100+ datasets found
  1. E-Commerce Data

    • kaggle.com
    zip
    Updated Aug 17, 2017
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    Carrie (2017). E-Commerce Data [Dataset]. https://www.kaggle.com/datasets/carrie1/ecommerce-data
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    zip(7548686 bytes)Available download formats
    Dataset updated
    Aug 17, 2017
    Authors
    Carrie
    Description

    Context

    Typically e-commerce datasets are proprietary and consequently hard to find among publicly available data. However, The UCI Machine Learning Repository has made this dataset containing actual transactions from 2010 and 2011. The dataset is maintained on their site, where it can be found by the title "Online Retail".

    Content

    "This is a transnational data set which contains all the transactions occurring between 01/12/2010 and 09/12/2011 for a UK-based and registered non-store online retail.The company mainly sells unique all-occasion gifts. Many customers of the company are wholesalers."

    Acknowledgements

    Per the UCI Machine Learning Repository, this data was made available by Dr Daqing Chen, Director: Public Analytics group. chend '@' lsbu.ac.uk, School of Engineering, London South Bank University, London SE1 0AA, UK.

    Image from stocksnap.io.

    Inspiration

    Analyses for this dataset could include time series, clustering, classification and more.

  2. E-commerce dataset by Olist (SQLite)

    • kaggle.com
    zip
    Updated Apr 28, 2024
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    Terenci Claramunt (2024). E-commerce dataset by Olist (SQLite) [Dataset]. https://www.kaggle.com/datasets/terencicp/e-commerce-dataset-by-olist-as-an-sqlite-database
    Explore at:
    zip(51085670 bytes)Available download formats
    Dataset updated
    Apr 28, 2024
    Authors
    Terenci Claramunt
    License

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

    Description

    I imported the two Olist Kaggle datasets into an SQLite database. I modified the original table names to make them shorter and easier to understand. Here's the Entity-Relationship Diagram of the resulting SQLite database:

    https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F2473556%2F23a7d4d8cd99e36e32e57303eb804fff%2Fdb-schema.png?generation=1714391550829633&alt=media" alt="Database Schema">

    Data sources:

    https://www.kaggle.com/datasets/olistbr/brazilian-ecommerce

    https://www.kaggle.com/datasets/olistbr/marketing-funnel-olist


    I used this database as a data source for my notebook:

    SQL Challenge: E-commerce data analysis

  3. U

    United States E-Commerce Transactions: Volume: E-Commerce & Shopping:...

    • ceicdata.com
    Updated Oct 15, 2025
    + more versions
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    CEICdata.com (2025). United States E-Commerce Transactions: Volume: E-Commerce & Shopping: Classifieds [Dataset]. https://www.ceicdata.com/en/united-states/ecommerce-transactions-by-category/ecommerce-transactions-volume-ecommerce--shopping-classifieds
    Explore at:
    Dataset updated
    Oct 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 18, 2025 - Mar 1, 2025
    Area covered
    United States
    Description

    United States E-Commerce Transactions: Volume: E-Commerce & Shopping: Classifieds data was reported at 13.000 Unit in 10 May 2025. This records a decrease from the previous number of 33.000 Unit for 09 May 2025. United States E-Commerce Transactions: Volume: E-Commerce & Shopping: Classifieds data is updated daily, averaging 43.000 Unit from Dec 2018 (Median) to 10 May 2025, with 2322 observations. The data reached an all-time high of 697.000 Unit in 27 Nov 2022 and a record low of 2.000 Unit in 31 Dec 2018. United States E-Commerce Transactions: Volume: E-Commerce & Shopping: Classifieds data remains active status in CEIC and is reported by Grips Intelligence Inc.. The data is categorized under Global Database’s United States – Table US.GI.EC: E-Commerce Transactions: by Category.

  4. Food & personal care: top 5 online stores in the United Kingdom in 2021, by...

    • statista.com
    Updated Sep 25, 2018
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    Yihan Ma (2018). Food & personal care: top 5 online stores in the United Kingdom in 2021, by net sales [Dataset]. https://www.statista.com/study/57591/ecommercedb-top-online-stores-worldwide/
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    Dataset updated
    Sep 25, 2018
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Yihan Ma
    Description

    This statistic presents a ranking of the most popular online stores in the United Kingdom in the food and personal care segment in 2021, sorted by annual net e-commerce sales. For more information please visit ecommerceDB.com.In 2021, market leader tesco.com generated 6.1 billion U.S. dollars via the sale of products from the foor and personal care segment in the United Kingdom. The online store sainsbury.co.uk was ranked second with a revenue of 4 billion U.S. dollars.

