100+ datasets found
  1. m

    Big Data Analytics in Retail Market - Trends & Industry Analysis

    • mordorintelligence.com
    pdf,excel,csv,ppt
    Updated Dec 11, 2024
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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 authored and provided by
    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.

  2. Retail Trade in the US - Market Research Report (2015-2030)

    • ibisworld.com
    Updated Sep 15, 2025
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    IBISWorld (2025). Retail Trade in the US - Market Research Report (2015-2030) [Dataset]. https://www.ibisworld.com/united-states/market-research-reports/retail-trade-industry/
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    Dataset updated
    Sep 15, 2025
    Dataset authored and provided by
    IBISWorld
    License

    https://www.ibisworld.com/about/termsofuse/https://www.ibisworld.com/about/termsofuse/

    Time period covered
    2015 - 2030
    Area covered
    United States
    Description

    The Retail Trade sector entered 2025 on a muted footing, with revenue growth of just 0.2% to reach $7.4 trillion. E-commerce remains a bright spot, with steady mid-single-digit gains in recent years, boosted by younger consumers' strong preference for digital channels. Yet, the sector's gains in digital shopping are balanced by ongoing challenges in discretionary spending, high operating costs and tariffs that threaten earnings. Profit has been pressured by steep price competition online and inflation-related expenses, though essential retailers in sub-sectors like food and health have managed steadier performance. Current efforts around omnichannel strategies, technology-driven efficiencies and sustainability reflect the sector's dual focus: capturing digital momentum while offsetting erosion in traditional store-based sales. Over the current period, the sector's revenue expanded at a modest CAGR of 2.2%, highlighting how the pandemic's volatility gave way to cautious but relatively stable expansion. Revenue streams benefited from major operations like Target, Walmart and Amazon reshaping retail into one-stop ecosystems that blend products and services, diversifying into groceries, healthcare, beauty and wellness. Automation adoption--from self-checkout kiosks to advanced inventory management--helped mitigate rising wage costs and sharpened efficiency, while marketing automation improved customer engagement through more tailored promotions. Still, profit took hits from inflation, heightened competition and consumers trading down to value alternatives amid tightening budgets. Consumer priorities for sustainability have altered market dynamics, leading to investments in resale programs and greener programs. The sector's growth is expected to slow, with revenue climbing at an anticipated 1.3% CAGR through 2030, reaching $7.9 trillion. While consumer disposable income is set to strengthen modestly, fragile sentiment from inflation, tariffs and labor market uncertainty may temper spending power. Technology will be a key driver in reshaping operations and growth opportunities. AI is poised to enhance inventory control, price optimization, delivery logistics and fraud prevention. Extended reality innovations, from AR try-ons to immersive VR shopping, will engage younger consumers and potentially redefine customer experiences, though costs and adoption hurdles remain. Reverse logistics and the circular economy will gain ground as sustainability priorities align with value-seeking behavior. Discounters and warehouse clubs are expected to capture share in the near term as households continue trading down, though specialty and discretionary retail could stage a rebound later in the outlook period as consumer confidence improves.

  3. FRED: U.S. Advance Retail Sales Dataset

    • kaggle.com
    Updated Sep 8, 2025
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    Swati Hegde (2025). FRED: U.S. Advance Retail Sales Dataset [Dataset]. https://www.kaggle.com/datasets/swatih/fred-u-s-advance-retail-sales-dataset
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Sep 8, 2025
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Swati Hegde
    Area covered
    United States
    Description

    This dataset, identified by the series ID RSXFS, is sourced from the U.S. Census Bureau and is available through the Federal Reserve Economic Data (FRED) system of the St. Louis Fed. It provides a monthly measure of retail sales across the United States. The data represents the total value of sales at retail and food services stores, measured in millions of dollars and adjusted for seasonal variations. It is important to note that the most recent month's value is an advance estimate, which is subject to revision in subsequent months as more comprehensive data becomes available. As a key economic indicator, this series is widely used by economists and analysts to gauge consumer spending and assess the overall health of the U.S. economy.

    Suggested Use Cases: - This dataset is highly valuable for economic analysis and can be used to: - Conduct time series analysis and modeling. - Track consumer spending patterns. - Forecast future retail sales. - Analyze the impact of economic events on the retail sector.

