100+ datasets found
  1. G

    Retail e-commerce sales, inactive

    • open.canada.ca
    • ouvert.canada.ca
    • +1more
    csv, html, xml
    Updated Mar 24, 2023
    + more versions
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    Statistics Canada (2023). Retail e-commerce sales, inactive [Dataset]. https://open.canada.ca/data/en/dataset/0ffbe1ee-7fa7-4369-ac78-a01c8175e1a6
    Explore at:
    html, csv, xmlAvailable download formats
    Dataset updated
    Mar 24, 2023
    Dataset provided by
    Statistics Canada
    License

    Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
    License information was derived automatically

    Description

    This table contains 3 series, with data for years 2016 - 2017 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: Canada); Sales (3 items: Retail trade; Electronic shopping and mail-order houses; Retail E-commerce sales).

  2. u

    E-commerce Industry Statistics 2025

    • upmetrics.co
    webpage
    Updated Oct 25, 2023
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    Upmetrics (2023). E-commerce Industry Statistics 2025 [Dataset]. https://upmetrics.co/blog/ecommerce-statistics
    Explore at:
    webpageAvailable download formats
    Dataset updated
    Oct 25, 2023
    Dataset provided by
    UpMetrics
    Authors
    Upmetrics
    License

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

    Time period covered
    2023
    Description

    A comprehensive dataset providing key insights into the eCommerce industry, including global retail online sales projections, number of eCommerce stores, digital buyer statistics, revenue growth in the United States, sector-wise revenue details with a focus on consumer electronics, average conversion rates, and mobile commerce sales forecasts.

  3. F

    E-Commerce Retail Sales as a Percent of Total Sales

    • fred.stlouisfed.org
    json
    Updated May 19, 2025
    + more versions
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    (2025). E-Commerce Retail Sales as a Percent of Total Sales [Dataset]. https://fred.stlouisfed.org/series/ECOMPCTSA
    Explore at:
    jsonAvailable download formats
    Dataset updated
    May 19, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Description

    Graph and download economic data for E-Commerce Retail Sales as a Percent of Total Sales (ECOMPCTSA) from Q4 1999 to Q1 2025 about e-commerce, retail trade, percent, sales, retail, and USA.

  4. Australia Online Retail Sales

    • ceicdata.com
    Updated Nov 23, 2024
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    CEICdata.com (2024). Australia Online Retail Sales [Dataset]. https://www.ceicdata.com/en/australia/online-retail-sales/online-retail-sales
    Explore at:
    Dataset updated
    Nov 23, 2024
    Dataset provided by
    CEIC Data
    License

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

    Time period covered
    Feb 1, 2024 - Jan 1, 2025
    Area covered
    Australia
    Variables measured
    Domestic Trade
    Description

    Australia Online Retail Sales data was reported at 4,207.200 AUD mn in Mar 2025. This records an increase from the previous number of 3,758.800 AUD mn for Feb 2025. Australia Online Retail Sales data is updated monthly, averaging 1,659.100 AUD mn from Mar 2013 (Median) to Mar 2025, with 145 observations. The data reached an all-time high of 5,349.400 AUD mn in Dec 2024 and a record low of 417.400 AUD mn in Mar 2013. Australia Online Retail Sales data remains active status in CEIC and is reported by Australian Bureau of Statistics. The data is categorized under Global Database’s Australia – Table AU.H020: Online Retail Sales. [COVID-19-IMPACT]

  5. Retail Sales Index internet sales

    • ons.gov.uk
    • cy.ons.gov.uk
    xlsx
    Updated Jun 20, 2025
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    Office for National Statistics (2025). Retail Sales Index internet sales [Dataset]. https://www.ons.gov.uk/businessindustryandtrade/retailindustry/datasets/retailsalesindexinternetsales
    Explore at:
    xlsxAvailable download formats
    Dataset updated
    Jun 20, 2025
    Dataset provided by
    Office for National Statisticshttp://www.ons.gov.uk/
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Description

    Internet sales in Great Britain by store type, month and year.