  5. Data from: E-commerce and ICT activity

    • ons.gov.uk
    • cy.ons.gov.uk
    xlsx
    Updated Feb 5, 2021
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    Office for National Statistics (2021). E-commerce and ICT activity [Dataset]. https://www.ons.gov.uk/businessindustryandtrade/itandinternetindustry/datasets/ictactivityofukbusinessesecommerceandictactivity
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    xlsxAvailable download formats
    Dataset updated
    Feb 5, 2021
    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

    Use of information and communication technology (ICT) and e-commerce activity by UK businesses. Annual data on e-commerce sales and how businesses are using the internet.

  6. ECommerce Data Analysis

    • kaggle.com
    Updated Jan 1, 2024
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    M Mohaiminul Islam (2024). ECommerce Data Analysis [Dataset]. https://www.kaggle.com/datasets/mmohaiminulislam/ecommerce-data-analysis
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jan 1, 2024
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    M Mohaiminul Islam
    License

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

    Description

    Objectives:

    • I leveraged advanced data visualization techniques to extract valuable insights from a comprehensive dataset. By visualizing sales patterns, customer behavior, and product trends, I identified key growth opportunities and provided actionable recommendations to optimize business strategies and enhance overall performance. you can find the GitHub repo here Link to GitHub Repository.

    Data Description:

    there are exactly 6 table and 1 is a fact table and the rest of them are dimension tables: Fact Table:

    payment_key:
      Description: An identifier representing the payment transaction associated with the fact.
      Use Case: This key links to a payment dimension table, providing details about the payment method and related information.
    
    customer_key:
      Description: An identifier representing the customer associated with the fact.
      Use Case: This key links to a customer dimension table, providing details about the customer, such as name, address, and other customer-specific information.
    
    time_key:
      Description: An identifier representing the time dimension associated with the fact.
      Use Case: This key links to a time dimension table, providing details about the time of the transaction, such as date, day of the week, and month.
    
    item_key:
      Description: An identifier representing the item or product associated with the fact.
      Use Case: This key links to an item dimension table, providing details about the product, such as category, sub-category, and product name.
    
    store_key:
      Description: An identifier representing the store or location associated with the fact.
      Use Case: This key links to a store dimension table, providing details about the store, such as location, store name, and other store-specific information.
    
    quantity:
      Description: The quantity of items sold or involved in the transaction.
      Use Case: Represents the amount or number of items associated with the transaction.
    
    unit:
      Description: The unit or measurement associated with the quantity (e.g., pieces, kilograms).
      Use Case: Specifies the unit of measurement for the quantity.
    
    unit_price:
      Description: The price per unit of the item.
      Use Case: Represents the cost or price associated with each unit of the item.
    
    total_price:
      Description: The total price of the transaction, calculated as the product of quantity and unit price.
      Use Case: Represents the overall cost or revenue generated by the transaction.
    

    Customer Table: customer_key:

    Description: An identifier representing a unique customer.
    Use Case: Serves as the primary key to link with the fact table, allowing for easy and efficient retrieval of customer-specific information.
    

    name:

    Description: The name of the customer.
    Use Case: Captures the personal or business name of the customer for identification and reference purposes.
    

    contact_no:

    Description: The contact number associated with the customer.
    Use Case: Stores the phone number or contact details for communication or outreach purposes.
    

    nid:

    Description: The National ID (NID) or a unique identification number for the customer.
    

    Item Table: item_key:

    Description: An identifier representing a unique item or product.
    Use Case: Serves as the primary key to link with the fact table, enabling retrieval of detailed information about specific items in transactions.
    

    item_name:

    Description: The name or title of the item.
    Use Case: Captures the descriptive name of the item, providing a recognizable label for the product.
    

    desc:

    Description: A description of the item.
    Use Case: Contains additional details about the item, such as features, specifications, or any relevant information.
    

    unit_price:

    Description: The price per unit of the item.
    Use Case: Represents the cost or price associated with each unit of the item.
    

    man_country:

    Description: The country where the item is manufactured.
    Use Case: Captures the origin or manufacturing location of the item.
    

    supplier:

    Description: The supplier or vendor providing the item.
    Use Case: Stores the name or identifier of the supplier, facilitating tracking of item sources.
    

    unit:

    Description: The unit of measurement associated with the item (e.g., pieces, kilograms).
    