    License The RSXFS dataset is sourced from the U.S. Census Bureau and is considered Public Domain: Citation Requested. This means the data is freely available for use, but you must cite the source and acknowledge that the data was obtained from FRED. If you plan on using any copyrighted series from other data providers on FRED for commercial purposes, you would need to contact the original data owner for permission.

    Data Fields: The dataset primarily contains two columns: - observation_date: The date of the monthly data point, recorded as the first day of each month from January 1992 to July 2025. - RSXFS: The value of advance retail sales in millions of dollars.

    Citation and Provenance:
    Source: U.S. Census Bureau
    Release: Advance Monthly Sales for Retail and Food Services
    FRED Link: https://fred.stlouisfed.org/series/RSXFS
    Citation: U.S. Census Bureau, Advance Retail Sales: Retail Trade [RSXFS], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/RSXFS, September 8, 2025.

  4. Data usage in consumer products and retail industry 2020

    • statista.com
    Updated May 15, 2021
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    Statista (2021). 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
    May 15, 2021
    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. World: retail sales growth 2020-2025

    • statista.com
    Updated Nov 25, 2025
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    Statista (2025). World: retail sales growth 2020-2025 [Dataset]. https://www.statista.com/statistics/232347/forecast-of-global-retail-sales-growth/
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    Dataset updated
    Nov 25, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 2020
    Area covered
    Worldwide
    Description

    In 2020, global retail sales fell by 2.9 percent as a result of the COVID-19 pandemic, bouncing back in 2021 with a growth of 9.7 percent Global retail sales were projected to amount to around 27.3 trillion U.S. dollars by 2022, up from approximately 23.7 trillion U.S. dollars in 2020.

    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.

  6. Retail Trade in the US

    • ibisworld.com
    Updated Sep 15, 2025
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    IBISWorld (2025). Retail Trade in the US [Dataset]. https://www.ibisworld.com/united-states/market-size/retail-trade/1000/
    Explore at:
    Dataset updated
    Sep 15, 2025
    Dataset authored and provided by
    IBISWorld
    License

    https://www.ibisworld.com/about/termsofuse/https://www.ibisworld.com/about/termsofuse/

    Time period covered
    2005 - 2031
    Area covered
    United States
    Description

    Market Size statistics on the Retail Trade industry in the US

  7. Data from: Retail Sales Analysis

    • kaggle.com
    Updated Jun 23, 2024
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    Sahir Maharaj (2024). Retail Sales Analysis [Dataset]. https://www.kaggle.com/datasets/sahirmaharajj/retail-sales-analysis
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jun 23, 2024
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Sahir Maharaj
    License

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

    Description

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

    It is rich in information that can be leveraged for various data science applications. For instance, analyzing this dataset can offer insights into consumer behavior, such as preferences for specific types of beverages (e.g., wine, beer) during different times of the year. Furthermore, the dataset can be used to identify trends in sales and transfers, highlighting seasonal effects or the impact of certain suppliers on the market.

    One could start with exploratory data analysis (EDA) to understand the basic distribution of sales and transfers across different item types and suppliers. Time series analysis can provide insights into seasonal trends and sales forecasts. Cluster analysis might reveal groups of suppliers or items with similar sales patterns, which can be useful for targeted marketing and inventory management.

  8. 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
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    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.

  9. Retail sales channel share in the United States 2022-2028

    • statista.com
    Updated Nov 28, 2025
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    Statista (2025). Retail sales channel share in the United States 2022-2028 [Dataset]. https://www.statista.com/statistics/829220/share-of-retail-sales-by-channel-us/
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    Dataset updated
    Nov 28, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jul 2024
    Area covered
    United States
    Description

    In 2024, the in-store or brick-and-mortar retail channel was forecast to account for **** percent of total retail sales in the United States. By 2028, e-commerce is expected to make up ** percent of all retail sales.

  10. Online share of retail sales in Great Britain 2025, by sector

    • statista.com
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    Statista, Online share of retail sales in Great Britain 2025, by sector [Dataset]. https://www.statista.com/statistics/280655/proportion-of-retail-sales-made-online-great-britain-by-retail-sector/
    Explore at:
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Mar 2025
    Area covered
    United Kingdom
    Description

    In August 2025, internet sales accounted for 26.2 percent of all retail sales in Great Britain. Over the considered period, food online sales did not go over 10 percent of total retail sales.

