100+ datasets found
  1. Consumers that would shop mostly online vs. offline worldwide 2023, by...

    • statista.com
    Updated Jun 23, 2025
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    Statista (2025). Consumers that would shop mostly online vs. offline worldwide 2023, by country [Dataset]. https://www.statista.com/statistics/1384193/mostly-online-vs-offline-shopping-worldwide/
    Explore at:
    Dataset updated
    Jun 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 2023 - Mar 2023
    Area covered
    Worldwide
    Description

    As of early 2023, approximately ** percent of consumers in the United States said they would prefer to shop mostly online rather than in-store, making it the country with highest online shopping preference. In contrast, more shoppers preferred visiting physical stores in countries such as Austria, Finland, and New Zealand.

  2. 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.

  3. d

    Warehouse and Retail Sales

    • catalog.data.gov
    • data.montgomerycountymd.gov
    • +2more
    Updated Sep 7, 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
    Sep 7, 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

  4. 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/ECOMNSA
    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 (ECOMNSA) from Q4 1999 to Q2 2025 about e-commerce, retail trade, sales, retail, and USA.

  5. 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
    Lao People's Democratic Republic, Canada, Northern Mariana Islands, Austria, Korea (Democratic People's Republic of), Italy, Mexico, Malta, Fiji, Andorra
    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...
  6. c

    Clickstream for Online Shopping Dataset

    • cubig.ai
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    CUBIG, Clickstream for Online Shopping Dataset [Dataset]. https://cubig.ai/store/products/376/clickstream-for-online-shopping-dataset
    Explore at:
    Dataset authored and provided by
    CUBIG
    License

    https://cubig.ai/store/terms-of-servicehttps://cubig.ai/store/terms-of-service

    Measurement technique
    Synthetic data generation using AI techniques for model training, Privacy-preserving data transformation via differential privacy
    Description

    1) Data Introduction • The Clickstream Data for Online Shopping is an e-commerce analysis dataset that summarizes user clickstream, product information, country, price, and other session-specific behavior data from April to August 2008 at an online shopping mall specializing in maternity clothing.

    2) Data Utilization (1) Clickstream Data for Online Shopping has characteristics that: • Each row contains 14 key variables: year, month, day, click order, country (by access IP), session ID, main category, product code, color, photo location, model photo type, price, category average price, page number, etc. • Data is configured to enable analysis of various consumer behaviors such as click flows for each session, product attributes, and country-specific access patterns. (2) Clickstream Data for Online Shopping can be used to: • Online Shopping Mall User Behavior Analysis: Using clickstream, session, and product information, you can analyze purchase conversion routes, popular products, and behavioral patterns by country and category. • Improve marketing strategies and UI/UX: analyze the relationship between product photo location, color, price, etc. and click behavior and apply to establish effective marketing strategies and improvement of shopping mall UI/UX.

  7. Online Retail Store Dataset

    • kaggle.com
    Updated May 2, 2024
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    Ankush Kashyap (2024). Online Retail Store Dataset [Dataset]. https://www.kaggle.com/datasets/kashyapankush/online-retail-store-dataset
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    May 2, 2024
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Ankush Kashyap
    License

    Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
    License information was derived automatically

    Description

    Dataset

    This dataset was created by Ankush Kashyap

    Released under Apache 2.0

    Contents

  8. d

    Ecommerce Data | Store Location Data | Global Coverage | 60M+ Contacts |...

    • datarade.ai
    Updated Jan 24, 2024
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    Exellius Systems (2024). Ecommerce Data | Store Location Data | Global Coverage | 60M+ 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
    Explore at:
    .bin, .json, .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset updated
    Jan 24, 2024
    Dataset authored and provided by
    Exellius Systems
    Area covered
    Heard Island and McDonald Islands, Namibia, Jersey, Congo (Democratic Republic of the), Iran (Islamic Republic of), Lithuania, Spain, Seychelles, Saint Vincent and the Grenadines, Gabon
    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 confidence and insight.

  9. Global retail e-commerce sales 2022-2028

    • statista.com
    • abripper.com
    • +2more
    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/
    Explore at:
    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.

  10. Tata Online Retail Dataset

    • kaggle.com
    Updated Jun 12, 2024
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    MD. ROMAN TALUKDAR (2024). Tata Online Retail Dataset [Dataset]. http://doi.org/10.34740/kaggle/dsv/8677438
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jun 12, 2024
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    MD. ROMAN TALUKDAR
    License

    http://opendatacommons.org/licenses/dbcl/1.0/http://opendatacommons.org/licenses/dbcl/1.0/

    Description

    Dataset Description: Online Retail Dataset

    Overview:😊 The Online Retail dataset contains transactional data for a UK-based online retail company. The dataset includes details of orders made from various countries between 2010 and 2011. It is useful for exploring purchase behaviors, sales patterns, and customer segmentation.

    Attributes: InvoiceNo, StockCode, Description, Quantity, InvoiceDate, UnitPrice, CustomerID, Country

    Potential Uses:

    Sales Analysis:✅ Analyzing sales trends over time, identifying best-selling products, and understanding sales performance across different regions.