    Store Table: store_key:

    Description: An identifier representing a unique store or location.
    Use Case: Serves as the primary key to link with the fact table, allowing for easy retrieval of information about transactions associated with specific stores.
    

    division:

    Description: The administrative division or region where the store is located.
    Use Case: Captures the broader geographical area in which...
    
  7. F

    E-Commerce Retail Sales

    • fred.stlouisfed.org
    json
    Updated Aug 19, 2025
    + more versions
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    (2025). E-Commerce Retail Sales [Dataset]. https://fred.stlouisfed.org/series/ECOMSA
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Aug 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 (ECOMSA) from Q4 1999 to Q2 2025 about e-commerce, retail trade, sales, retail, and USA.

  8. S

    Singapore E-Commerce Transactions: AOV: Heavy Industry & Engineering: Heavy...

    • ceicdata.com
    Updated Nov 1, 2023
    + more versions
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    CEICdata.com (2023). Singapore E-Commerce Transactions: AOV: Heavy Industry & Engineering: Heavy Industry & Engineering [Dataset]. https://www.ceicdata.com/en/singapore/ecommerce-transactions-by-category
    Explore at:
    Dataset updated
    Nov 1, 2023
    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 29, 2024 - Mar 16, 2025
    Area covered
    Singapore
    Description

    E-Commerce Transactions: AOV: Heavy Industry & Engineering: Heavy Industry & Engineering data was reported at 28.023 USD in 30 Mar 2025. This records an increase from the previous number of 2.633 USD for 23 Mar 2025. E-Commerce Transactions: AOV: Heavy Industry & Engineering: Heavy Industry & Engineering data is updated daily, averaging 136.247 USD from Sep 2019 (Median) to 30 Mar 2025, with 283 observations. The data reached an all-time high of 14,209.838 USD in 19 Oct 2023 and a record low of 2.633 USD in 23 Mar 2025. E-Commerce Transactions: AOV: Heavy Industry & Engineering: Heavy Industry & Engineering data remains active status in CEIC and is reported by Grips Intelligence Inc.. The data is categorized under Global Database’s Singapore – Table SG.GI.EC: E-Commerce Transactions: by Category.

  9. U

    United Kingdom E Commerce: Business With Website

    • ceicdata.com
    Updated Nov 15, 2025
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    CEICdata.com (2025). United Kingdom E Commerce: Business With Website [Dataset]. https://www.ceicdata.com/en/united-kingdom/e-commerce-proportion-of-businesses-with-a-website/e-commerce-business-with-website
    Explore at:
    Dataset updated
    Nov 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
    Dec 1, 2007 - Dec 1, 2016
    Area covered
    United Kingdom
    Variables measured
    Business Outlook Survey
    Description

    United Kingdom E Commerce: Business With Website data was reported at 82.000 % in 2017. This records a decrease from the previous number of 83.700 % for 2016. United Kingdom E Commerce: Business With Website data is updated yearly, averaging 80.300 % from Dec 2007 (Median) to 2017, with 11 observations. The data reached an all-time high of 83.700 % in 2016 and a record low of 70.000 % in 2007. United Kingdom E Commerce: Business With Website data remains active status in CEIC and is reported by Office for National Statistics. The data is categorized under Global Database’s United Kingdom – Table UK.S033: E Commerce: Proportion of Businesses With a Website.

  10. d

    Ecommerce Market Data | South-east Asia E-commerce Contacts | 170M Profiles...

    • datarade.ai
    + more versions
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    Success.ai, Ecommerce Market Data | South-east Asia E-commerce Contacts | 170M Profiles | Verified Accuracy | Best Price Guarantee [Dataset]. https://datarade.ai/data-products/ecommerce-market-data-south-east-asia-e-commerce-contacts-success-ai
    Explore at:
    .bin, .json, .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset provided by
    Success.ai
    Area covered
    Nepal, Yemen, Sri Lanka, Israel, Timor-Leste, Philippines, Iraq, Lebanon, Syrian Arab Republic, Qatar, South East Asia
    Description

    Success.ai’s Ecommerce Market Data for South-east Asia E-commerce Contacts provides a robust and accurate dataset tailored for businesses and organizations looking to connect with professionals in the fast-growing e-commerce industry across South-east Asia. Covering roles such as e-commerce managers, digital strategists, logistics experts, and online marketplace leaders, this dataset offers verified contact details, professional insights, and actionable market data.

