In 2024, Walmart registered global net sales of about *** billion U.S. dollars, making it the leading U.S. retailer in terms of worldwide retail sales. Amazon was the closest challenger to Walmart's figures, with retail sales amounting to approximately *** billion U.S. dollars that year.

By 2027, the e-commerce retailer Amazon is forecast to be the leading retailer worldwide, just barely outdoing the Alibaba Group in terms of sales. Specifically, projections for 2027 show that the total chain retail sales of Amazon are going to reach a value of more than **** trillion U.S. dollars. Walmart would rank fifth, generating an estimated *** billion U.S. dollars in chain retail sales that year.

Retail Sales in the United States increased 0.50 percent in July 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.

In 2023, ** percent of Walmart's retail sales came from U.S. operations. In comparison, all of The Kroger Company's retail sales were generated within the United States. Walmart was the leading retailer based on U.S. retail sales.

This ranking depicts the leading 100 American retailers in 2024, based on U.S. retail sales. Once again, Walmart was the leading American retailer. That year, the company accounted for retail sales of about *** billion U.S. dollars. Walmart was founded by Samuel Moore Walton (1918-1992) in 1962. Walmart's headquarters is situated in Bentonville, Arkansas and operates worldwide under different names (such as Walmex in Mexico and Best Price in India). Leading retailers in the United States Although Walmart is the unequivocal front-running retailer in terms of U.S. retail sales, Amazon.com inches closer each and every year. The retail industry is in the midst of a customer revolution. The collision of the virtual and physical worlds is fundamentally changing consumers' purchasing behaviors. Consumers are seeking an integrated shopping experience across all channels and expect retailers to deliver this experience. The key drivers of this customer revolution are the rapid adoption of mobile devices, digital media and tablets equipped with shopping apps. In fact, the share of smartphone users in the United States was around ** percent. In other words, nearly the entire country's population now uses smartphones. As such, the retail paradigm has shifted from a physical connection point with customers to a multi-pronged approach that crosses both physical and digital channels. The traditional brick-and-mortar retail store is no longer the dominant medium for purchasing all types of goods. Instead, it serves as one of many potential connection points between customers and a retailer's brand. Today's consumer is increasingly connected to both the physical and digital space and able to interact with retailers through multiple channels simultaneously. To stay competitive in this ever-evolving landscape, it is imperative for retailers to deliver a seamless customer experience across all channels and provide the right services and products at the right time.

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

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 sever

Small specialty retail stores are influenced by broad macroeconomic variables rather than product-specific trends. Still, individual segments do respond to specific shifts in consumer preferences. In recent years, rising per capita disposable income has sustained demand throughout the retail sector. A recovery from the pandemic boosted consumer spending and encouraged consumers to return to brick-and-mortar stores. Specialty retailers were relatively unaffected by pandemic declines as high-income consumers and tobacco users, two significant markets for the industry, continued to spend. Competition from online and big-box retailers has risen, putting downward pressure on profit. More stores are expanding their online platforms to boost consumer reach and provide additional revenue streams. Rising operational costs have contributed to a slight dip in profit. Revenue for small specialty retailers is expected to swell at a CAGR of 4.0% to $68.4 billion through the end of 2025, including a hike of 2.0% in 2025 alone. Despite intensifying competition from discount department stores and online retailers, specialty retail stores have relied on serving a particular niche to remain successful. Big-box stores offer a one-stop shopping experience with lower prices for similar products. External competition has driven underperforming retailers to exit the industry, leaving nonemployers and small retail stores with low barriers to entry. Still, revenue gains have prompted the emergence of many new specialty retailers seeking to capitalize on the trend of shopping locally and broader sustainability trends. Small retailers have maintained a strong customer base by offering a unique in-store experience and high-quality products. Moving forward, small specialty retailers will continue expanding, albeit slower than in the previous five-year period. A gain in consumer spending and consumer confidence compounded by growing environmental awareness will support specialty retail store sales. Ongoing competition from large-scale retailers and declining smoking rates will mitigate specialty retailers' expansion. More consumers view consumer products, particularly luxury and nostalgic items, as sound investment options. Stores can benefit from this trend by stocking high-end goods that appeal to these consumers, focusing on popular brands. Revenue is expected to expand at a CAGR of 1.4% to $73.3 billion through the end of 2030.

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!