  11. 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
      ...

  12. y

    US Retail Sales TTM

    • ycharts.com
    html
    Updated Sep 16, 2025
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    Census Bureau (2025). US Retail Sales TTM [Dataset]. https://ycharts.com/indicators/retail_sales_ttm
    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, 1993 - Aug 31, 2025
    Area covered
    United States
    Variables measured
    US Retail Sales TTM
    Description

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

  13. Retail market size in India 2011-2035

    • statista.com
    • abripper.com
    Updated Nov 25, 2025
    + more versions
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    Statista (2025). Retail market size in India 2011-2035 [Dataset]. https://www.statista.com/statistics/935872/india-retail-market-size/
    Explore at:
    Dataset updated
    Nov 25, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    India
    Description

    The retail market size in India was expected to amount to *** trillion U.S. dollars by 2026, up from *** trillion dollars in 2023. While an overall increase was noted up to 2019, 2020 marked a decrease due to the coronavirus pandemic. The Indian retail landscape Despite the pandemic, India was among the few countries showing growth in retail sales in 2020. Characterized by its unorganized retail, primarily via kirana stores, the country underwent a process of change in retail forms, which is yet to pace down. The emergence of larger retail spaces such as malls and supermarkets, along with the growth of online commerce, drove change in the subcontinent’s retail landscape. Nevertheless, kirana stores continued to dominate Indian retail, adopting digitalization and collaboration with larger players in this sector. The dominance of grocery retail   The retail of groceries contributed as much as ** percent to India’s retail industry. However, only a small share of that was sold through online or modern retailers. The coronavirus (COVID-19) pandemic in 2020 gave online retail a new push to e-grocers. As products were sometimes not available at physical stores, online grocers such as BigBasket managed to fill that gap successfully.

  14. T

    Vietnam Retail Sales YoY

    • tradingeconomics.com
    • id.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Nov 12, 2025
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    TRADING ECONOMICS (2025). Vietnam Retail Sales YoY [Dataset]. https://tradingeconomics.com/vietnam/retail-sales-yoy
    Explore at:
    csv, json, xml, excelAvailable download formats
    Dataset updated
    Nov 12, 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
    Mar 31, 2002 - Oct 31, 2025
    Area covered
    Vietnam
    Description

    Retail Sales in Vietnam increased 7.20 percent in October of 2025 over the same month in the previous year. This dataset provides - Vietnam Retail Sales YoY - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  15. T

    Finland Retail Sales MoM

    • tradingeconomics.com
    • id.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Feb 15, 2025
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    TRADING ECONOMICS (2025). Finland Retail Sales MoM [Dataset]. https://tradingeconomics.com/finland/retail-sales
    Explore at:
    json, csv, xml, excelAvailable download formats
    Dataset updated
    Feb 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 28, 1995 - Oct 31, 2025
    Area covered
    Finland
    Description

    Retail Sales in Finland increased 0.40 percent in October of 2025 over the previous month. This dataset provides - Finland Retail Sales MoM - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  16. US Retail Sales Data from 1992 to 2024

    • kaggle.com
    zip
    Updated Nov 20, 2024
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    Anjali Hansda (2024). US Retail Sales Data from 1992 to 2024 [Dataset]. https://www.kaggle.com/datasets/anjalihansda16/us-retail-sales-data-from-1992-to-2024
    Explore at:
    zip(1221599 bytes)Available download formats
    Dataset updated
    Nov 20, 2024
    Authors
    Anjali Hansda
    License

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

    Area covered
    United States
    Description

    Data Overview

    • Scale: All sales figures are reported in millions of dollars.
    • Size: The dataset contains 40,479 rows and 5 columns.
    • Time Frame: January 1992 - September 2024.
    • Industries Covered: Over 60 industries, including food, clothing, footwear, office supplies, automobiles, electronics, books, beverages, furniture, grocery and many more.
    • Attributes:
      • naics_code
      • kind_of_business
      • sales_month
      • sales
      • estimate_type
    • Source: This dataset was sourced from the publicly available U.S. Census Bureau retail sales data.

