industries that fall under its fold that includes the area of retail, travelling, electronics and digital products. Some of the most common implementations are in the ecommerce sites, mobile applications, and membership services. Some aspects of the B2C e-commerce market include increased popularity of omnichannel retailing that combines online and offline environments and the shift to the concept of individualization due to the digitalization and data processing using artificial intelligence and machine learning. Also, growth is noted in mobile commerce (m-commerce) as a result of the increase in the number of mobile devices and more effective mobile payments. To this list one should also include the concepts of social commerce and sustainability which also became significant in today’s society due to increasing importance of ethical and convenient shopping. Recent developments include: In March 2024, Blink, an Amazon company, launched the Blink Mini 2 camera. The new compact plug-in camera offers enhanced features such as person detection, a broader field of view, a built-in LED spotlight for night view in color, and improved image quality. The Blink Mini 2 is designed to work indoors and outdoors, with the option to purchase the Blink Weather Resistant Power Adapter for outdoor use. , In October 2023, Flipkart.com introduced the 'Flipkart Commerce Cloud,' a customized suite of AI-driven retail technology solutions for global retailers and e-commerce businesses. This extensive offering includes marketplace technology, retail media solutions, pricing, and inventory management features rigorously assessed by Flipkart.com. The company aims to equip international sellers with reliable and secure tools to enhance business expansion and efficiency within the competitive global market. , In August 2023, Shopify and Amazon.com, Inc. announced a strategic partnership that will allow Shopify merchants to seamlessly implement Amazon's "Buy with Prime" option on their sites. As a result of the agreement, Amazon.com, Inc. Prime customers will enjoy a more efficient checkout process on various platforms. This collaboration allows Amazon Prime members to utilize their existing Amazon payment options, while Shopify will handle the transaction processing through its system, showcasing a partnership between the two leading companies. , In February 2023, eBay acquired 3PM Shield, a developer of AI-powered online retail solutions. 3PM Shield uses machine learning and artificial intelligence to analyze extensive data sets, enhancing marketplace compliance and user experience. This acquisition aligns with eBay's goal to offer a "safe and reliable" platform by boosting its ability to block the sale of counterfeit and prohibited items. By incorporating 3PM Shield's sophisticated monitoring technologies, eBay seeks to enhance its capability to address problematic seller behavior and spot problematic listings, fostering a safer e-commerce space for its worldwide community of sellers and buyers. .

  17. Amazon revenue 2004-2024

    • statista.com
    Updated Jun 25, 2025
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    Statista (2025). Amazon revenue 2004-2024 [Dataset]. https://www.statista.com/statistics/266282/annual-net-revenue-of-amazoncom/
    Explore at:
    Dataset updated
    Jun 25, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States, Worldwide
    Description

    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.

  18. u

    Product Exchange/Bartering Data

    • cseweb.ucsd.edu
    json
    + more versions
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    UCSD CSE Research Project, Product Exchange/Bartering Data [Dataset]. https://cseweb.ucsd.edu/~jmcauley/datasets.html
    Explore at:
    jsonAvailable download formats
    Dataset authored and provided by
    UCSD CSE Research Project
    Description

    These datasets contain peer-to-peer trades from various recommendation platforms.

    Metadata includes

    • peer-to-peer trades

    • have and want lists

    • image data (tradesy)

  19. Online Retail Market in the US by Product and Device - Forecast and Analysis...

    • technavio.com
    Updated Mar 3, 2022
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    Technavio (2022). Online Retail Market in the US by Product and Device - Forecast and Analysis 2022-2026 [Dataset]. https://www.technavio.com/report/online-retail-market-industry-in-the-us-analysis
    Explore at:
    Dataset updated
    Mar 3, 2022
    Dataset provided by
    TechNavio
    Authors
    Technavio
    Time period covered
    2021 - 2026
    Area covered
    United States
    Description

    Snapshot img

    The online retail market share in the US is expected to increase to USD 460.13 billion from 2021 to 2026, and the market’s growth momentum will accelerate at a CAGR of 11.64%.

    The report extensively covers online retail market in the US segmentation by the following:

    Product - Apparel, footwear, and accessories, consumer electronics and electricals, food and grocery, home furniture and furnishing, and others
    Device - Smartphones and tablets and PCs
    

    The US online retail market report offers information on several market vendors, including Amazon.com Inc., Apple Inc., Best Buy Co. Inc., Costco Wholesale Corp., eBay Inc., Kroger Co., Target Corp., The Home Depot Inc., Walmart Inc., and Wayfair Inc. among others.

    This online retail market in the US research report provides valuable insights on the post COVID-19 impact on the market, which will help companies evaluate their business approaches.

    What will the Online Retail Market Size in the US be During the Forecast Period?

