Retail Sales in the United States increased 0.20 percent in September 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.

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

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.

By the end of 2024, total retail sales reached approximately **** trillion U.S. dollars, around a quarter of a billion U.S. dollar increase from the year before. Retail sales have steadily increased since 2009, as the economy recovered from the downward trend due to the recession following the 2007-2008 financial crisis, and most recently from the impact of the coronavirus (COVID-19) crisis. The United States as retail powerhouse The United States is home to many of the leading retail companies in the world, including Walmart, Costco, and Amazon. Amazon, in particular, has seen extreme levels of growth in revenue in tandem with the increase of e-commerce globally. The rise of e-commerce and mobile shopping E-commerce is responsible for a growing percentage of total retail sales, partially due to a surge in mobile shopping, with customers increasingly using their mobile devices for various online shopping activities. Smartphones accounted for more retail website visits than desktops or tablets, and matched desktops in generating online shopping orders.

In the second quarter of 2025, the share of e-commerce in total U.S. retail sales stood at **** percent, up from the previous quarter. From January to March 2025, retail e-commerce sales in the United States hit over *** billion U.S. dollars, the highest quarterly revenue in history. How e-commerce measures up in total U.S. retail In 2024, the reported total value of retail e-commerce sales in the United States amounted to over ****trillion U.S. dollars—impressive, but the figure pales compared to the total annual retail trade value of ******trillion U.S. dollars. Rising e-commerce segments Online shopping is popular among all age groups, though digital purchases are most common among Millennial internet users. In 2022, around ** percent of Millennials purchased items via the internet. Mobile commerce is also growing in popularity, as consumers increasingly rely on their smartphones and mobile apps for shopping activities. In the fourth quarter of 2022, m-commerce spending made up ** percent of the overall online spending in the United States.

Context

The Monthly State Retail Sales (MSRS) is the Census Bureau's new experimental data product featuring modeled state-level retail sales. This is a blended data product using Monthly Retail Trade Survey data, administrative data, and third-party data. Year-over-year percentage changes are available for Total Retail Sales excluding Non-store Retailers as well as 11 retail North American Industry Classification System (NAICS) retail subsectors. These data are provided by state and NAICS codes beginning with January 2019.

Content

Geography: US

Time period: 2019 - 2022

Unit of analysis: US Census Bureau's Monthly State Retail Sales Data

Variables

Acknowledgements

Datasource: United States Census Bureau's Monthly State Retail Sales

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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.

Overview with Chart & Report: Retail Sales m/m reflect a change in the US retail sails in the reported month compared to the previous one. The indicator is calculated based on statistics received from 5,000 retail stores of

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.

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

This statistic shows a trend in total retail sales, including food services, in the United States from January 2017 to July 2025. In July 2025, U.S. retail sales had amounted to an estimated *********** U.S. dollars (not adjusted), which is an increase of approximately ** ******* U.S. dollars compared to the same month one year earlier.

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

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Market Size statistics on the Retail Trade industry in the US

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The 'Retail Sales MoM' (Month-over-Month) in the USA measures the percentage change in the total value of sales at the retail level from one month to the next.-2025-01-16

The 'Retail Sales MoM' (Month-over-Month) in the USA measures the percentage change in the total value of sales at the retail level from one month to the next.-2025-06-17