  6. d

    Warehouse and Retail Sales

    • catalog.data.gov
    • data.montgomerycountymd.gov
    • +4more
    Updated Jul 5, 2025
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    data.montgomerycountymd.gov (2025). Warehouse and Retail Sales [Dataset]. https://catalog.data.gov/dataset/warehouse-and-retail-sales
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    Dataset updated
    Jul 5, 2025
    Dataset provided by
    data.montgomerycountymd.gov
    Description

    This dataset contains a list of sales and movement data by item and department appended monthly. Update Frequency : Monthly

  7. T

    US Retail Sales

    • tradingeconomics.com
    • zh.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Jun 17, 2025
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    TRADING ECONOMICS (2025). US Retail Sales [Dataset]. https://tradingeconomics.com/united-states/retail-sales
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    csv, xml, excel, jsonAvailable download formats
    Dataset updated
    Jun 17, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Feb 29, 1992 - May 31, 2025
    Area covered
    United States
    Description

    Retail Sales in the United States decreased 0.90 percent in May of 2025 over the previous month. This dataset provides - U.S. December Retail Sales Increased More Than Forecast - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  8. Global retail e-commerce sales 2022-2028

    • statista.com
    • aconto.anazko.com
    Updated Jun 24, 2025
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    Statista (2025). Global retail e-commerce sales 2022-2028 [Dataset]. https://www.statista.com/statistics/379046/worldwide-retail-e-commerce-sales/
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    Dataset updated
    Jun 24, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Feb 2025
    Area covered
    Worldwide
    Description

    In 2024, global retail e-commerce sales reached an estimated ************ U.S. dollars. Projections indicate a ** percent growth in this figure over the coming years, with expectations to come close to ************** dollars by 2028. World players Among the key players on the world stage, the American marketplace giant Amazon holds the title of the largest e-commerce player globally, with a gross merchandise value of nearly *********** U.S. dollars in 2024. Amazon was also the most valuable retail brand globally, followed by mostly American competitors such as Walmart and the Home Depot. Leading e-tailing regions E-commerce is a dormant channel globally, but nowhere has it been as successful as in Asia. In 2024, the e-commerce revenue in that continent alone was measured at nearly ************ U.S. dollars, outperforming the Americas and Europe. That year, the up-and-coming e-commerce markets also centered around Asia. The Philippines and India stood out as the swiftest-growing e-commerce markets based on online sales, anticipating a growth rate surpassing ** percent.

  9. sales data

    • kaggle.com
    Updated Aug 2, 2023
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    Ronny Kimathi kaimenyi (2023). sales data [Dataset]. https://www.kaggle.com/datasets/ronnykym/online-store-sales-data
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Aug 2, 2023
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Ronny Kimathi kaimenyi
    License

    https://ec.europa.eu/info/legal-notice_enhttps://ec.europa.eu/info/legal-notice_en

    Description

    Deluxe is an online retailer based in UK that deals in a wide range of products in the following categories: 1. Clothing 2. Games 3. Appliances 4. Electronics 5. Books 6. Beauty products 7. Smartphones 8. Outdoors products 9. Accessories 10. Other Basic household products are classified as 'Other' in the category column since they have small value to the business.

    Data Description: dates: sale date order_value_EUR : sale price in EUR cost: cost of goods sold in EUR category: item category country: customers' country at the time of purchase customer_name: name of customer device_type: The gadget used by customer to access our online store(PC, mobile, tablet) sales_manager: name of the sales manager for each sale sales_representative: name of the sales rep for each sale order_id: unique identifier of an order

    The data was recorded for the period 1/2/2019 and 12/30/2020 with an aim to generate business insights to guide business direction. We would like to see what interesting insights the Kaggle community members can produce from this data.

