100+ datasets found
  1. y

    US Retail Sales

    • ycharts.com
    html
    Updated Sep 16, 2025
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    Census Bureau (2025). US Retail Sales [Dataset]. https://ycharts.com/indicators/us_retail_sales
    Explore at:
    htmlAvailable download formats
    Dataset updated
    Sep 16, 2025
    Dataset provided by
    YCharts
    Authors
    Census Bureau
    License

    https://www.ycharts.com/termshttps://www.ycharts.com/terms

    Time period covered
    Jan 31, 1992 - Aug 31, 2025
    Area covered
    United States
    Variables measured
    US Retail Sales
    Description

    View monthly updates and historical trends for US Retail Sales. from United States. Source: Census Bureau. Track economic data with YCharts analytics.

  2. World: retail sales 2021-2026

    • statista.com
    • tokrwards.com
    • +2more
    Updated Jun 24, 2025
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    Statista (2025). World: retail sales 2021-2026 [Dataset]. https://www.statista.com/statistics/443522/global-retail-sales/
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    Dataset updated
    Jun 24, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Dec 2022
    Area covered
    Worldwide
    Description

    Global retail sales were projected to amount to around **** trillion U.S. dollars by 2026, up from approximately **** trillion U.S. dollars in 2021. The retail industry encompasses the journey of a good or service. This typically starts with the manufacturing of a product and ends with said product being purchased by a consumer from a retailer. Retail establishments come in many forms such as grocery stores, restaurants, and bookstores. American retailers worldwide As a result of globalization and various trade agreements between markets and countries, many retailers are capable of doing business on a global scale. Many of the world’s leading retailers are American companies. Walmart and Amazon are examples of such American retailers. The success of U.S. retailers can also be seen through their performance in online retail. Retail in the U.S. The domestic retail market in the United States is a lucrative market, in which many companies compete. Walmart, a retail chain offering low prices and a wide selection of products, is the leading retailer in the United States. Amazon, The Kroger Co., Costco, and Target are a selection of other leading U.S. retailers.

  3. d

    Retail Food Stores

    • catalog.data.gov
    • data.buffalony.gov
    • +4more
    Updated Oct 4, 2025
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    data.ny.gov (2025). Retail Food Stores [Dataset]. https://catalog.data.gov/dataset/retail-food-stores
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    Dataset updated
    Oct 4, 2025
    Dataset provided by
    data.ny.gov
    Description

    A listing of all retail food stores which are licensed by the Department of Agriculture and Markets.

  4. Data usage in consumer products and retail industry 2020

    • statista.com
    Updated Jun 26, 2025
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    Statista (2025). Data usage in consumer products and retail industry 2020 [Dataset]. https://www.statista.com/statistics/1262066/data-usage-in-consumer-products-and-retail-industry/
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    Dataset updated
    Jun 26, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Aug 2020
    Area covered
    Worldwide
    Description

    A global survey from Capgemini showed that retail companies were lagging behind consumer products enterprises in the use of data. The gap was significant in the automation of processes and in data collecting: only ** percent of retailers automated data collection, against ** percent of consumer goods companies. However, one in **** organizations in both categories reported to have implemented practices involving data engineering, machine learning, and DevOps.

  5. 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
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    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.

  6. x

    Retail Store Location Data | Retail Location Data | Xtract.io

    • xtract.io
    Updated Nov 4, 2022
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    Xtract.io Technology Solutions (2022). Retail Store Location Data | Retail Location Data | Xtract.io [Dataset]. https://www.xtract.io/cmp/poidata/retail
    Explore at:
    Dataset updated
    Nov 4, 2022
    Dataset provided by
    Xtract.Io Technology Solutions Private Limited
    Authors
    Xtract.io Technology Solutions
    License

    https://www.xtract.io/privacy-policyhttps://www.xtract.io/privacy-policy

    Area covered
    United States
    Description

    This core point of interest dataset consists of 1M location information of retail stores in the US and Canada. The POI database includes electronic stores, supermarkets and groceries, specialty retailers, home improvement and convenience stores, and apparel and accessories shops.