    With access to over 170 million verified profiles globally, Success.ai ensures your outreach, marketing, and research strategies are powered by accurate, continuously updated, and AI-validated data. Backed by our Best Price Guarantee, this solution empowers you to excel in one of the world’s most dynamic e-commerce regions.

    Why Choose Success.ai’s Ecommerce Market Data?

    1. Verified Contact Data for Precision Outreach

      • Access verified work emails, phone numbers, and LinkedIn profiles of e-commerce professionals across South-east Asia.
      • AI-driven validation ensures 99% accuracy, reducing communication inefficiencies and enhancing engagement rates.
    2. Comprehensive Coverage of South-east Asia’s E-commerce Market

      • Includes professionals from key e-commerce hubs such as Singapore, Indonesia, Thailand, Vietnam, Malaysia, and the Philippines.
      • Gain insights into regional consumer trends, logistics challenges, and online marketplace dynamics.
    3. Continuously Updated Datasets

      • Real-time updates capture changes in professional roles, company expansions, and market conditions.
      • Stay aligned with industry trends and emerging opportunities in South-east Asia’s e-commerce sector.
    4. Ethical and Compliant

      • Fully adheres to GDPR, CCPA, and other global data privacy regulations, ensuring responsible and lawful data usage.

    Data Highlights:

    • 170M+ Verified Global Profiles: Engage with e-commerce professionals and decision-makers across South-east Asia.
    • Verified Contact Details: Gain work emails, phone numbers, and LinkedIn profiles for precision targeting.
    • Regional Insights: Understand key trends in e-commerce, logistics, and consumer preferences in South-east Asia.
    • Leadership Insights: Connect with online marketplace leaders, logistics managers, and digital marketing professionals driving innovation in the sector.

    Key Features of the Dataset:

    1. Comprehensive Professional Profiles in E-commerce

      • Identify and connect with professionals managing e-commerce platforms, online marketplaces, and logistics operations.
      • Target individuals responsible for digital marketing, supply chain management, and e-commerce strategies.
    2. Advanced Filters for Precision Campaigns

      • Filter professionals by industry focus (apparel, electronics, food delivery), geographic location, or job function.
      • Tailor campaigns to align with specific business goals, such as logistics optimization, consumer engagement, or market entry.
    3. Regional and Market-specific Insights

      • Leverage data on e-commerce trends, regional consumer behaviors, and logistics challenges unique to South-east Asia.
      • Refine marketing strategies and business plans based on actionable insights from the region.
    4. AI-Driven Enrichment

      • Profiles enriched with actionable data enable personalized messaging, highlight unique value propositions, and improve engagement outcomes.

    Strategic Use Cases:

    1. Marketing Campaigns and Digital Outreach

      • Promote e-commerce solutions, logistics services, or online marketing tools to professionals in South-east Asia’s e-commerce industry.
      • Use verified contact data for multi-channel outreach, including email, phone, and digital campaigns.
    2. Market Research and Competitive Analysis

      • Analyze e-commerce trends and consumer preferences across South-east Asia to refine product offerings and marketing strategies.
      • Benchmark against competitors to identify growth opportunities and high-demand solutions.
    3. Partnership Development and Vendor Collaboration

      • Build relationships with e-commerce platforms, logistics providers, and digital marketing agencies exploring strategic partnerships.
      • Foster collaborations that enhance consumer experiences, improve delivery efficiency, or expand market reach.
    4. Recruitment and Talent Acquisition

      • Target HR professionals and hiring managers in the e-commerce industry seeking candidates for logistics, digital marketing, and platform management roles.
      • Provide workforce optimization platforms or training solutions tailored to the sector.

    Why Choose Success.ai?