  10. China Online Retail Sales: YoY: ytd: Goods and Service

    • ceicdata.com
    Updated Feb 15, 2025
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    CEICdata.com (2025). China Online Retail Sales: YoY: ytd: Goods and Service [Dataset]. https://www.ceicdata.com/en/china/online-retail-sales/online-retail-sales-yoy-ytd-goods-and-service
    Explore at:
    Dataset updated
    Feb 15, 2025
    Dataset provided by
    CEIC Data
    License

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

    Time period covered
    Dec 1, 2023 - Dec 1, 2024
    Area covered
    China
    Variables measured
    Domestic Trade
    Description

    China Online Retail Sales: YoY: Year to Date: Goods and Service data was reported at 7.900 % in Mar 2025. This records an increase from the previous number of 7.300 % for Feb 2025. China Online Retail Sales: YoY: Year to Date: Goods and Service data is updated monthly, averaging 17.100 % from Feb 2015 (Median) to Mar 2025, with 112 observations. The data reached an all-time high of 44.600 % in Feb 2015 and a record low of -3.000 % in Feb 2020. China Online Retail Sales: YoY: Year to Date: Goods and Service data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Consumer Goods and Services – Table CN.HA: Online Retail Sales.

  11. Linear Regression E-commerce Dataset

    • kaggle.com
    zip
    Updated Sep 16, 2019
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    Saurabh Kolawale (2019). Linear Regression E-commerce Dataset [Dataset]. https://www.kaggle.com/datasets/kolawale/focusing-on-mobile-app-or-website
    Explore at:
    zip(44169 bytes)Available download formats
    Dataset updated
    Sep 16, 2019
    Authors
    Saurabh Kolawale
    Description

    This dataset is having data of customers who buys clothes online. The store offers in-store style and clothing advice sessions. Customers come in to the store, have sessions/meetings with a personal stylist, then they can go home and order either on a mobile app or website for the clothes they want.

    The company is trying to decide whether to focus their efforts on their mobile app experience or their website.

  12. C

    China Online Retail Sales: YoY: ytd: Goods

    • ceicdata.com
    Updated Feb 5, 2025
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    CEICdata.com (2025). China Online Retail Sales: YoY: ytd: Goods [Dataset]. https://www.ceicdata.com/en/china/online-retail-sales/online-retail-sales-yoy-ytd-goods
    Explore at:
    Dataset updated
    Feb 5, 2025
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Dec 1, 2023 - Dec 1, 2024
    Area covered
    China
    Variables measured
    Domestic Trade
    Description

    China Online Retail Sales: YoY: Year to Date: Goods data was reported at 5.700 % in Mar 2025. This records an increase from the previous number of 5.000 % for Feb 2025. China Online Retail Sales: YoY: Year to Date: Goods data is updated monthly, averaging 19.900 % from Jun 2014 (Median) to Mar 2025, with 115 observations. The data reached an all-time high of 49.900 % in Sep 2014 and a record low of 3.000 % in Feb 2020. China Online Retail Sales: YoY: Year to Date: Goods data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Consumer Goods and Services – Table CN.HA: Online Retail Sales.

  13. Envestnet | Yodlee's De-Identified Retail Sales Data | Row/Aggregate Level |...

    • datarade.ai
    .sql, .txt
    + more versions
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    Envestnet | Yodlee, Envestnet | Yodlee's De-Identified Retail Sales Data | Row/Aggregate Level | USA Consumer Data covering 3600+ corporations | 90M+ Accounts [Dataset]. https://datarade.ai/data-products/envestnet-yodlee-s-de-identified-retail-sales-data-row-ag-envestnet-yodlee
    Explore at:
    .sql, .txtAvailable download formats
    Dataset provided by
    Yodlee
    Envestnethttp://envestnet.com/
    Authors
    Envestnet | Yodlee
    Area covered
    United States of America
    Description

    Envestnet®| Yodlee®'s Retail Sales Data (Aggregate/Row) Panels consist of de-identified, near-real time (T+1) USA credit/debit/ACH transaction level data – offering a wide view of the consumer activity ecosystem. The underlying data is sourced from end users leveraging the aggregation portion of the Envestnet®| Yodlee®'s financial technology platform.