Department stores have continued their long-term dip, with revenue falling amid shifting market dynamics. The industry's slump has been fueled by a 7.2% revenue drop in 2021 alone, caused by relatively low consumer confidence levels and high unemployment. Industry performance has been challenged by rising inflationary pressure since 2022 and the competitive presence of e-commerce rivals. Another rising trend is the increasing number of major retailers that have expanded their product ranges to include groceries, providing a heightened level of convenience. This transitions the revenue of these retailers to the Warehouse Clubs and Supercenters industry (IBISWorld report 45291), reducing industry participation. Revenue for department stores is expected to dip at a CAGR of 2.7% to $187.4 billion through the end of 2025, including a slump of 0.3% in 2025 alone, when profit will account for 3.7% of revenue. Online companies are increasingly undercutting traditional department store prices to save on operational costs. Companies with brick-and-mortar stores incur higher operational costs than online-based businesses because they pay for high-traffic retail space and require sales associates. Retailers have lowered selling prices and offered increased promotional deals to better compete. In April 2024, Nordstrom launched its digital Marketplace to expand its online presence and appeal to a wider audience. Through online platforms, retailers can offer a wider selection of brands, sizes and products. Similarly, department stores have since launched their digital stores and integrated them into their operations to provide an omnichannel shopping experience. While these efforts have helped retain some customers, profit has dropped because of inflationary pressures on the industry, resulting in retailers making more cost-cutting decisions, which has tempered declines. In the coming years, accelerating competition from e-commerce businesses and the transition of department stores to supercenters will continue to pressure revenue. Some department stores will shutter more locations. However, disposable income growth will help lessen these factors' blow on future revenue. Department stores like Macy's and Nordstrom will continue to benefit from strong brand recognition, particularly as older customers become more comfortable with online shopping. Investments in online platforms will pay off for retailers and help department stores be more competitive in a tough business landscape. Revenue for department stores is expected to slump at a CAGR of 0.2% to $185.1 billion through the end of 2030.

Japan Large Scale Retailers Sales: Communication Appliances data was reported at 26.665 JPY bn in Jan 2020. This records an increase from the previous number of 26.089 JPY bn for Dec 2019. Japan Large Scale Retailers Sales: Communication Appliances data is updated monthly, averaging 26.726 JPY bn from May 2014 (Median) to Jan 2020, with 69 observations. The data reached an all-time high of 44.744 JPY bn in Mar 2019 and a record low of 21.065 JPY bn in Feb 2016. Japan Large Scale Retailers Sales: Communication Appliances data remains active status in CEIC and is reported by Ministry of Economy, Trade and Industry. The data is categorized under Global Database’s Japan – Table JP.H009: Large Scale Specialty Retail Stores: Sales.

Context

You are provided with historical sales data from 2009 to 2012. This data contain 3 product category which are office supplies, technology, and furniture. Each category has several sub-categories. The company also runs promotional in the form of a discount.

There is two CSV file provided in the dataset. The raw_data.csv is the unformatted file that has 5499 rows and 1 column. While clean_data.csv is a formatted file that has 5499 rows and 10 columns.

Content

Attribute Information: - order_id : unique order number - order_status : status of the order, whether is finished or returned - customer : customer name - order_date : date of the order - order_quantity : the quantity on a particular order - sales : sales generated on a particular order, the value is in IDR(Indonesia Rupiah) currency - discount : a discount percentage - discount_value : a sales multiply by discount, the value is in IDR(Indonesia Rupiah) currency - product_category : a category of the product - product_sub_category : a subcategory from product category

Acknowledgements

DQLab is an Online Data Science Learning Center to produce data practitioners who can make an impact. This dataset is part of a project in order to build analytical skills and apply knowledge to industry problems.

Source

Project Data Analysis for Retail: Sales Performance Report: https://academy.dqlab.id/main/package/project/182?pf=0

The rapid ascent of e-commerce and omnichannel strategies is reshaping consumer engagement and purchasing patterns, driving a wave of transformation across the retail trade sector. As of 2025, the sector is expected to log $7.4 trillion in revenue, although its growth is anticipated to decelerate slightly to 0.4% in the current year. Gen Z and millennials have championed the digital shopping revolution, pushing retailers to prioritize online sales and customer engagement platforms. However, brick-and-mortar stores retain a pivotal role in supporting ongoing customer engagement alongside the online momentum as retailers blend physical and digital experiences. As automation has augmented efficiency across operations, retailers have also strategically diversified product lines and incorporated sustainability into their brands to meet changing consumer expectations. Over the past five years, the retail sector has seen a compound annual growth rate of 2.2%, which underscores the impact of diversified strategies in maintaining momentum. The adoption of automation has produced mixed results. Self-checkout systems, for example, have reduced payroll expenses for businesses while streamlining the customer experience, though several studies have reported that some customer segments dislike self-checkout due to technological glitches and some retailers have struggled with implementation and reported a rise in theft. Major chains like Target have honed their product diversification strategies, transforming their stores into one-stop shops that blend essential goods with discretionary items and healthcare, driving up revenue in multiple categories. Sustainability is another theme of the current period, with the sector’s commitment marked by increased budgets for eco-friendly practices and a growing market for pre-owned goods. Despite high inflation during the period giving way to high interest rates that stayed stagnant for a year before beginning to fall again in September 2024, retailers managed to navigate the challenges of economic fluctuations and keep consumer interest high through diversification. A projected compound annual growth rate of 0.9% for the next five years would set revenue on a steady path toward an expected $7.7 trillion through the end of 2030. Artificial intelligence is set to further revolutionize retail operations, enhancing stock management, logistics and consumer personalization. Augmented and virtual reality technologies will prove integral to engaging the tech-savvy younger generations by offering novel ways to interact with products before purchase. However, global trade tensions and tariffs could challenge profitability as retailers manage higher import costs. Reverse logistics will thrive as consumers’ eco-consciousness continues to grow, turning returns into revenue opportunities and aligning with trends toward sustainable consumption. The sector’s profit is expected to remain steady over the next five years, bolstered by consumers’ willingness to trade up to items that mix luxury and affordability.