    1. Best Price Guarantee

      • Access premium-quality e-commerce market data at competitive prices, ensuring strong ROI for your marketing, sales, and business development initiatives.
    2. Seamless Integration

      • Integrate verified e-commerce data into CRM systems, analytics ...
  11. S

    Singapore E-Commerce Transactions: AOV: Health: Health

    • ceicdata.com
    Updated Nov 1, 2023
    + more versions
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    CEICdata.com (2023). Singapore E-Commerce Transactions: AOV: Health: Health [Dataset]. https://www.ceicdata.com/en/singapore/ecommerce-transactions-by-category
    Explore at:
    Dataset updated
    Nov 1, 2023
    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 18, 2025 - Mar 1, 2025
    Area covered
    Singapore
    Description

    E-Commerce Transactions: AOV: Health: Health data was reported at 44.692 USD in 10 May 2025. This records an increase from the previous number of 42.366 USD for 04 May 2025. E-Commerce Transactions: AOV: Health: Health data is updated daily, averaging 65.643 USD from Dec 2018 (Median) to 10 May 2025, with 2210 observations. The data reached an all-time high of 259.705 USD in 24 Feb 2020 and a record low of 35.118 USD in 30 Jan 2020. E-Commerce Transactions: AOV: Health: Health data remains active status in CEIC and is reported by Grips Intelligence Inc.. The data is categorized under Global Database’s Singapore – Table SG.GI.EC: E-Commerce Transactions: by Category.

  12. Ecommerce Merchant Data | Global E-commerce Professionals | 170M Verified...

    • datarade.ai
    Updated Oct 27, 2021
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    Success.ai (2021). Ecommerce Merchant Data | Global E-commerce Professionals | 170M Verified Profiles | Work Emails & Direct Phone Numbers | Best Price Guarantee [Dataset]. https://datarade.ai/data-products/ecommerce-merchant-data-global-e-commerce-professionals-1-success-ai
    Explore at:
    .bin, .json, .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset updated
    Oct 27, 2021
    Dataset provided by
    Area covered
    Mali, Bosnia and Herzegovina, Nicaragua, Norfolk Island, Ghana, Czech Republic, Gabon, United Arab Emirates, Canada, Guadeloupe
    Description

    Success.ai’s Ecommerce Merchant Data and B2B Contact Data for Global E-commerce Professionals provides a comprehensive and highly accurate database from over 170 million verified profiles. Specifically tailored for the e-commerce sector, this dataset features work emails, direct phone numbers, and enriched professional profiles to connect businesses with the leaders and decision-makers shaping the global e-commerce landscape. Continuously updated with advanced AI validation, this resource is ideal for enhancing marketing campaigns, sales initiatives, recruitment efforts, and market research.

    Key Features of Success.ai's Global E-commerce Professional Contact Data

    1. Global Data Coverage Gain access to an extensive database spanning key e-commerce markets worldwide. With verified profiles from 170M+ professionals, Success.ai ensures you can connect with global influencers, decision-makers, and strategists across diverse regions and industries.

    2. AI-Driven Accuracy Harness the power of AI validation for 99% accuracy rates across emails and phone numbers. Our continuously updated dataset ensures that you reach the right professionals with reliable and actionable contact data.

    3. Tailored for E-commerce Professionals Our data includes profiles of experts in online retail, supply chain logistics, payment systems, digital marketing, and e-commerce technology, making it a perfect fit for targeting niche segments within the e-commerce industry.

    4. Customizable Data Delivery Choose from API integrations, custom flat files, or direct database access to seamlessly integrate this dataset into your existing systems, empowering your team with flexibility and efficiency.

    5. Compliance-Ready Data Success.ai ensures all data is collected and processed in alignment with GDPR, CCPA, and other international compliance standards, so you can leverage this resource with confidence and ethical assurance.

    Why Choose Success.ai for Global E-commerce Contact Data?

    • Best Price Guarantee We offer a highly competitive pricing model that ensures the best value for high-quality, actionable data.

    • Strategic Applications Success.ai’s B2B Contact Data supports a variety of business functions:

    E-commerce Marketing Campaigns: Use verified contact information to launch targeted campaigns that reach decision-makers in the e-commerce sector. Sales and Outreach: Enhance your sales strategy with direct access to key players in global e-commerce. Talent Acquisition: Identify and engage with e-commerce professionals for roles in marketing, logistics, technology, and operations. Market Insights: Leverage enriched demographic and firmographic data to conduct in-depth market research and refine your strategies. Business Networking: Build connections with professionals and companies driving innovation in the global e-commerce ecosystem.

    • Technology-Enhanced Solutions Our data delivery is optimized for seamless integration into your systems, including:

    Enrichment API: Real-time updates to maintain the accuracy and relevance of your contact database. Lead Generation API: Maximize outreach efforts with access to key contact information, enabling up to 860,000 API calls per day.

