17 datasets found
  1. Global online shopper per visit spend 2024, by category

    • statista.com
    Updated Mar 4, 2025
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    Koen van Gelder (2025). Global online shopper per visit spend 2024, by category [Dataset]. https://www.statista.com/topics/871/online-shopping/
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    Dataset updated
    Mar 4, 2025
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Koen van Gelder
    Description

    In the fourth quarter of 2024, online shoppers spent an average of about 2.98 U.S. dollars per visit across all verticals. Electronics is the category in which consumers spent the most money per visit on average, at 3.32 U.S. dollars, followed by luxury apparel at 3.10 dollars. Nickels and dimes Over the past few years, the average order value for e-commerce purchases has increased globally, from around 118 U.S. dollars in September 2022 to around 126 U.S. dollars in the same month of 2023. The average order value also depends heavily on the online traffic source consumers use. In 2023, the value per order value was the highest when navigating directly, averaging around 167 dollars. Direct navigation means searching for a website directly in the browser's address bar, bypassing the use of search engines. Orders placed from social media stores were the lowest in value, with an average of less than 110 dollars. Mobile shopping on the rise Online shoppers have clear preferences when it comes to device type. When comparing gadgets, the average purchase amount has always been the highest for desktops, with an order value of 160 U.S. dollars. This indicates that bigger purchases are made via desktop computers. However, consumers are more likely to complete orders when shopping on mobile devices. Mobile devices were also clearly preferred when browsing retail websites, with around three-fourths of consumers using smartphones instead of desktops or tablets.

  2. Global conversion rates in selected verticals 2024

    • statista.com
    Updated Mar 4, 2025
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    Koen van Gelder (2025). Global conversion rates in selected verticals 2024 [Dataset]. https://www.statista.com/topics/871/online-shopping/
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    Dataset updated
    Mar 4, 2025
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Koen van Gelder
    Description

    Online conversion rates of e-commerce sites were the highest in the food & beverage sector, at 3.1 percent in the fourth quarter of 2024. Beauty & skincare followed, with a three percent conversion rate. For comparison, the average conversion rate of e-commerce sites across all selected sectors stood at just over two percent. How does conversion vary by region and device? The conversion rate, which indicates the proportion of visits to e-commerce websites that result in purchases, varies by country and region. For instance, since at least 2023, e-commerce sites have consistently recorded higher conversion rates among shoppers in Great Britain compared to those in the United States and other global regions. Furthermore, despite the increasing prevalence of mobile shopping worldwide, conversions remain more pronounced on larger screens such as tablets and desktops. Online shopping cart abandonment on the rise Recently, the rate at which consumers abandon their online shopping carts has been gradually rising to more than 70 percent in 2024, showing a higher difficulty for e-commerce sites to convert website traffic into purchases. By the end of that year, food and beverage was one of the product categories with the lowest online cart abandonment rate, confirming the sector’s relatively high conversion rate. In the United States, the primary reason why customers abandoned their shopping carts is that extra costs such as shipping, tax, and service fees were too high at checkout.

  3. Global retail e-commerce sales 2022-2028

    • statista.com
    Updated Apr 22, 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
    Apr 22, 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 six trillion U.S. dollars. Projections indicate a 31 percent growth in this figure over the coming years, with expectations to come close to eight trillion 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 800 billion 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 two trillion 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 20 percent.

  4. U.S. International Trade in Goods and Services

    • catalog.data.gov
    • data.amerigeoss.org
    • +1more
    Updated Jan 1, 1994
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    US Census Bureau, Department of Commerce (1994). U.S. International Trade in Goods and Services [Dataset]. https://catalog.data.gov/es/dataset/u-s-international-trade-in-goods-and-services
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    Dataset updated
    Jan 1, 1994
    Dataset provided by
    United States Department of Commercehttp://www.commerce.gov/
    Area covered
    United States
    Description

    Monthly report that provides national trade data including imports, exports, and balance of payments for goods and services. Statistics are also reported on a year-to-date basis. Data are continuously compiled and processed. Documents are collected as shipments arrive and depart, and are processed on a flow basis. The BEA uses the data to update U.S. balance of payments, gross domestic product, and national accounts. Other federal agencies use them for economic, financial, and trade policy analysis (such as import/export promotion studies and import/export price indexes). Private businesses and trade associations use them for domestic and overseas market analysis, and industry-, product-, and area-based business planning. Major print and electronic news media use them for general and business news reports.