    Customer Segmentation:✅ Segmenting customers based on purchasing behavior, frequency, and monetary value to tailor marketing strategies.

    Inventory Management:✅ Monitoring stock levels and predicting future inventory needs based on sales patterns.

    Market Basket Analysis:✅ Identifying products that are frequently bought together to improve cross-selling strategies. 🎯

    License:

    Please specify the appropriate license (e.g., Apache 2.0 or MIT) when uploading the dataset to ensure clear usage guidelines for other users.

  11. T

    US Retail Sales

    • tradingeconomics.com
    • zh.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Aug 15, 2025
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    TRADING ECONOMICS (2025). US Retail Sales [Dataset]. https://tradingeconomics.com/united-states/retail-sales
    Explore at:
    csv, xml, excel, jsonAvailable download formats
    Dataset updated
    Aug 15, 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 - Aug 31, 2025
    Area covered
    United States
    Description

    Retail Sales in the United States increased 0.60 percent in August 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.

  12. Data from: Online Retail Store

    • kaggle.com
    Updated Jul 24, 2023
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    Shubham_Gupta012 (2023). Online Retail Store [Dataset]. https://www.kaggle.com/datasets/shubhamgupta012/online-retail-store/code
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jul 24, 2023
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Shubham_Gupta012
    Description

    Dataset

    This dataset was created by Shubham_Gupta012

    Contents

  13. Data from: Online Retail

    • kaggle.com
    Updated Jul 29, 2024
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    Deepak VD (2024). Online Retail [Dataset]. https://www.kaggle.com/datasets/deepakvd/online-retail
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jul 29, 2024
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Deepak VD
    License

    Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
    License information was derived automatically

    Description

    Dataset

    This dataset was created by Deepak VD

    Released under Apache 2.0

    Contents

  14. c

    E Commerce Dataset

    • cubig.ai
    Updated May 25, 2025
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    CUBIG (2025). E Commerce Dataset [Dataset]. https://cubig.ai/store/products/277/e-commerce-dataset
    Explore at:
    Dataset updated
    May 25, 2025
    Dataset authored and provided by
    CUBIG
    License

    https://cubig.ai/store/terms-of-servicehttps://cubig.ai/store/terms-of-service

    Measurement technique
    Synthetic data generation using AI techniques for model training, Privacy-preserving data transformation via differential privacy
    Description

    1) Data Introduction • The E-Commerce Data Dataset contains actual transaction records from an online retail company based in the UK. It includes various transaction-related attributes such as customer ID, product information, transaction date, quantity, and country.

    2) Data Utilization (1) Characteristics of the E-Commerce Data Dataset: • This dataset is structured as time-series consumer behavior data at the transaction level. It includes attributes such as product category, quantity, unit price, and country, making it suitable for analyzing country-specific consumption patterns and developing region-based classification models.

    (2) Applications of the E-Commerce Data Dataset: • Developing country-specific marketing strategies: By analyzing purchasing trends, frequently bought product categories, and transaction frequency by country, the dataset can be used to design regionally tailored marketing strategies.

  15. 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
    Cyprus, Hong Kong, Singapore, Bangladesh, Georgia, Kuwait, Jordan, Malaysia, Lebanon, Turkmenistan
    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.

    ...

  16. 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.

  17. Large Target store products dataset

    • crawlfeeds.com
    csv, zip
    Updated Jan 6, 2025
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    Crawl Feeds (2025). Large Target store products dataset [Dataset]. https://crawlfeeds.com/datasets/large-target-store-products-dataset
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    zip, csvAvailable download formats
    Dataset updated
    Jan 6, 2025
    Dataset authored and provided by
    Crawl Feeds
    License

    https://crawlfeeds.com/privacy_policyhttps://crawlfeeds.com/privacy_policy

    Description

    Access the Large Target Store Products Dataset, a detailed collection of web-scraped data featuring a wide range of retail products. Discover trending categories, including groceries, home goods, electronics, clothing, beauty products, and more. Gain insights into product availability, pricing, customer ratings, and brand preferences from one of the leading retailers.

    Perfect for market analysis, competitive research, and consumer behavior studies, this dataset offers valuable information to inform retail strategies and decision-making.

  18. Retail Sales Index internet sales

    • ons.gov.uk
    • cy.ons.gov.uk
    xlsx
    Updated Sep 19, 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
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    xlsxAvailable download formats
    Dataset updated
    Sep 19, 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.

  19. Retail Data | Retail Sector in North America | Comprehensive Contact...

    • datarade.ai
    + more versions
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    Success.ai, Retail Data | Retail Sector in North America | Comprehensive Contact Profiles | Best Price Guaranteed [Dataset]. https://datarade.ai/data-products/retail-data-retail-sector-in-north-america-comprehensive-success-ai
    Explore at:
    .bin, .json, .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset provided by
    Area covered
    United States
    Description

    Success.ai’s Retail Data for the Retail Sector in North America offers a comprehensive dataset designed to connect businesses with key players across the diverse retail industry. Covering everything from department stores and supermarkets to specialty shops and e-commerce platforms, this dataset provides verified contact details, business locations, and leadership profiles for retail companies in the United States, Canada, and Mexico.