    Cleaning & Preprocessing

    • Missing Values:
      Some entries contained (NA) and (S) values, which were converted to null values.
      • (S): Estimate does not meet publication standards due to high sampling variability (coefficient of variation greater than 30%) or poor response quality (low total quantity response rate).
    • Formatting:
      The downloaded data included headings, subheadings, and notes embedded within the tables. These extraneous elements were removed to ensure a clean and consistent dataset.
    • Data Compilation:
      The original dataset was spread across multiple sheets, with each sheet containing data for a specific year. These sheets were consolidated into a single, unified table.
    • Feature Engineering:
      A new column was created to provide both seasonally adjusted and non-seasonally adjusted sales values, enabling more nuanced analysis. Estimates are adjusted for seasonal variations, as well as holiday and trading-day differences, but not for price changes.

    Use Cases

    This dataset can be applied to a variety of analytical and machine learning tasks, including:

    • Data Cleaning: Practice handling missing values, stray entries, and working with datetime data.
    • Time Series Analysis: Perform trend analysis, seasonality detection, and forecasting.
    • Exploratory Data Analysis (EDA): Gain insights into industry-specific trends and patterns.
    • Machine Learning: Use it for predictive modeling and classification tasks.
    • Market Research: Analyze industry performance to inform business strategies.
  17. Online Retail Market in the US by Product and Device - Forecast and Analysis...

    • technavio.com
    pdf
    Updated Mar 3, 2022
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    Technavio (2022). Online Retail Market in the US by Product and Device - Forecast and Analysis 2022-2026 [Dataset]. https://www.technavio.com/report/online-retail-market-industry-in-the-us-analysis
    Explore at:
    pdfAvailable download formats
    Dataset updated
    Mar 3, 2022
    Dataset provided by
    TechNavio
    Authors
    Technavio
    License

    https://www.technavio.com/content/privacy-noticehttps://www.technavio.com/content/privacy-notice

    Time period covered
    2021 - 2026
    Description

    Snapshot img

    The online retail market share in the US is expected to increase to USD 460.13 billion from 2021 to 2026, and the market’s growth momentum will accelerate at a CAGR of 11.64%.

    The report extensively covers online retail market in the US segmentation by the following:

    Product - Apparel, footwear, and accessories, consumer electronics and electricals, food and grocery, home furniture and furnishing, and others
    Device - Smartphones and tablets and PCs
    

    The US online retail market report offers information on several market vendors, including Amazon.com Inc., Apple Inc., Best Buy Co. Inc., Costco Wholesale Corp., eBay Inc., Kroger Co., Target Corp., The Home Depot Inc., Walmart Inc., and Wayfair Inc. among others.

    This online retail market in the US research report provides valuable insights on the post COVID-19 impact on the market, which will help companies evaluate their business approaches.

    What will the Online Retail Market Size in the US be During the Forecast Period?

    Download the Free Report Sample to Unlock the Online Retail Market Size in the US for the Forecast Period and Other Important Statistics

    Online Retail Market in the US: Key Drivers, Trends, and Challenges

    The growing seasonal and holiday sales is notably driving the online retail market growth in the US, although factors such as transportation and logistics may impede the market growth. Our research analysts have studied the historical data and deduced the key market drivers and the COVID-19 pandemic impact on the online retail industry in the US. The holistic analysis of the drivers will help in deducing end goals and refining marketing strategies to gain a competitive edge.

    Key US Online Retail Market Driver

    The growing seasonal and holiday sales is one of the key drivers supporting the US online retail market growth. For instance, from November 1 to December 24, e-commerce sales in the US increased by 11% in 2021, when compared to a massive 47.2% growth in the holiday season of 2020. E-commerce sales made up 20.9 % of total retail sales in the holiday season of 2021, slightly higher than 20.6 percent in 2020. Thanksgiving, Black Friday, and Cyber Monday are the days that see a high amount of online shopping. Apparel, footwear and accessories, consumer electronics, computer hardware, and toys are the largest gaining product categories during the holiday season. Consumers in the US spent $204.5 billion online in November and December 2021, up 8.6% over the same period in 2020. Such exciting sales and offers are driving the market growth.