  5. Global online retail website visits and orders 2024, by device

    • statista.com
    Updated Mar 4, 2025
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    Koen van Gelder (2025). Global online retail website visits and orders 2024, by device [Dataset]. https://www.statista.com/topics/871/online-shopping/
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    Dataset updated
    Mar 4, 2025
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Koen van Gelder
    Description

    Mobile phones dominate global digital commerce website visits and contribute to the largest share of online orders. As of the fourth quarter of 2024, smartphones constituted around 78 percent of retail site traffic globally, responsible for generating 68 percent of online shopping orders. Marketplace momentum Retail e-commerce has significantly increased globally over the past few years. Currently, the leading countries in retail e-commerce growth, such as the Philippines, have seen an increase of up to 24 percent. In 2024, the majority of online purchases worldwide were made on online marketplaces, incurring around a 30 percent share of consumer purchases. The top four retail websites for consumers to visit globally were all marketplaces, with the leading website being Amazon.com. Converting clicks When shopping online, website visits often do not end in purchases. This can be due to having second thoughts when online shopping, or simply due to consumers using the platforms to search for products. In 2024, the conversion rate of online shoppers globally was just over two percent, with food and beverages incurring the highest conversion rate from online purchases. Across the globe, almost 20 percent of all retail sales were conducted online. This figure is forecast to increase to at least 21 percent by 2027.

  6. d

    Enhanced Global Steel Trade Monitor

    • datasets.ai
    • catalog.data.gov
    • +1more
    Updated Aug 1, 2016
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    Department of Commerce (2016). Enhanced Global Steel Trade Monitor [Dataset]. https://datasets.ai/datasets/enhanced-global-steel-trade-monitor
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    Dataset updated
    Aug 1, 2016
    Dataset authored and provided by
    Department of Commerce
    Description

    Enforcement and Compliance's Global Steel Trade Monitor provides global import and export trends for the top countries trading in steel mill products.To supplement ITA's core trade statistics in the Steel Import Monitoring and Analysis (SIMA) system, quarterly country reports for the top 20 steel importing and top 20 steel exporting countries will be published.Each country report includes export and import trends by country and aggregate product, production and consumption data, and where available, information about trade remedy actions taken on steel products.

  7. Variability and control of carbon consumption, export and accumulation in...

    • dataone.org
    • catalog.data.gov
    • +1more
    Updated Mar 24, 2016
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    Just Cebrian (2016). Variability and control of carbon consumption, export and accumulation in marine communities - Dataset (NCEI Accession 0131995) [Dataset]. https://dataone.org/datasets/%7B393FF0E4-DCF1-45D3-B48D-2A41B55AC647%7D
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    Dataset updated
    Mar 24, 2016
    Dataset provided by
    National Oceanic and Atmospheric Administrationhttp://www.noaa.gov/
    National Centers for Environmental Informationhttps://www.ncei.noaa.gov/
    Authors
    Just Cebrian
    Time period covered
    Jan 1, 1962 - Dec 31, 1997
    Area covered
    Description

    This dataset is a compilation of published data on primary production, decomposition, herbivory, export, and refractory accumulation of primary producers in a wide range of marine community types.

  8. Quarterly global online shopper conversion rate 2024, by country and region

    • statista.com
    Updated Mar 4, 2025
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    Koen van Gelder (2025). Quarterly global online shopper conversion rate 2024, by country and region [Dataset]. https://www.statista.com/topics/871/online-shopping/
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    Dataset updated
    Mar 4, 2025
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Koen van Gelder
    Description

    During the fourth quarter of 2024, 3.1 percent of visits to e-commerce websites in the UK converted to purchases. In Switzerland, online shopper conversion rates stood at 2.9 percent. Mobile takes over e-shopping Online shopping has long since established itself as an everyday activity of online life – this holds for both desktop and mobile. As of the third quarter of 2024, more than three-quarters of retail site visits worldwide came from smartphones and generated about two-thirds of online shopping orders. Based on mobile retail performance growth, it is only a matter of time before mobile overtakes desktop in revenue generation.