  7. E-commerce as share of total retail sales worldwide 2017-2030

    • statista.com
    • abripper.com
    • +3more
    Updated Sep 2, 2025
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    Statista (2025). E-commerce as share of total retail sales worldwide 2017-2030 [Dataset]. https://www.statista.com/statistics/534123/e-commerce-share-of-retail-sales-worldwide/
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    Dataset updated
    Sep 2, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    Internet sales have played an increasingly significant role in retailing. In 2025, e-commerce accounted for over ***percent of retail sales worldwide. Forecasts indicate that by 2030, the online segment will make up ***percent of total global retail sales. Retail e-commerce Online shopping has grown steadily in popularity in recent years. In 2024, global e-commerce sales amounted to over ************ U.S. dollars, a figure expected to approach * trillion U.S. dollars by 2030. Digital development boomed during the COVID-19 pandemic, generating unprecedented e-commerce growth in various economies across the globe. This trend correlates strongly with the constantly improving online access, especially in "mobile-first" online communities, which have long struggled with traditional commercial fixed broadband connections due to financial or infrastructure constraints but enjoy the advantages of cheap mobile broadband connections. M-commerce on the rise The order share of online shopping via smartphones and tablets now outperforms traditional e-commerce via desktop computers. As such, e-retailers around the world have caught up in mobile e-commerce sales. Online shopping via smartphones is particularly prominent in Asia. By the end of 2023, South Korea was the top digital market based on the percentage of the population that had purchased something by phone, with nearly ** percent having made a weekly mobile purchase. Malaysia, UAE, and Turkey completed the top of the ranking.

  8. F

    Sales by Retail Stores for United States

    • fred.stlouisfed.org
    json
    Updated Aug 17, 2012
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    (2012). Sales by Retail Stores for United States [Dataset]. https://fred.stlouisfed.org/series/M0689BUSM144NNBR
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Aug 17, 2012
    License

    https://fred.stlouisfed.org/legal/#copyright-citation-requiredhttps://fred.stlouisfed.org/legal/#copyright-citation-required

    Area covered
    United States
    Description

    Graph and download economic data for Sales by Retail Stores for United States (M0689BUSM144NNBR) from Jan 1946 to Sep 1974 about retail trade, sales, retail, and USA.

  9. Retail Sales Dataset

    • kaggle.com
    Updated Aug 22, 2023
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    Mohammad Talib (2023). Retail Sales Dataset [Dataset]. https://www.kaggle.com/datasets/mohammadtalib786/retail-sales-dataset/data
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Aug 22, 2023
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Mohammad Talib
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    Welcome to the Retail Sales and Customer Demographics Dataset! This synthetic dataset has been meticulously crafted to simulate a dynamic retail environment, providing an ideal playground for those eager to sharpen their data analysis skills through exploratory data analysis (EDA). With a focus on retail sales and customer characteristics, this dataset invites you to unravel intricate patterns, draw insights, and gain a deeper understanding of customer behavior.

    ****Dataset Overview:**

    This dataset is a snapshot of a fictional retail landscape, capturing essential attributes that drive retail operations and customer interactions. It includes key details such as Transaction ID, Date, Customer ID, Gender, Age, Product Category, Quantity, Price per Unit, and Total Amount. These attributes enable a multifaceted exploration of sales trends, demographic influences, and purchasing behaviors.

    Why Explore This Dataset?

    • Realistic Representation: Though synthetic, the dataset mirrors real-world retail scenarios, allowing you to practice analysis within a familiar context.
    • Diverse Insights: From demographic insights to product preferences, the dataset offers a broad spectrum of factors to investigate.
    • Hypothesis Generation: As you perform EDA, you'll have the chance to formulate hypotheses that can guide further analysis and experimentation.
    • Applied Learning: Uncover actionable insights that retailers could use to enhance their strategies and customer experiences.

    Questions to Explore:

    • How does customer age and gender influence their purchasing behavior?
    • Are there discernible patterns in sales across different time periods?
    • Which product categories hold the highest appeal among customers?
    • What are the relationships between age, spending, and product preferences?
    • How do customers adapt their shopping habits during seasonal trends?
    • Are there distinct purchasing behaviors based on the number of items bought per transaction?
    • What insights can be gleaned from the distribution of product prices within each category?

    Your EDA Journey:

    Prepare to immerse yourself in a world of data-driven exploration. Through data visualization, statistical analysis, and correlation examination, you'll uncover the nuances that define retail operations and customer dynamics. EDA isn't just about numbers—it's about storytelling with data and extracting meaningful insights that can influence strategic decisions.