    Download the Free Report Sample to Unlock the Online Retail Market Size in the US for the Forecast Period and Other Important Statistics

    Online Retail Market in the US: Key Drivers, Trends, and Challenges

    The growing seasonal and holiday sales is notably driving the online retail market growth in the US, although factors such as transportation and logistics may impede the market growth. Our research analysts have studied the historical data and deduced the key market drivers and the COVID-19 pandemic impact on the online retail industry in the US. The holistic analysis of the drivers will help in deducing end goals and refining marketing strategies to gain a competitive edge.

    Key US Online Retail Market Driver

    The growing seasonal and holiday sales is one of the key drivers supporting the US online retail market growth. For instance, from November 1 to December 24, e-commerce sales in the US increased by 11% in 2021, when compared to a massive 47.2% growth in the holiday season of 2020. E-commerce sales made up 20.9 % of total retail sales in the holiday season of 2021, slightly higher than 20.6 percent in 2020. Thanksgiving, Black Friday, and Cyber Monday are the days that see a high amount of online shopping. Apparel, footwear and accessories, consumer electronics, computer hardware, and toys are the largest gaining product categories during the holiday season. Consumers in the US spent $204.5 billion online in November and December 2021, up 8.6% over the same period in 2020. Such exciting sales and offers are driving the market growth.

    Key US Online Retail Market Trend

    Omni-channel retailing is one of the key US online retail market trends fueling the market growth. It is rapidly becoming the norm for many retailers in the US. It offers consumers the option to shop online and pick up the merchandise from the store nearest to their location on the same day. Retailers are observing a high web influence on their in-store sales. For instance, Best Buy is integrating its offline and online stores to boost revenues. As a part of its omnichannel strategy, the retailer is utilizing physical stores as distribution centers for online purchases. According to Best Buy, 40% of its online shoppers prefer picking up their purchases from physical stores. Best Buy also challenges online and discount retailers with its match-to-price strategy, claiming to offer gadgets at or below the price offered by competitors. Such strategies are expected to boost market growth during the forecast period.

    Key US Online Retail Market Challenge

    Transportation and logistics are some of the factors hindering the US online retail market growth. Product procurement or sourcing, shipment of ordered items, and delivery to customers are the three major processes where the intervention of transportation and logistics come into the picture. All these processes require a high investment of both time and money, which challenges the efficiency and effectiveness of retailers and their costing strategies. The higher cost incurred from transportation and logistics reduces the margin of retailers, and most of the time, retailers are unable to break even. Between rising fuel prices, driver shortages, as well as a governmental and societal push for increased digitization and sustainability, transport and logistics will continue to be under a lot of pressure. Such factors will negatively impact the market growth during the forecast period.

    This online retail market in the US analysis report also provides detailed information on other upcoming trends and challenges that will have a far-reaching effect on the market growth. The actionable insights on the trends and challenges will help companies evaluate and develop growth strategies for 2022-2026.

    Who are the Major Online Retail Market Vendors in the US?

    The report analyzes the market’s competitive landscape and offers information on sever

  20. Total global visitor traffic to amazon.com 2024

    • statista.com
    Updated Feb 18, 2025
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    Statista (2025). Total global visitor traffic to amazon.com 2024 [Dataset]. https://www.statista.com/statistics/623566/web-visits-to-amazoncom/
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    Dataset updated
    Feb 18, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Oct 2023 - Mar 2024
    Area covered
    Worldwide
    Description

    In March 2024, Amazon.com had approximately 2.2 billion combined web visits, up from 2.1 billion visits in February. In the fourth quarter of 2024, Amazon’s net income amounted to approximately 20 billion U.S. dollars. Online retail in the United States Online retail in the United States is constantly growing. In the third quarter of 2023, e-commerce sales accounted for 15.6 percent of retail sales in the United States. During that quarter, U.S. retail e-commerce sales amounted to over 284 billion U.S. dollars. Amazon is the leading online store in the country, in terms of e-commerce net sales. Amazon.com generated around 130 billion U.S. dollars in online sales in 2022. Walmart ranked as the second-biggest online store, with revenues of 52 billion U.S. dollars. The king of Black Friday In 2023, Amazon ranked as U.S. shoppers' favorite place to go shopping during Black Friday, even surpassing in-store purchasing. Nearly six out of ten consumers chose Amazon as the number one place to go find the best Black Friday deals. Similar findings can be observed in the United Kingdom (UK), where Amazon is also ranked as the preferred Black Friday destination.

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Business of Apps (2025). Amazon Statistics (2025) [Dataset]. https://www.businessofapps.com/data/amazon-statistics/

Amazon Statistics (2025)

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11 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Jul 20, 2025
Dataset authored and provided by
Business of Apps
License

Attribution-NonCommercial-NoDerivs 4.0 (CC BY-NC-ND 4.0)https://creativecommons.org/licenses/by-nc-nd/4.0/
License information was derived automatically

Description

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,...

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