  9. NCEP GFS 0.25 Degree Global Forecast Grids Historical Archive

    • rda.ucar.edu
    • data.ucar.edu
    • +2more
    Updated Jan 26, 2015
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    National Centers for Environmental Prediction/National Weather Service/NOAA/U.S. Department of Commerce (2015). NCEP GFS 0.25 Degree Global Forecast Grids Historical Archive [Dataset]. http://doi.org/10.5065/D65D8PWK
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    Dataset updated
    Jan 26, 2015
    Dataset provided by
    University Corporation for Atmospheric Research
    Authors
    National Centers for Environmental Prediction/National Weather Service/NOAA/U.S. Department of Commerce
    Time period covered
    Jan 15, 2015 - Jun 23, 2025
    Area covered
    Earth
    Description

    The NCEP operational Global Forecast System analysis and forecast grids are on a 0.25 by 0.25 global latitude longitude grid. Grids include analysis and forecast time steps at a 3 hourly interval from 0 to 240, and a 12 hourly interval from 240 to 384. Model forecast runs occur at 00, 06, 12, and 18 UTC daily. For real-time data access please use the NCEP data server [http://www.nco.ncep.noaa.gov/pmb/products/gfs/].

    NOTE: This dataset now has a direct, continuously updating copy located on AWS (https://noaa-gfs-bdp-pds.s3.amazonaws.com/index.html [https://noaa-gfs-bdp-pds.s3.amazonaws.com/index.html]). Therefore, the RDA will stop updating this dataset in early 2025

  10. Patterns of herbivory and decomposition in aquatic and terrestrial...

    • dataone.org
    • catalog.data.gov
    Updated Mar 24, 2016
    + more versions
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    Just Cebrian (2016). Patterns of herbivory and decomposition in aquatic and terrestrial ecosystems: Role of first-order consumers in ecosystem carbon flow - Dataset (NCEI Accession 0131996) [Dataset]. https://dataone.org/datasets/%7B132EE523-6865-404B-A0B7-D95F4023ECA1%7D
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    Dataset updated
    Mar 24, 2016
    Dataset provided by
    National Oceanic and Atmospheric Administrationhttp://www.noaa.gov/
    National Centers for Environmental Informationhttps://www.ncei.noaa.gov/
    Authors
    Just Cebrian
    Time period covered
    Jan 1, 1962 - Dec 31, 2000
    Area covered
    Description

    This dataset is a compilation of published data on primary production, detrital production, herbivorous consumption, detrital consumption, decomposition, producer biomass, consumer biomass, and nutrient content of primary producers and their detritus.

  11. K10 Global 10km Analyzed SST data set for 2016-02-18 (NCEI Accession...

    • dataone.org
    Updated Apr 6, 2016
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    NOAA NCEI Environmental Data Archive (2016). K10 Global 10km Analyzed SST data set for 2016-02-18 (NCEI Accession 0146112) [Dataset]. https://dataone.org/datasets/%7BF03F2068-0698-476B-826D-95DBDEB3E1BB%7D
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    Dataset updated
    Apr 6, 2016
    Dataset provided by
    National Oceanic and Atmospheric Administrationhttp://www.noaa.gov/
    National Centers for Environmental Informationhttps://www.ncei.noaa.gov/
    Time period covered
    Feb 18, 2016
    Area covered
    Description

    A Group for High Resolution Sea Surface Temperature (GHRSST) Level 4 sea surface temperature analysis produced daily on an operational basis at the Naval Oceanographic Office (NAVOCEANO) on a global 0.1 degree grid. The K10 L4 sea surface temperature analysis uses SST observations from the Advanced Very High Resolution Radiometer (AVHRR), the Advanced Microwave Scanning Radiometer for EOS (AMSR-E), and the Geostationary Operational Environmental Satellite (GOES) Imager. The age, reliability, and resolution of the data are used in the weighted average with the analysis tuned to represent SST at 1 meter depth. AVHRR Pathfinder 9km climatology is used when no new satellite SST retrievals are available after 34 days.

  12. K10 Global 10km Analyzed SST data set for 2016-08-03 (NCEI Accession...

    • search.dataone.org
    Updated Jan 14, 2017
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    NOAA NCEI Environmental Data Archive (2017). K10 Global 10km Analyzed SST data set for 2016-08-03 (NCEI Accession 0158547) [Dataset]. https://search.dataone.org/view/%7B83CB9EB3-1072-4D36-8DAE-478608ADCECB%7D
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    Dataset updated
    Jan 14, 2017
    Dataset provided by
    National Oceanic and Atmospheric Administrationhttp://www.noaa.gov/
    National Centers for Environmental Informationhttps://www.ncei.noaa.gov/
    Time period covered
    Aug 3, 2016
    Area covered
    Description

    A Group for High Resolution Sea Surface Temperature (GHRSST) Level 4 sea surface temperature analysis produced daily on an operational basis at the Naval Oceanographic Office (NAVOCEANO) on a global 0.1 degree grid. The K10 L4 sea surface temperature analysis uses SST observations from the Advanced Very High Resolution Radiometer (AVHRR), the Advanced Microwave Scanning Radiometer for EOS (AMSR-E), and the Geostationary Operational Environmental Satellite (GOES) Imager. The age, reliability, and resolution of the data are used in the weighted average with the analysis tuned to represent SST at 1 meter depth. AVHRR Pathfinder 9km climatology is used when no new satellite SST retrievals are available after 34 days.