    Key US Online Retail Market Trend

    Omni-channel retailing is one of the key US online retail market trends fueling the market growth. It is rapidly becoming the norm for many retailers in the US. It offers consumers the option to shop online and pick up the merchandise from the store nearest to their location on the same day. Retailers are observing a high web influence on their in-store sales. For instance, Best Buy is integrating its offline and online stores to boost revenues. As a part of its omnichannel strategy, the retailer is utilizing physical stores as distribution centers for online purchases. According to Best Buy, 40% of its online shoppers prefer picking up their purchases from physical stores. Best Buy also challenges online and discount retailers with its match-to-price strategy, claiming to offer gadgets at or below the price offered by competitors. Such strategies are expected to boost market growth during the forecast period.

    Key US Online Retail Market Challenge

    Transportation and logistics are some of the factors hindering the US online retail market growth. Product procurement or sourcing, shipment of ordered items, and delivery to customers are the three major processes where the intervention of transportation and logistics come into the picture. All these processes require a high investment of both time and money, which challenges the efficiency and effectiveness of retailers and their costing strategies. The higher cost incurred from transportation and logistics reduces the margin of retailers, and most of the time, retailers are unable to break even. Between rising fuel prices, driver shortages, as well as a governmental and societal push for increased digitization and sustainability, transport and logistics will continue to be under a lot of pressure. Such factors will negatively impact the market growth during the forecast period.

    This online retail market in the US analysis report also provides detailed information on other upcoming trends and challenges that will have a far-reaching effect on the market growth. The actionable insights on the trends and challenges will help companies evaluate and develop growth strategies for 2022-2026.

    Who are the Major Online Retail Market Vendors in the US?

    The report analyzes the market’s competitive landscape and offers information on several market vendors, includi

  18. y

    US Retail and Food Services Sales

    • ycharts.com
    html
    Updated Sep 16, 2025
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    Census Bureau (2025). US Retail and Food Services Sales [Dataset]. https://ycharts.com/indicators/us_retail_and_food_services_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 and Food Services Sales
    Description

    View monthly updates and historical trends for US Retail and Food Services Sales. from United States. Source: Census Bureau. Track economic data with YCha…

  19. Indonesia Retail Market Report | Industry Analysis, Size & Forecast, 2030

    • mordorintelligence.com
    pdf,excel,csv,ppt
    Updated Jun 17, 2025
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    Mordor Intelligence (2025). Indonesia Retail Market Report | Industry Analysis, Size & Forecast, 2030 [Dataset]. https://www.mordorintelligence.com/industry-reports/indonesian-retail-industry
    Explore at:
    pdf,excel,csv,pptAvailable download formats
    Dataset updated
    Jun 17, 2025
    Dataset provided by
    Authors
    Mordor Intelligence
    License

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

    Time period covered
    2019 - 2030
    Area covered
    Indonesia
    Description

    Retail in the Indonesian Market is Segmented Into by Products (Food and Beverages, Personal and Household Care, and More), by Distribution Channel (Hypermarkets and Supermarkets, Department Stores and More), by Payment Method (Cash, Debit & Credit Cards and More), Region (Greater Jakarta, Rest of Java and More). Market Forecasts are Provided in Terms of Value (USD).

  20. Total retail sales - Business Environment Profile

    • ibisworld.com
    Updated Oct 20, 2025
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    IBISWorld (2025). Total retail sales - Business Environment Profile [Dataset]. https://www.ibisworld.com/canada/bed/total-retail-sales/17
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    Dataset updated
    Oct 20, 2025
    Dataset authored and provided by
    IBISWorld
    License

    https://www.ibisworld.com/about/termsofuse/https://www.ibisworld.com/about/termsofuse/

    Description

    Total retail sales in Canada represents the aggregate value of goods sold through retail channels, measured in billions of Canadian dollars. This includes sales across all retail subsectors such as food and beverage stores, motor vehicle and parts dealers, clothing and accessories, furniture and home furnishings, electronics, building materials, gasoline stations, health and personal care, and general merchandise stores. Data encompasses both brick-and-mortar and e-commerce transactions. Data is sourced from Statistics Canada's Monthly Retail Trade Survey and is presented in chained 2017 dollars.

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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

Big Data Analytics in Retail Market - Trends & Industry Analysis

Explore at:
pdf,excel,csv,pptAvailable download formats
Dataset updated
Dec 11, 2024
Dataset authored and provided by
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.

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