    Envestnet | Yodlee Consumer Panels (Aggregate/Row) include data relating to millions of transactions, including ticket size and merchant location. The dataset includes de-identified credit/debit card and bank transactions (such as a payroll deposit, account transfer, or mortgage payment). Our coverage offers insights into areas such as consumer, TMT, energy, REITs, internet, utilities, ecommerce, MBS, CMBS, equities, credit, commodities, FX, and corporate activity. We apply rigorous data science practices to deliver key KPIs daily that are focused, relevant, and ready to put into production.

    We offer free trials. Our team is available to provide support for loading, validation, sample scripts, or other services you may need to generate insights from our data.

    Investors, corporate researchers, and corporates can use our data to answer some key business questions such as: - How much are consumers spending with specific merchants/brands and how is that changing over time? - Is the share of consumer spend at a specific merchant increasing or decreasing? - How are consumers reacting to new products or services launched by merchants? - For loyal customers, how is the share of spend changing over time? - What is the company’s market share in a region for similar customers? - Is the company’s loyal user base increasing or decreasing? - Is the lifetime customer value increasing or decreasing?

    Additional Use Cases: - Use spending data to analyze sales/revenue broadly (sector-wide) or granular (company-specific). Historically, our tracked consumer spend has correlated above 85% with company-reported data from thousands of firms. Users can sort and filter by many metrics and KPIs, such as sales and transaction growth rates and online or offline transactions, as well as view customer behavior within a geographic market at a state or city level. - Reveal cohort consumer behavior to decipher long-term behavioral consumer spending shifts. Measure market share, wallet share, loyalty, consumer lifetime value, retention, demographics, and more.) - Study the effects of inflation rates via such metrics as increased total spend, ticket size, and number of transactions. - Seek out alpha-generating signals or manage your business strategically with essential, aggregated transaction and spending data analytics.

    Use Cases Categories (Our data provides an innumerable amount of use cases, and we look forward to working with new ones): 1. Market Research: Company Analysis, Company Valuation, Competitive Intelligence, Competitor Analysis, Competitor Analytics, Competitor Insights, Customer Data Enrichment, Customer Data Insights, Customer Data Intelligence, Demand Forecasting, Ecommerce Intelligence, Employee Pay Strategy, Employment Analytics, Job Income Analysis, Job Market Pricing, Marketing, Marketing Data Enrichment, Marketing Intelligence, Marketing Strategy, Payment History Analytics, Price Analysis, Pricing Analytics, Retail, Retail Analytics, Retail Intelligence, Retail POS Data Analysis, and Salary Benchmarking

    1. Investment Research: Financial Services, Hedge Funds, Investing, Mergers & Acquisitions (M&A), Stock Picking, Venture Capital (VC)

    2. Consumer Analysis: Consumer Data Enrichment, Consumer Intelligence

    3. Market Data: AnalyticsB2C Data Enrichment, Bank Data Enrichment, Behavioral Analytics, Benchmarking, Customer Insights, Customer Intelligence, Data Enhancement, Data Enrichment, Data Intelligence, Data Modeling, Ecommerce Analysis, Ecommerce Data Enrichment, Economic Analysis, Financial Data Enrichment, Financial Intelligence, Local Economic Forecasting, Location-based Analytics, Market Analysis, Market Analytics, Market Intelligence, Market Potential Analysis, Market Research, Market Share Analysis, Sales, Sales Data Enrichment, Sales Enablement, Sales Insights, Sales Intelligence, Spending Analytics, Stock Market Predictions, and Trend Analysis

  14. Retail ecommerce sales in India 2019-2025

    • statista.com
    Updated Jun 23, 2025
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    Statista (2025). Retail ecommerce sales in India 2019-2025 [Dataset]. https://www.statista.com/statistics/255359/online-retail-sales-in-india/
    Explore at:
    Dataset updated
    Jun 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    India
    Description