    Embrace the Retail Sales and Customer Demographics Dataset as your canvas for discovery. As you traverse the landscape of this synthetic retail environment, you'll refine your analytical skills, pose intriguing questions, and contribute to the ever-evolving narrative of the retail industry. Happy exploring!

  10. Retail trade sales by industry, inactive (x 1,000)

    • www150.statcan.gc.ca
    Updated Feb 21, 2023
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    Government of Canada, Statistics Canada (2023). Retail trade sales by industry, inactive (x 1,000) [Dataset]. http://doi.org/10.25318/2010000801-eng
    Explore at:
    Dataset updated
    Feb 21, 2023
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    Area covered
    Canada
    Description

    Retail Trade, sales by industries based on North American Industry Classification System (NAICS), monthly.

  11. Big Data Analytics in Retail Market - Trends & Industry Analysis

    • mordorintelligence.com
    pdf,excel,csv,ppt
    Updated Dec 11, 2024
    + more versions
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    Mordor Intelligence (2024). Big Data Analytics in Retail Market - Trends & Industry Analysis [Dataset]. https://www.mordorintelligence.com/industry-reports/big-data-analytics-in-retail-marketing-market
    Explore at:
    pdf,excel,csv,pptAvailable download formats
    Dataset updated
    Dec 11, 2024
    Dataset provided by
    Authors
    Mordor Intelligence
    License

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

    Time period covered
    2021 - 2030
    Area covered
    Global
    Description

    The Data Analytics in Retail Industry is segmented by Application (Merchandising and Supply Chain Analytics, Social Media Analytics, Customer Analytics, Operational Intelligence, Other Applications), by Business Type (Small and Medium Enterprises, Large-scale Organizations), and Geography. The market size and forecasts are provided in terms of value (USD billion) for all the above segments.

  12. y

    US E-Commerce Sales as Percent of Retail Sales

    • ycharts.com
    html
    Updated Aug 19, 2025
    + more versions
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    Census Bureau (2025). US E-Commerce Sales as Percent of Retail Sales [Dataset]. https://ycharts.com/indicators/us_ecommerce_sales_as_percent_retail_sales
    Explore at:
    htmlAvailable download formats
    Dataset updated
    Aug 19, 2025
    Dataset provided by
    YCharts
    Authors
    Census Bureau
    License

    https://www.ycharts.com/termshttps://www.ycharts.com/terms

    Time period covered
    Dec 31, 1999 - Jun 30, 2025
    Area covered
    United States
    Variables measured
    US E-Commerce Sales as Percent of Retail Sales
    Description

    View quarterly updates and historical trends for US E-Commerce Sales as Percent of Retail Sales. from United States. Source: Census Bureau. Track economic…

  13. U

    United States Retail Sales Growth

    • ceicdata.com
    Updated Feb 15, 2020
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    CEICdata.com (2020). United States Retail Sales Growth [Dataset]. https://www.ceicdata.com/en/indicator/united-states/retail-sales-growth
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    Dataset updated
    Feb 15, 2020
    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
    Jun 1, 2022 - May 1, 2023
    Area covered
    United States
    Description

    Key information about United States Retail Sales Growth

    • United States Retail Sales grew 1.0 % YoY in May 2023, compared with a 1.6 % increase in the previous month.
    • US Retail Sales Growth YoY data is updated monthly, available from Jan 1993 to May 2023, with an average growth rate of 4.7 %.
    • The data reached an all-time high of 42.0 % in Apr 2021 and a record low of -15.8 % in Apr 2020.
    • In the latest reports, Car Sales of US recorded 1,407,152.0 units in May 2023, representing a growth of 22.8 %.

    CEIC calculates monthly Retail Sales: Excl. Motor Vehicles Growth from monthly Retail Sales excluding Motor Vehicle and Parts. The U.S. Census Bureau provides Retail Sales excluding Motor Vehicle and Parts in USD. Retail Sales include Food Services.

  14. F

    Retailers Sales

    • fred.stlouisfed.org
    json
    Updated Sep 16, 2025
    + more versions
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    (2025). Retailers Sales [Dataset]. https://fred.stlouisfed.org/series/RETAILSMSA
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Sep 16, 2025
    License

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

    Description

    Graph and download economic data for Retailers Sales (RETAILSMSA) from Jan 1992 to Jul 2025 about retail trade, sales, retail, and USA.