    With access to over 170 million verified professional profiles and 30 million company profiles, Success.ai ensures your outreach, marketing, and business development efforts are powered by accurate, continuously updated, and AI-validated data.

    Backed by our Best Price Guarantee, this solution empowers businesses to thrive in North America’s competitive retail landscape.

    Why Choose Success.ai’s Retail Data for North America?

    1. Verified Contact Data for Precision Outreach

      • Access verified phone numbers, work emails, and LinkedIn profiles of retail executives, store managers, and decision-makers.
      • AI-driven validation ensures 99% accuracy, enabling confident communication and efficient campaign execution.
    2. Comprehensive Coverage Across Retail Segments

      • Includes profiles of retail businesses across major markets, from large department stores and grocery chains to boutique retailers and online platforms.
      • Gain insights into the operational dynamics of retail hubs in cities such as New York, Los Angeles, Toronto, and Mexico City.
    3. Continuously Updated Datasets

      • Real-time updates reflect leadership changes, new store openings, market expansions, and shifts in consumer preferences.
      • Stay aligned with evolving industry trends and emerging opportunities in the North American retail sector.
    4. Ethical and Compliant

      • Adheres to GDPR, CCPA, and other privacy regulations, ensuring responsible and lawful use of data in your campaigns.

    Data Highlights:

    • 170M+ Verified Professional Profiles: Engage with executives, marketing directors, and operations managers across the North American retail sector.
    • 30M Company Profiles: Access firmographic data, including revenue ranges, store counts, and geographic footprints.
    • Store Location Data: Pinpoint retail outlets, regional offices, and distribution centers to refine supply chain and marketing strategies.
    • Leadership Contact Details: Connect with CEOs, CMOs, and procurement officers influencing retail operations and vendor selections.

    Key Features of the Dataset:

    1. Retail Decision-Maker Profiles

      • Identify and engage with store owners, category managers, and marketing directors shaping customer experiences and product strategies.
      • Target professionals responsible for inventory planning, vendor contracts, and store performance.
    2. Advanced Filters for Precision Targeting

      • Filter companies by industry segment (luxury, grocery, e-commerce), geographic location, company size, or revenue range.
      • Tailor outreach to align with regional market trends, customer demographics, and operational priorities.
    3. Market Trends and Operational Insights

      • Analyze trends such as online shopping growth, sustainability practices, and supply chain optimization.
      • Leverage insights to refine product offerings, identify partnership opportunities, and design effective campaigns.
    4. AI-Driven Enrichment

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

    Strategic Use Cases:

    1. Sales and Lead Generation

      • Present products, services, or technology solutions to retail procurement teams, marketing departments, and operations managers.
      • Build relationships with retailers seeking innovative tools, efficient supply chain solutions, or unique product offerings.
    2. Market Research and Consumer Insights

      • Analyze retail trends, customer behaviors, and seasonal demands to inform marketing strategies and product launches.
      • Benchmark against competitors to identify gaps, emerging niches, and growth opportunities.
    3. E-Commerce and Digital Strategy Development

      • Target e-commerce managers and digital transformation teams driving online retail initiatives and omnichannel integration.
      • Offer solutions to enhance online shopping experiences, logistics, and customer loyalty programs.
    4. Recruitment and Workforce Solutions

      • Engage HR professionals and hiring managers in recruiting talent for store operations, customer service, or marketing roles.
      • Provide workforce optimization tools, training platforms, or staffing services tailored to retail environments.

    Why Choose Success.ai?

    1. Best Price Guarantee

      • Access premium-quality retail data at competitive prices, ensuring strong ROI for your marketing and outreach efforts in North America.
    2. Seamless Integration
      ...

  20. Data from: Online retail

    • kaggle.com
    Updated May 31, 2024
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    Nghiem Quang Minh (2024). Online retail [Dataset]. https://www.kaggle.com/datasets/nghiemquangminh/online-retail/suggestions
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    May 31, 2024
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Nghiem Quang Minh
    License

    Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
    License information was derived automatically

    Description

    Dataset

    This dataset was created by Nghiem Quang Minh

    Released under Apache 2.0

    Contents

Share
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Statista (2025). Consumers that would shop mostly online vs. offline worldwide 2023, by country [Dataset]. https://www.statista.com/statistics/1384193/mostly-online-vs-offline-shopping-worldwide/
Organization logo

Consumers that would shop mostly online vs. offline worldwide 2023, by country

Explore at:
4 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Jun 23, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
Jan 2023 - Mar 2023
Area covered
Worldwide
Description

As of early 2023, approximately ** percent of consumers in the United States said they would prefer to shop mostly online rather than in-store, making it the country with highest online shopping preference. In contrast, more shoppers preferred visiting physical stores in countries such as Austria, Finland, and New Zealand.

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