    Online shopping sales across India amounted to around ** billion U.S. dollars in 2021. The e-commerce market is likely to grow to over *** billion U.S. dollars by 2025. The e-commerce market in India is the fastest-growing market in the world. Online retail segments In fiscal year 2017, the retail market was led by electronics with a penetration rate of about ** percent. However, in terms of groceries, local offline vendors or kiranas continued to be the preferred choice for daily groceries due the ease of bargaining and benefitting from the ‘old-customer’ designation with extra rations as a gesture from the vendor. Nevertheless, the number of online shoppers in the country was estimated to increase to over *** million in 2025, up from around ** million in 2017. Impact of COVID-19 on the marketThe coronavirus outbreak in March 2020 caused a surge in prices across e-commerce platforms. Panic purchasing resulted in the shortage of sanitary and food items online as well as in physical stores across the country. As the online consumption continued to increase, unscrupulous sellers jacked up the prices on certain items. Amazon and Flipkart, the two e-commerce market leaders in India urged sellers and even blocked certain products to exercise responsible pricing. Manufacturers increased production in order to keep up with the supply of fast-moving items. With the uncertainty surrounding the impact of COVID-19, manufacturers and retailers will presumably have to work in unison to keep track of an unprecedented demand and supply scenario.

  15. Retail trade, total sales and e-commerce sales, inactive

    • www150.statcan.gc.ca
    • open.canada.ca
    • +2more
    Updated Feb 20, 2023
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    Government of Canada, Statistics Canada (2023). Retail trade, total sales and e-commerce sales, inactive [Dataset]. http://doi.org/10.25318/2010006501-eng
    Explore at:
    Dataset updated
    Feb 20, 2023
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    Area covered
    Canada
    Description

    E-commerce sales and total sales for retail trade in Canada, available on an annual basis.

  16. Retail Store Data | Retail & E-commerce Sector in Asia | Verified Business...

    • datarade.ai
    Updated Feb 12, 2018
    + more versions
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    Success.ai (2018). Retail Store Data | Retail & E-commerce Sector in Asia | Verified Business Profiles & eCommerce Professionals | Best Price Guaranteed [Dataset]. https://datarade.ai/data-products/retail-store-data-retail-e-commerce-sector-in-asia-veri-success-ai
    Explore at:
    .bin, .json, .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset updated
    Feb 12, 2018
    Dataset provided by
    Area covered
    Singapore, Lebanon, Malaysia, Kuwait, Georgia, Turkmenistan, Cyprus, Bangladesh, Hong Kong, Jordan
    Description

    Success.ai delivers unparalleled access to Retail Store Data for Asia’s retail and e-commerce sectors, encompassing subcategories such as ecommerce data, ecommerce merchant data, ecommerce market data, and company data. Whether you’re targeting emerging markets or established players, our solutions provide the tools to connect with decision-makers, analyze market trends, and drive strategic growth. With continuously updated datasets and AI-validated accuracy, Success.ai ensures your data is always relevant and reliable.

    Key Features of Success.ai's Retail Store Data for Retail & E-commerce in Asia:

    Extensive Business Profiles: Access detailed profiles for 70M+ companies across Asia’s retail and e-commerce sectors. Profiles include firmographic data, revenue insights, employee counts, and operational scope.

    Ecommerce Data: Gain insights into online marketplaces, customer demographics, and digital transaction patterns to refine your strategies.

    Ecommerce Merchant Data: Understand vendor performance, supply chain metrics, and operational details to optimize partnerships.

    Ecommerce Market Data: Analyze purchasing trends, regional preferences, and market demands to identify growth opportunities.

    Contact Data for Decision-Makers: Reach key stakeholders, such as CEOs, marketing executives, and procurement managers. Verified contact details include work emails, phone numbers, and business addresses.

    Real-Time Accuracy: AI-powered validation ensures a 99% accuracy rate, keeping your outreach efforts efficient and impactful.

    Compliance and Ethics: All data is ethically sourced and fully compliant with GDPR and other regional data protection regulations.

    Why Choose Success.ai for Retail Store Data?