  15. G

    Retail store financial estimates, inactive

    • ouvert.canada.ca
    • www150.statcan.gc.ca
    • +2more
    csv, html, xml
    Updated Jan 17, 2023
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    Statistics Canada (2023). Retail store financial estimates, inactive [Dataset]. https://ouvert.canada.ca/data/dataset/7b56980f-1ea0-4c9f-bdf5-1970576753b9
    Explore at:
    csv, html, xmlAvailable download formats
    Dataset updated
    Jan 17, 2023
    Dataset provided by
    Statistics Canada
    License

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

    Description

    Estimates of financial variables for store retailers, by type of store, based on the North American Industry Classification System (NAICS), annual.

  16. Grocery Data | Food Data | Food & Grocery Data | Industry Data | Grocery POI...

    • datarade.ai
    Updated Jan 29, 2025
    + more versions
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    MealMe (2025). Grocery Data | Food Data | Food & Grocery Data | Industry Data | Grocery POI and SKU Level Product Data from 1M+ Locations with Prices [Dataset]. https://datarade.ai/data-products/grocery-data-food-data-food-grocery-data-industry-dat-mealme
    Explore at:
    .bin, .json, .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset updated
    Jan 29, 2025
    Dataset provided by
    MealMe, Inc.
    Authors
    MealMe
    Area covered
    Sao Tome and Principe, Lesotho, Honduras, Belarus, Chile, Kiribati, French Polynesia, India, Tonga, Tajikistan
    Description

    MealMe provides comprehensive grocery and retail SKU-level product data, including real-time pricing, from the top 100 retailers in the USA and Canada. Our proprietary technology ensures accurate and up-to-date insights, empowering businesses to excel in competitive intelligence, pricing strategies, and market analysis.

    Retailers Covered: MealMe’s database includes detailed SKU-level data and pricing from leading grocery and retail chains such as Walmart, Target, Costco, Kroger, Safeway, Publix, Whole Foods, Aldi, ShopRite, BJ’s Wholesale Club, Sprouts Farmers Market, Albertsons, Ralphs, Pavilions, Gelson’s, Vons, Shaw’s, Metro, and many more. Our coverage spans the most influential retailers across North America, ensuring businesses have the insights needed to stay competitive in dynamic markets.

    Key Features: SKU-Level Granularity: Access detailed product-level data, including product descriptions, categories, brands, and variations. Real-Time Pricing: Monitor current pricing trends across major retailers for comprehensive market comparisons. Regional Insights: Analyze geographic price variations and inventory availability to identify trends and opportunities. Customizable Solutions: Tailored data delivery options to meet the specific needs of your business or industry. Use Cases: Competitive Intelligence: Gain visibility into pricing, product availability, and assortment strategies of top retailers like Walmart, Costco, and Target. Pricing Optimization: Use real-time data to create dynamic pricing models that respond to market conditions. Market Research: Identify trends, gaps, and consumer preferences by analyzing SKU-level data across leading retailers. Inventory Management: Streamline operations with accurate, real-time inventory availability. Retail Execution: Ensure on-shelf product availability and compliance with merchandising strategies. Industries Benefiting from Our Data CPG (Consumer Packaged Goods): Optimize product positioning, pricing, and distribution strategies. E-commerce Platforms: Enhance online catalogs with precise pricing and inventory information. Market Research Firms: Conduct detailed analyses to uncover industry trends and opportunities. Retailers: Benchmark against competitors like Kroger and Aldi to refine assortments and pricing. AI & Analytics Companies: Fuel predictive models and business intelligence with reliable SKU-level data. Data Delivery and Integration MealMe offers flexible integration options, including APIs and custom data exports, for seamless access to real-time data. Whether you need large-scale analysis or continuous updates, our solutions scale with your business needs.

    Why Choose MealMe? Comprehensive Coverage: Data from the top 100 grocery and retail chains in North America, including Walmart, Target, and Costco. Real-Time Accuracy: Up-to-date pricing and product information ensures competitive edge. Customizable Insights: Tailored datasets align with your specific business objectives. Proven Expertise: Trusted by diverse industries for delivering actionable insights. MealMe empowers businesses to unlock their full potential with real-time, high-quality grocery and retail data. For more information or to schedule a demo, contact us today!