    • Data Highlights 170M+ Verified Global Profiles 50M Direct Phone Numbers 700M Total Professional Profiles Worldwide 70M Verified Company Profiles

    • Use Cases

    1. Enhanced Marketing: Empower your e-commerce marketing strategies with precise email and phone contact details.
    2. Sales Growth: Equip your sales team to connect with top-level executives and decision-makers.
    3. Recruitment Excellence: Source global e-commerce talent efficiently with verified professional profiles.
    4. Customer Understanding: Deepen insights into customer demographics for improved personalization.
    5. Partnership Building: Identify potential collaborators and strengthen relationships with influential industry players.

    Success.ai is the ultimate choice for global e-commerce data solutions, delivering unmatched volume, accuracy, and flexibility:

    • AI-Validated Data: Ensures a 99% accuracy rate to drive success in your campaigns. Extensive Reach: Access professionals and companies across key regions in the e-commerce sector.
    • Seamless Integration: Choose the data delivery method that works best for your business needs.
    • Compliance Assurance: Leverage ethically sourced data in adherence to global privacy regulations.

    Transform your e-commerce strategies today with Success.ai. Gain access to reliable, verified contact data for global e-commerce professionals and unlock unparalleled opportunities for growth and innovation.

    No one beats us on price. Period.

  13. Ecommerce Store Data | APAC E-commerce Sector | Verified Business Profiles...

    • datarade.ai
    Updated Jan 1, 2018
    + more versions
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    Success.ai (2018). Ecommerce Store Data | APAC E-commerce Sector | Verified Business Profiles with Key Insights | Best Price Guarantee [Dataset]. https://datarade.ai/data-products/ecommerce-store-data-apac-e-commerce-sector-verified-busi-success-ai
    Explore at:
    .bin, .json, .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset updated
    Jan 1, 2018
    Dataset provided by
    Area covered
    Fiji, Andorra, Lao People's Democratic Republic, Mexico, Malta, Northern Mariana Islands, Korea (Democratic People's Republic of), Italy, Austria, Canada
    Description

    Success.ai’s Ecommerce Store Data for the APAC E-commerce Sector provides a reliable and accurate dataset tailored for businesses aiming to connect with e-commerce professionals and organizations across the Asia-Pacific region. Covering roles and businesses involved in online retail, marketplace management, logistics, and digital commerce, this dataset includes verified business profiles, decision-maker contact details, and actionable insights.

    With access to continuously updated, AI-validated data and over 700 million global profiles, Success.ai ensures your outreach, market analysis, and partnership strategies are effective and data-driven. Backed by our Best Price Guarantee, this solution helps you excel in one of the world’s fastest-growing e-commerce markets.

    Why Choose Success.ai’s Ecommerce Store Data?

    1. Verified Profiles for Precision Engagement

      • Access verified profiles, business locations, employee counts, and decision-maker details for e-commerce businesses across APAC.
      • AI-driven validation ensures 99% accuracy, improving engagement rates and reducing outreach inefficiencies.
    2. Comprehensive Coverage of the APAC E-commerce Sector

      • Includes businesses from major e-commerce hubs such as China, India, Japan, South Korea, Australia, and Southeast Asia.
      • Gain insights into regional e-commerce trends, digital transformation efforts, and logistics innovations.
    3. Continuously Updated Datasets

      • Real-time updates ensure that business profiles, employee roles, and operational insights remain accurate and relevant.
      • Stay aligned with dynamic market conditions and emerging opportunities in the APAC region.
    4. Ethical and Compliant

      • Fully adheres to GDPR, CCPA, and other global data privacy regulations, ensuring responsible and lawful data usage.

    Data Highlights:

    • 700M+ Verified Global Profiles: Access business profiles for e-commerce professionals and organizations across APAC.
    • Firmographic Insights: Gain detailed information, including business locations, employee counts, and operational details.
    • Decision-maker Profiles: Connect with key e-commerce leaders, managers, and strategists driving online retail innovation.
    • Industry Trends: Understand emerging e-commerce trends, consumer behavior, and market dynamics in the APAC region.