    Best Price Guarantee: We deliver industry-leading value with the most competitive pricing for comprehensive retail store data.

    Customizable Solutions: Tailor your data to meet specific needs, such as targeting particular regions, industries, or company sizes.

    Scalable Access: Our data solutions are built to grow with your business, supporting small startups to large-scale enterprises.

    Seamless Integration: Effortlessly incorporate our data into your existing CRM, marketing, or analytics platforms.

    Comprehensive Use Cases for Retail Store Data:

    1. Market Entry and Expansion:

    Identify potential partners, distributors, and clients to expand your footprint in Asia’s dynamic retail and e-commerce markets. Use detailed profiles to assess market opportunities and risks.

    1. Personalized Marketing Campaigns:

    Leverage ecommerce data and consumer insights to craft highly targeted campaigns. Connect directly with decision-makers for precise and effective communication.

    1. Competitive Benchmarking:

    Analyze competitors’ operations, market positioning, and consumer strategies to refine your business plans and gain a competitive edge.

    1. Supplier and Vendor Selection:

    Evaluate potential suppliers or vendors using ecommerce merchant data, including financial health, operational details, and contact data.

    1. Customer Engagement and Retention:

    Enhance customer loyalty programs and retention strategies by leveraging ecommerce market data and purchasing trends.

    APIs to Amplify Your Results:

    Enrichment API: Keep your CRM and analytics platforms up-to-date with real-time data enrichment, ensuring accurate and actionable company profiles.

    Lead Generation API: Maximize your outreach with verified contact data for retail and e-commerce decision-makers. Ideal for driving targeted marketing and sales efforts.

    Tailored Solutions for Industry Professionals:

    Retailers: Expand your supply chain, identify new markets, and connect with key partners in the e-commerce ecosystem.

    E-commerce Platforms: Optimize your vendor and partner selection with verified profiles and operational insights.

    Marketing Agencies: Deliver highly personalized campaigns by leveraging detailed consumer data and decision-maker contacts.

    Consultants: Provide data-driven recommendations to clients with access to comprehensive company data and market trends.

    What Sets Success.ai Apart?

    70M+ Business Profiles: Access an extensive and detailed database of companies across Asia’s retail and e-commerce sectors.

    Global Compliance: All data is sourced ethically and adheres to international data privacy standards, including GDPR.

    Real-Time Updates: Ensure your data remains accurate and relevant with our continuously updated datasets.

    Dedicated Support: Our team of experts is available to help you maximize the value of our data solutions.

    Empower Your Business with Success.ai:

    Success.ai’s Retail Store Data for the retail and e-commerce sectors in Asia provides the insights and connections needed to thrive in this competitive market. Whether you’re entering a new region, launching a targeted campaign, or analyzing market trends, our data solutions ensure measurable success.

    ...

  17. Online Retail Sales Proportion (Out Of The Respective Industry's Total...

    • data.gov.sg
    Updated Jul 5, 2025
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    Singapore Department of Statistics (2025). Online Retail Sales Proportion (Out Of The Respective Industry's Total Sales), Monthly [Dataset]. https://data.gov.sg/datasets/d_65e4d47c3616d251f9a84ec1ad28f43c/view
    Explore at:
    Dataset updated
    Jul 5, 2025
    Dataset authored and provided by
    Singapore Department of Statistics
    License

    https://data.gov.sg/open-data-licencehttps://data.gov.sg/open-data-licence

    Time period covered
    Jan 2018 - May 2025
    Description

    Dataset from Singapore Department of Statistics. For more information, visit https://data.gov.sg/datasets/d_65e4d47c3616d251f9a84ec1ad28f43c/view

  18. E-commerce as share of total retail sales in the U.S. 2019-2027

    • statista.com
    • ai-chatbox.pro
    Updated Mar 10, 2025
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    Statista Research Department (2025). E-commerce as share of total retail sales in the U.S. 2019-2027 [Dataset]. https://www.statista.com/topics/2477/online-shopping-behavior/
    Explore at:
    Dataset updated
    Mar 10, 2025
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Statista Research Department
    Description