  13. Enhanced Magnetic Model 2015

    • datasets.ai
    • gimi9.com
    • +4more
    0, 21
    Updated Aug 29, 2024
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    National Oceanic and Atmospheric Administration, Department of Commerce (2024). Enhanced Magnetic Model 2015 [Dataset]. https://datasets.ai/datasets/enhanced-magnetic-model-20151
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    21, 0Available download formats
    Dataset updated
    Aug 29, 2024
    Dataset provided by
    National Oceanic and Atmospheric Administrationhttp://www.noaa.gov/
    Authors
    National Oceanic and Atmospheric Administration, Department of Commerce
    Description

    The Enhanced Magnetic Model (EMM) extends to degree and order 720, resolving magnetic anomalies down to 56 km wavelength. The higher resolution of the EMM results in significantly improved pointing accuracy than the World Magnetic Model (WMM), which uses spherical harmonic representation to degree and order 12, resolving the magnetic field at 3000 km wavelength. The EMM model provides the magnetic field vector at any desired location and altitude close to and above the Earth's surface.

  14. u

    NCEP GDAS/FNL 0.25 Degree Global Tropospheric Analyses and Forecast Grids

    • data.ucar.edu
    • rda.ucar.edu
    • +2more
    grib
    Updated Jun 5, 2025
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    National Centers for Environmental Prediction, National Weather Service, NOAA, U.S. Department of Commerce (2025). NCEP GDAS/FNL 0.25 Degree Global Tropospheric Analyses and Forecast Grids [Dataset]. http://doi.org/10.5065/D65Q4T4Z
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    gribAvailable download formats
    Dataset updated
    Jun 5, 2025
    Dataset provided by
    Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory
    Authors
    National Centers for Environmental Prediction, National Weather Service, NOAA, U.S. Department of Commerce
    Time period covered
    Jul 8, 2015 - Jun 5, 2025
    Area covered
    Earth
    Description

    These NCEP FNL (Final) operational global analysis and forecast data are on 0.25-degree by 0.25-degree grids prepared operationally every six hours. This product is from the Global Data Assimilation System (GDAS), which continuously collects observational data from the Global Telecommunications System (GTS), and other sources, for many analyses. The FNLs are made with the same model which NCEP uses in the Global Forecast System (GFS), but the FNLs are prepared about an hour or so after the GFS is initialized. The FNLs are delayed so that more observational data can be used. The GFS is run earlier in support of time critical forecast needs, and uses the FNL from the previous 6 hour cycle as part of its initialization. The analyses are available on the surface, at 26 mandatory (and other pressure) levels from 1000 millibars to 10 millibars, in the surface boundary layer and at some sigma layers, the tropopause and a few others. Parameters include surface pressure, sea level pressure, geopotential height, temperature, sea surface temperature, soil values, ice cover, relative humidity, u- and v- winds, vertical motion, vorticity and ozone. The archive time series is continuously extended to a near-current date. It is not maintained in real-time.

  15. u

    NCEP FNL Operational Model Global Tropospheric Analyses, continuing from...

    • data.ucar.edu
    • rda-web-prod.ucar.edu
    • +2more
    grib
    Updated Jun 5, 2025
    + more versions
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    National Centers for Environmental Prediction, National Weather Service, NOAA, U.S. Department of Commerce (2025). NCEP FNL Operational Model Global Tropospheric Analyses, continuing from July 1999 [Dataset]. http://doi.org/10.5065/D6M043C6
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    gribAvailable download formats
    Dataset updated
    Jun 5, 2025
    Dataset provided by
    Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory
    Authors
    National Centers for Environmental Prediction, National Weather Service, NOAA, U.S. Department of Commerce
    Time period covered
    Jul 30, 1999 - Jun 5, 2025
    Area covered
    Earth
    Description