    Key Features of the Dataset:

    1. Comprehensive E-commerce Business Profiles

      • Identify and connect with businesses specializing in online retail, marketplace management, and digital commerce logistics.
      • Target decision-makers involved in supply chain optimization, digital marketing, and platform development.
    2. Advanced Filters for Precision Campaigns

      • Filter businesses and professionals by industry focus (fashion, electronics, grocery), geographic location, or employee size.
      • Tailor campaigns to address specific goals, such as promoting technology adoption, enhancing customer engagement, or expanding supply chains.
    3. Regional and Sector-specific Insights

      • Leverage data on APAC’s fast-growing e-commerce markets, consumer purchasing trends, and regional challenges.
      • Refine your marketing strategies and outreach efforts to align with market priorities.
    4. AI-Driven Enrichment

      • Profiles enriched with actionable data allow for personalized messaging, highlight unique value propositions, and improve engagement outcomes.

    Strategic Use Cases:

    1. Marketing Campaigns and Outreach

      • Promote e-commerce solutions, logistics services, or digital commerce tools to businesses and professionals in the APAC region.
      • Use verified contact data for multi-channel outreach, including email, phone, and social media campaigns.
    2. Partnership Development and Vendor Collaboration

      • Build relationships with e-commerce marketplaces, logistics providers, and payment solution companies seeking strategic partnerships.
      • Foster collaborations that drive operational efficiency, enhance customer experiences, or expand market reach.
    3. Market Research and Competitive Analysis

      • Analyze regional e-commerce trends, consumer preferences, and logistics challenges to refine product offerings and business strategies.
      • Benchmark against competitors to identify growth opportunities and high-demand solutions.
    4. Recruitment and Talent Acquisition

      • Target HR professionals and hiring managers in the e-commerce industry recruiting for roles in operations, logistics, and digital marketing.
      • Provide workforce optimization platforms or training solutions tailored to the digital commerce sector.

    Why Choose Success.ai?

    1. Best Price Guarantee

      • Access premium-quality e-commerce store data at competitive prices, ensuring strong ROI for your marketing, sales, and strategic initiatives.
    2. Seamless Integration

      • Integrate verified e-commerce data into CRM systems, analytics platforms, or market...
  14. d

    Purchase Real-Time eCommerce Leads List | Gain Direct Access to Store Owners...

    • datacaptive.com
    Updated May 23, 2022
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    DataCaptive™ (2022). Purchase Real-Time eCommerce Leads List | Gain Direct Access to Store Owners | 40+ Data Points | Lifetime Access | DataCaptive [Dataset]. https://www.datacaptive.com/technology-users-email-list/ecommerce-company-data/
    Explore at:
    Dataset updated
    May 23, 2022
    Authors
    DataCaptive™
    Area covered
    New Zealand, United States, Kuwait, Norway, United Kingdom, Sweden, Romania, Australia, Bahrain, Georgia
    Description

    Unlock the door to business expansion by investing in our real-time eCommerce leads list. Gain direct access to store owners and make informed decisions with data fields including 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.

    Ensure a lifetime of access for continuous growth and tailor your campaigns with accurate and reliable information, initiating targeted efforts that align with your marketing goals. Whether you're targeting specific industries or global locations, our database provides up-to-date and valuable insights to support your business journey.

    • 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

  15. United Kingdom: Top 10 Toys & Baby online stores

    • statista.com
    Updated Sep 25, 2018
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    Yihan Ma (2018). United Kingdom: Top 10 Toys & Baby online stores [Dataset]. https://www.statista.com/study/57591/ecommercedb-top-online-stores-worldwide/
    Explore at:
    Dataset updated
    Sep 25, 2018
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Yihan Ma
    Description

    Amazon.co.uk is leading the Toys & Baby e-commerce market in the UK, with e-commerce net sales of US$854 million in 2021 generated in the UK, followed by argos.co.uk with US$779 million. Third place is taken by sainsburys.co.uk with a revenue of US$529 million. Very.co.uk is the fourth biggest Toys & Baby online store in the UK with net sales of US$302 million in 2021. For an extended ranking, please visit ecommerceDB.com.

  16. m

    E-Commerce Companies in the United Arab Emirates (UAE) - Domain Names and...

    • data.mendeley.com
    Updated Jan 15, 2024
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    Gurdal Ertek (2024). E-Commerce Companies in the United Arab Emirates (UAE) - Domain Names and Product Categories [Dataset]. http://doi.org/10.17632/dscx426m45.1
    Explore at:
    Dataset updated
    Jan 15, 2024
    Authors
    Gurdal Ertek
    License

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

    Area covered
    United Arab Emirates
    Description

    A dataset of the top 10,000 E-Commerce Companies in the United Arab Emirates (UAE), to accompany the paper that describes the analysis of domain names and product categories.