  17. Annual retail store survey, financial estimates by store type and trade...

    • www150.statcan.gc.ca
    • datasets.ai
    • +3more
    Updated Mar 13, 2017
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    Government of Canada, Statistics Canada (2017). Annual retail store survey, financial estimates by store type and trade group based on the North American Industry Classification System (NAICS), inactive [Dataset]. http://doi.org/10.25318/2010003501-eng
    Explore at:
    Dataset updated
    Mar 13, 2017
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    Area covered
    Canada
    Description

    This table contains 9702 series, with data for years 1999 - 2009 (not all combinations necessarily have data for all years), and was last released on 2012-03-28. This table contains data described by the following dimensions (Not all combinations are available): Geography (14 items: Canada;Nova Scotia;Prince Edward Island;Newfoundland and Labrador ...), Trade group (21 items: Total; all trade groups;New car dealers;Used and recreational motor vehicle and parts dealers;Furniture stores ...), Financial estimates (11 items: Sales of goods for resale;Total revenue;Opening inventory;Total operating revenue ...), Type of store (3 items: Total all stores;Chain stores;Non-chain stores ...).

  18. d

    CPG Data | Retail Store Location Data | 75M+ POI | SafeGraph Places

    • datarade.ai
    .csv
    Updated Jun 25, 2024
    + more versions
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    SafeGraph (2024). CPG Data | Retail Store Location Data | 75M+ POI | SafeGraph Places [Dataset]. https://datarade.ai/data-products/cpg-data-retail-store-location-data-52m-poi-safegraph-safegraph
    Explore at:
    .csvAvailable download formats
    Dataset updated
    Jun 25, 2024
    Dataset authored and provided by
    SafeGraph
    Area covered
    China, Ghana, Saint Helena, Svalbard and Jan Mayen, Turkey, Qatar, Korea (Republic of), Sint Eustatius and Saba, Guadeloupe, Angola
    Description

    SafeGraph Places provides baseline location information for every record in the SafeGraph product suite via the Places schema and polygon information when applicable via the Geometry schema. The current scope of a place is defined as any location humans can visit with the exception of single-family homes. This definition encompasses a diverse set of places ranging from restaurants, grocery stores, and malls; to parks, hospitals, museums, offices, and industrial parks. Premium sets of Places include apartment buildings, Parking Lots, and Point POIs (such as ATMs or transit stations).

    SafeGraph Places is a point of interest (POI) data offering with varying coverage depending on the country. Note that address conventions and formatting vary across countries. SafeGraph has coalesced these fields into the Places schema.

  19. s

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

    • data.success.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://data.success.ai/products/retail-store-data-retail-e-commerce-sector-in-asia-veri-success-ai
    Explore at:
    Dataset updated
    Feb 12, 2018
    Dataset provided by
    Success.ai
    Area covered
    Asia, Japan, Afghanistan, Lebanon, Yemen, Maldives, Lao People's Democratic Republic, Hong Kong, Israel, Palestine, Nepal
    Description

    Discover Retail Store Data for Asia’s retail and e-commerce industries. Includes verified contact data, business histories, and market insights from 70M+ businesses. Best price guaranteed.

  20. Retail Data | Retail Sector in Asia | Verified Business Profiles & Insights...

    • datarade.ai
    + more versions
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    Success.ai, Retail Data | Retail Sector in Asia | Verified Business Profiles & Insights | Best Price Guaranteed [Dataset]. https://datarade.ai/data-products/retail-data-retail-sector-in-asia-verified-business-profi-success-ai
    Explore at:
    .bin, .json, .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset provided by
    Area covered
    Myanmar, India, Lao People's Democratic Republic, State of, Cambodia, Indonesia, Saudi Arabia, Turkmenistan, Qatar, Uzbekistan, Asia
    Description

    Success.ai’s Retail Data for the Retail Sector in Asia enables businesses to navigate dynamic consumer markets, evolving retail landscapes, and rapidly changing consumer behavior across the region. Leveraging over 170 million verified professional profiles and 30 million company profiles, this dataset delivers comprehensive firmographic details, verified contact information, and decision-maker insights for retailers ranging from boutique shops and e-commerce platforms to large department store chains and multinational franchises.