    These NCEP FNL (Final) Operational Global Analysis data are on 1-degree by 1-degree grids prepared operationally every six hours. This product is from the Global Data Assimilation System (GDAS), which continuously collects observational data from the Global Telecommunications System (GTS), and other sources, for many analyses. The FNLs are made with the same model which NCEP uses in the Global Forecast System (GFS), but the FNLs are prepared about an hour or so after the GFS is initialized. The FNLs are delayed so that more observational data can be used. The GFS is run earlier in support of time critical forecast needs, and uses the FNL from the previous 6 hour cycle as part of its initialization. The analyses are available on the surface, at 26 mandatory (and other pressure) levels from 1000 millibars to 10 millibars, in the surface boundary layer and at some sigma layers, the tropopause and a few others. Parameters include surface pressure, sea level pressure, geopotential height, temperature, sea surface temperature, soil values, ice cover, relative humidity, u- and v- winds, vertical motion, vorticity and ozone. The archive time series is continuously extended to a near-current date. It is not maintained in real-time.

  16. K10 Global 10km Analyzed SST data set for 2016-09-21 (NCEI Accession...

    • search.dataone.org
    Updated Jan 13, 2017
    + more versions
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    NOAA NCEI Environmental Data Archive (2017). K10 Global 10km Analyzed SST data set for 2016-09-21 (NCEI Accession 0158157) [Dataset]. https://search.dataone.org/view/%7B08AA1564-80D1-4C22-A619-CFB2048D3483%7D
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    Dataset updated
    Jan 13, 2017
    Dataset provided by
    National Oceanic and Atmospheric Administrationhttp://www.noaa.gov/
    National Centers for Environmental Informationhttps://www.ncei.noaa.gov/
    Time period covered
    Sep 21, 2016
    Area covered
    Description

    A Group for High Resolution Sea Surface Temperature (GHRSST) Level 4 sea surface temperature analysis produced daily on an operational basis at the Naval Oceanographic Office (NAVOCEANO) on a global 0.1 degree grid. The K10 L4 sea surface temperature analysis uses SST observations from the Advanced Very High Resolution Radiometer (AVHRR), the Advanced Microwave Scanning Radiometer for EOS (AMSR-E), and the Geostationary Operational Environmental Satellite (GOES) Imager. The age, reliability, and resolution of the data are used in the weighted average with the analysis tuned to represent SST at 1 meter depth. AVHRR Pathfinder 9km climatology is used when no new satellite SST retrievals are available after 34 days.

  17. Amazon revenue 2004-2024

    • statista.com
    Updated Feb 21, 2025
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    Statista (2025). Amazon revenue 2004-2024 [Dataset]. https://www.statista.com/statistics/266282/annual-net-revenue-of-amazoncom/
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    Dataset updated
    Feb 21, 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 638 billion U.S. dollars, up from 575 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 185 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 353 billion U.S. dollars was earned in North America compared to only roughly 131 billion U.S. dollars internationally.

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    Learn how you can add new datasets to our index.

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Koen van Gelder (2025). Global online shopper per visit spend 2024, by category [Dataset]. https://www.statista.com/topics/871/online-shopping/
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Global online shopper per visit spend 2024, by category

Explore at:
Dataset updated
Mar 4, 2025
Dataset provided by
Statistahttp://statista.com/
Authors
Koen van Gelder
Description

In the fourth quarter of 2024, online shoppers spent an average of about 2.98 U.S. dollars per visit across all verticals. Electronics is the category in which consumers spent the most money per visit on average, at 3.32 U.S. dollars, followed by luxury apparel at 3.10 dollars. Nickels and dimes Over the past few years, the average order value for e-commerce purchases has increased globally, from around 118 U.S. dollars in September 2022 to around 126 U.S. dollars in the same month of 2023. The average order value also depends heavily on the online traffic source consumers use. In 2023, the value per order value was the highest when navigating directly, averaging around 167 dollars. Direct navigation means searching for a website directly in the browser's address bar, bypassing the use of search engines. Orders placed from social media stores were the lowest in value, with an average of less than 110 dollars. Mobile shopping on the rise Online shoppers have clear preferences when it comes to device type. When comparing gadgets, the average purchase amount has always been the highest for desktops, with an order value of 160 U.S. dollars. This indicates that bigger purchases are made via desktop computers. However, consumers are more likely to complete orders when shopping on mobile devices. Mobile devices were also clearly preferred when browsing retail websites, with around three-fourths of consumers using smartphones instead of desktops or tablets.

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