    In 2023, e-commerce comprised over 15.6 percent of total retail sales in the United States. Forecasts suggest that this proportion will continue to rise steadily in the coming years, reaching approximately 20.6 percent by 2027. Fashion fever The digital revolution has significantly changed how retail is done, impacting a wide range of product categories. Out of all e-commerce product categories, apparel and accessories are the most purchased online in the United States. As of February 2023, roughly 18 percent of all fashion retail sales took place online. Furniture and home furnishing, as well as computer and consumer electronics, ranked second, with over 15 percent of each product category purchased via the internet. The product categories that are least purchased online are office equipment and supplies (1.4 percent) and books, music, and video (5.1 percent). Shopping hotspots Amazon dominates the e-commerce industry in the United States, though other competitors still have significant market share. In December 2023, amazon.com was the most-visited e-commerce and shopping site in the United States. That month, around 45 percent of all visits to e-commerce sites were made to Amazon. Other popular shopping sites include ebay.com, walmart.com, etsy.com, and target.com. The staggering proportion of online retail sales in the country attributed to Amazon is quite remarkable. In 2023, Amazon's website accounted for almost half of all online computer and consumer electronics sales. Similarly, nearly one-third of online fashion purchases in the country were made on Amazon.

  19. C

    China Online Retail Sales: ytd: Goods

    • ceicdata.com
    Updated Feb 15, 2025
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    CEICdata.com (2025). China Online Retail Sales: ytd: Goods [Dataset]. https://www.ceicdata.com/en/china/online-retail-sales/online-retail-sales-ytd-goods
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    Dataset updated
    Feb 15, 2025
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Feb 1, 2024 - Feb 1, 2025
    Area covered
    China
    Variables measured
    Domestic Trade
    Description

    China Online Retail Sales: Year to Date: Goods data was reported at 2,994.820 RMB bn in Mar 2025. This records an increase from the previous number of 1,863.260 RMB bn for Feb 2025. China Online Retail Sales: Year to Date: Goods data is updated monthly, averaging 3,682.600 RMB bn from Jun 2013 (Median) to Mar 2025, with 117 observations. The data reached an all-time high of 13,081.570 RMB bn in Dec 2024 and a record low of 399.100 RMB bn in Feb 2015. China Online Retail Sales: Year to Date: Goods data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Consumer Goods and Services – Table CN.HA: Online Retail Sales.

  20. d

    Ecommerce Data | Store Location Data | Global Coverage | 61M+ Contacts |...

    • datarade.ai
    Updated Jan 24, 2024
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    Exellius Systems (2024). Ecommerce Data | Store Location Data | Global Coverage | 61M+ Contacts | (Verified E-mail, Direct Dails)| Decision Makers Contacts| 20+ Attributes [Dataset]. https://datarade.ai/data-products/ecommerce-data-ecommerce-store-data-global-coverage-200-exellius-systems
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    .bin, .json, .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset updated
    Jan 24, 2024
    Dataset authored and provided by
    Exellius Systems
    Area covered
    Spain, Namibia, Lithuania, Gabon, Seychelles, Jersey, Heard Island and McDonald Islands, Saint Vincent and the Grenadines, Congo (Democratic Republic of the), Iran (Islamic Republic of)
    Description

    Revolutionize Customer Engagement with Our Comprehensive Ecommerce Data

    Our Ecommerce Data is designed to elevate your customer engagement strategies, providing you with unparalleled insights and precision targeting capabilities. With over 61 million global contacts, this dataset goes beyond conventional data, offering a unique blend of shopping cart links, business emails, phone numbers, and LinkedIn profiles. This comprehensive approach ensures that your marketing strategies are not just effective but also highly personalized, enabling you to connect with your audience on a deeper level.

    What Makes Our Ecommerce Data Stand Out?