    Whether you’re launching new products, entering emerging markets, or optimizing supply chain strategies, Success.ai’s continuously updated and AI-validated data ensures you engage the right stakeholders at the right time, all backed by our Best Price Guarantee.

    Why Choose Success.ai’s Retail Data in Asia?

    1. Comprehensive Company Information

      • Access verified work emails, phone numbers, and LinkedIn profiles of retail decision-makers, buyers, and merchandising managers across Asia.
      • AI-driven validation ensures 99% accuracy, enabling confident communication and minimizing wasted outreach efforts.
    2. Regional Focus on Asian Markets

      • Includes profiles of small specialty retailers, large department stores, convenience chains, online marketplaces, and luxury brands spanning regions like East Asia, Southeast Asia, and South Asia.
      • Understand region-specific consumer preferences, product trends, and competitive dynamics to guide targeted campaigns and market entries.
    3. Continuously Updated Datasets

      • Real-time updates reflect leadership changes, store expansions, new franchise agreements, and shifts in inventory sourcing.
      • Stay aligned with evolving market conditions, shopper behaviors, and regulatory environments impacting the Asian retail sector.
    4. Ethical and Compliant

      • Adheres to GDPR, CCPA, and global privacy regulations, ensuring that your data usage remains compliant and your outreach respects personal boundaries.

    Data Highlights:

    • 170M+ Verified Professional Profiles: Engage with executives, buyers, store managers, and e-commerce directors shaping retail landscapes in Asia.
    • 30M Company Profiles: Gain insights into brand portfolios, store counts, revenue ranges, and distribution networks.
    • Firmographic & Demographic Data: Understand retail categories, merchandising strategies, supply chain partners, and consumer demographics influencing local markets.
    • Verified Decision-Maker Contacts: Connect directly with key stakeholders responsible for purchasing decisions, vendor selection, category management, and brand partnerships.

    Key Features of the Dataset:

    1. Retail Decision-Maker Profiles
      • Identify and connect with CEOs, CFOs, category buyers, inventory planners, marketing directors, and store operations leaders.
    2. Target professionals who determine product assortments, vendor negotiations, store layouts, pricing strategies, and promotional campaigns.

    3. Advanced Filters for Precision Targeting

      • Filter by retail segment (fashion, electronics, groceries, cosmetics), country of operation, store format, or omnichannel strategies.
      • Tailor campaigns to align with unique cultural preferences, local consumer spending habits, and regulatory frameworks.
    4. AI-Driven Enrichment

      • Profiles are enriched with actionable data, enabling personalized messaging, highlighting market-entry value propositions, and improving engagement outcomes in diverse Asian markets.

    Strategic Use Cases:

    1. Market Entry & Expansion

      • Identify suitable partners, franchisees, or distribution channels when entering new Asian markets.
      • Benchmark against established players, adapt offerings to local tastes, and secure placements in prime retail locations.
    2. Supplier and Vendor Relations

    3. Connect with procurement managers and inventory planners evaluating new suppliers or seeking innovative products.

    4. Present packaging solutions, POS technology, or loyalty programs to retailers aiming to enhance the shopping experience.

    5. Omnichannel and E-Commerce Growth

      • Engage e-commerce managers and digital marketing teams embracing online retail, click-and-collect services, and mobile payment integrations.
      • Align technology solutions with growing demand for contactless shopping, personalized recommendations, and seamless customer journeys.
    6. Seasonal and Cultural Campaigns

      • Leverage local holidays, shopping festivals, and cultural events by reaching marketing directors and store managers who coordinate merchandise rotations, promotional deals, and experiential activations.
      • Adapt messaging to align with regional festivities and peak shopping periods.

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Census Bureau (2025). US Retail Sales [Dataset]. https://ycharts.com/indicators/us_retail_sales

US Retail Sales

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htmlAvailable download formats
Dataset updated
Sep 16, 2025
Dataset provided by
YCharts
Authors
Census Bureau
License

https://www.ycharts.com/termshttps://www.ycharts.com/terms

Time period covered
Jan 31, 1992 - Aug 31, 2025
Area covered
United States
Variables measured
US Retail Sales
Description

View monthly updates and historical trends for US Retail Sales. from United States. Source: Census Bureau. Track economic data with YCharts analytics.

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