  17. d

    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
    Authors
    DataCaptive™
    Area covered
    Georgia, Finland, Jordan, Singapore, Sweden, Bahrain, Spain, United Kingdom, Canada, France
    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"

  18. d

    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
    Success.ai
    Area covered
    Georgia, Turkmenistan, Jordan, Kuwait, Cyprus, Singapore, Malaysia, Lebanon, Hong Kong, Bangladesh
    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.

    ...

  19. L

    Lebanon E-Commerce Transactions: AOV: E-Commerce & Shopping: E-Commerce &...

    • ceicdata.com
    Updated Aug 22, 2024
    + more versions
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    CEICdata.com (2024). Lebanon E-Commerce Transactions: AOV: E-Commerce & Shopping: E-Commerce & Shopping [Dataset]. https://www.ceicdata.com/en/lebanon/ecommerce-transactions-by-category/ecommerce-transactions-aov-ecommerce--shopping-ecommerce--shopping
    Explore at:
    Dataset updated
    Aug 22, 2024
    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
    Nov 12, 2023 - Aug 22, 2024
    Area covered
    Lebanon
    Description

    Lebanon E-Commerce Transactions: AOV: E-Commerce & Shopping: E-Commerce & Shopping data was reported at 143.612 USD in 22 Aug 2024. This records a decrease from the previous number of 177.227 USD for 16 Aug 2024. Lebanon E-Commerce Transactions: AOV: E-Commerce & Shopping: E-Commerce & Shopping data is updated daily, averaging 92.574 USD from Jan 2019 (Median) to 22 Aug 2024, with 703 observations. The data reached an all-time high of 1,925.262 USD in 19 Jun 2023 and a record low of 0.547 USD in 23 Jun 2020. Lebanon E-Commerce Transactions: AOV: E-Commerce & Shopping: E-Commerce & Shopping data remains active status in CEIC and is reported by Grips Intelligence Inc.. The data is categorized under Global Database’s Lebanon – Table LB.GI.EC: E-Commerce Transactions: by Category.

  20. E

    Egypt E-Commerce Transactions: Volume

    • ceicdata.com
    Updated Mar 3, 2025
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    CEICdata.com (2025). Egypt E-Commerce Transactions: Volume [Dataset]. https://www.ceicdata.com/en/egypt/ecommerce-transactions-by-device/ecommerce-transactions-volume
    Explore at:
    Dataset updated
    Mar 3, 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, 2024 - Mar 3, 2025
    Area covered
    Egypt
    Description

    Egypt E-Commerce Transactions: Volume data was reported at 4.000 Unit in 03 Mar 2025. This records a decrease from the previous number of 9.000 Unit for 24 Feb 2025. Egypt E-Commerce Transactions: Volume data is updated daily, averaging 223.000 Unit from Dec 2018 (Median) to 03 Mar 2025, with 1996 observations. The data reached an all-time high of 1,758.000 Unit in 26 Nov 2021 and a record low of 2.000 Unit in 11 Aug 2024. Egypt E-Commerce Transactions: Volume data remains active status in CEIC and is reported by Grips Intelligence Inc.. The data is categorized under Global Database’s Egypt – Table EG.GI.EC: E-Commerce Transactions: by Device.

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Carrie (2017). E-Commerce Data [Dataset]. https://www.kaggle.com/datasets/carrie1/ecommerce-data
Organization logo

E-Commerce Data

Actual transactions from UK retailer

Explore at:
zip(7548686 bytes)Available download formats
Dataset updated
Aug 17, 2017
Authors
Carrie
Description

Context

Typically e-commerce datasets are proprietary and consequently hard to find among publicly available data. However, The UCI Machine Learning Repository has made this dataset containing actual transactions from 2010 and 2011. The dataset is maintained on their site, where it can be found by the title "Online Retail".

Content

"This is a transnational data set which contains all the transactions occurring between 01/12/2010 and 09/12/2011 for a UK-based and registered non-store online retail.The company mainly sells unique all-occasion gifts. Many customers of the company are wholesalers."

Acknowledgements

Per the UCI Machine Learning Repository, this data was made available by Dr Daqing Chen, Director: Public Analytics group. chend '@' lsbu.ac.uk, School of Engineering, London South Bank University, London SE1 0AA, UK.

Image from stocksnap.io.

Inspiration

Analyses for this dataset could include time series, clustering, classification and more.

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