    • Unique Features for Enhanced Targeting
      Our Ecommerce Data is distinguished by its depth and precision. Unlike many other datasets, it includes shopping cart links—a rare and valuable feature that provides you with direct insights into consumer behavior and purchasing intent. This information allows you to tailor your marketing efforts with unprecedented accuracy. Additionally, the integration of business emails, phone numbers, and LinkedIn profiles adds multiple layers to traditional contact data, enriching your understanding of clients and enabling more personalized engagement.

    • Robust and Reliable Data Sourcing
      We pride ourselves on our dual-sourcing strategy that ensures the highest levels of data accuracy and relevance:

      • Real-Time Information from 10 Active Publication Sites: Our databases are continuously updated with the latest information, sourced from ten active publication sites that provide real-time data.
      • Dedicated Contact Discovery Team: Complementing our automated sources, our dedicated Contact Discovery Team conducts thorough research and investigations, ensuring that every piece of data is accurate and reliable. This two-pronged approach guarantees that our Ecommerce Data is both up-to-date and relevant, providing you with a solid foundation for your business strategies.

      Primary Use Cases Across Industries

    Our Ecommerce Data is versatile and can be leveraged across various industries for multiple applications: - Precision Targeting in Marketing: Create personalized marketing campaigns based on detailed shopping cart activities, ensuring that your outreach resonates with individual customer preferences. - Sales Enrichment: Sales teams can benefit from enriched client profiles that include comprehensive contact information, enabling them to connect with key decision-makers more effectively. - Market Research and Analytics: Research and analytics departments can use this data for in-depth market studies and trend analyses, gaining valuable insights into consumer behavior and market dynamics.

    Global Coverage for Comprehensive Engagement

    Our Ecommerce Data spans across the globe, providing you with extensive reach and the ability to engage with customers in diverse regions: - North America: United States, Canada, Mexico - Europe: United Kingdom, Germany, France, Italy, Spain, Netherlands, Sweden, and more - Asia: China, Japan, India, South Korea, Singapore, Malaysia, and more - South America: Brazil, Argentina, Chile, Colombia, and more - Africa: South Africa, Nigeria, Kenya, Egypt, and more - Australia and Oceania: Australia, New Zealand - Middle East: United Arab Emirates, Saudi Arabia, Israel, Qatar, and more

    Comprehensive Employee and Revenue Size Information

    Our dataset also includes detailed information on: - Employee Size: Whether you’re targeting small businesses or large corporations, our data covers all employee sizes, from startups to global enterprises. - Revenue Size: Gain insights into companies across various revenue brackets, enabling you to segment the market more effectively and target your efforts where they will have the most impact.

    Seamless Integration into Broader Data Offerings

    Our Ecommerce Data is not just a standalone product; it is a critical piece of our broader data ecosystem. It seamlessly integrates with our comprehensive suite of business and consumer datasets, offering you a holistic approach to data-driven decision-making: - Tailored Packages: Choose customized data packages that meet your specific business needs, combining Ecommerce Data with other relevant datasets for a complete view of your market. - Holistic Insights: Whether you are looking for industry-specific details or a broader market overview, our integrated data solutions provide you with the insights necessary to stay ahead of the competition and make informed business decisions.

    Elevate Your Business Decisions with Our Ecommerce Data

    In essence, our Ecommerce Data is more than just a collection of contacts—it’s a strategic tool designed to give you a competitive edge in understanding and engaging your target audience. By leveraging the power of this comprehensive dataset, you can elevate your business decisions, enhance customer interactions, and navigate the digital landscape with confi...

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Statistics Canada (2023). Retail e-commerce sales, inactive [Dataset]. https://open.canada.ca/data/en/dataset/0ffbe1ee-7fa7-4369-ac78-a01c8175e1a6

Retail e-commerce sales, inactive

Explore at:
html, csv, xmlAvailable download formats
Dataset updated
Mar 24, 2023
Dataset provided by
Statistics Canada
License

Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
License information was derived automatically

Description

This table contains 3 series, with data for years 2016 - 2017 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: Canada); Sales (3 items: Retail trade; Electronic shopping and mail-order houses; Retail E-commerce sales).

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