Korea Retail Sales: Major Department Stores: Men's Apparel data was reported at 10.100 % in Sep 2018. This records an increase from the previous number of 1.200 % for Aug 2018. Korea Retail Sales: Major Department Stores: Men's Apparel data is updated monthly, averaging -0.400 % from Feb 2003 (Median) to Sep 2018, with 188 observations. The data reached an all-time high of 19.900 % in Dec 2005 and a record low of -22.300 % in Mar 2004. Korea Retail Sales: Major Department Stores: Men's Apparel data remains active status in CEIC and is reported by Ministry of Trade, Industry and Energy. The data is categorized under Global Database’s South Korea – Table KR.H019: Retail Sales: YoY%.

Japan Large Scale Retailers Sales: Total data was reported at 385.119 JPY bn in Jan 2020. This records a decrease from the previous number of 447.821 JPY bn for Dec 2019. Japan Large Scale Retailers Sales: Total data is updated monthly, averaging 340.833 JPY bn from May 2014 (Median) to Jan 2020, with 69 observations. The data reached an all-time high of 515.391 JPY bn in Sep 2019 and a record low of 265.914 JPY bn in Oct 2019. Japan Large Scale Retailers Sales: Total data remains active status in CEIC and is reported by Ministry of Economy, Trade and Industry. The data is categorized under Global Database’s Japan – Table JP.H009: Large Scale Specialty Retail Stores: Sales.

Analysis of ‘Big Mart Sales’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/akashdeepkuila/big-mart-sales on 12 November 2021.

--- Dataset description provided by original source is as follows ---

Context

The data scientists at Big Mart have collected 2013 sales data for 1559 products across 10 stores in different cities. Also, certain attributes of each product and store have been defined. The aim is to build a predictive model and predict the sales of each product at a particular outlet.

Using this model, Big Mart will try to understand the properties of products and outlets which play a key role in increasing sales.

Please note that the data may have missing values as some stores might not report all the data due to technical glitches. Hence, it will be required to treat them accordingly.

Content

The dataset provides the product details and the outlet information of the products purchased with their sales value split into a train set (8523) and a test (5681) set. Train file: CSV containing the item outlet information with sales value Test file: CSV containing item outlet combinations for which sales need to be forecasted

Variable Description

• ProductID : unique product ID
• Weight : weight of products
• FatContent : specifies whether the product is low on fat or not
• Visibility : percentage of total display area of all products in a store allocated to the particular product
• ProductType : the category to which the product belongs
• MRP : Maximum Retail Price (listed price) of the products
• OutletID : unique store ID
• EstablishmentYear : year of establishment of the outlets
• OutletSize : the size of the store in terms of ground area covered
• LocationType : the type of city in which the store is located
• OutletType : specifies whether the outlet is just a grocery store or some sort of supermarket
• OutletSales : (target variable) sales of the product in the particular store

Inspiration

Sales of a given product at a retail store can depend both on store attributes as well as product attributes. The dataset is ideal to explore and build a data science model to predict the future sales.

--- Original source retains full ownership of the source dataset ---

Japan Large Scale Retailers Sales: Tokyo data was reported at 76.179 JPY bn in Jan 2020. This records a decrease from the previous number of 89.577 JPY bn for Dec 2019. Japan Large Scale Retailers Sales: Tokyo data is updated monthly, averaging 69.616 JPY bn from May 2014 (Median) to Jan 2020, with 69 observations. The data reached an all-time high of 104.225 JPY bn in Dec 2018 and a record low of 57.186 JPY bn in Oct 2019. Japan Large Scale Retailers Sales: Tokyo data remains active status in CEIC and is reported by Ministry of Economy, Trade and Industry. The data is categorized under Global Database’s Japan – Table JP.H009: Large Scale Specialty Retail Stores: Sales.

Japan Large Scale Retailers Sales: YoY: Miyazaki data was reported at 0.800 % in Jan 2020. This records an increase from the previous number of -8.100 % for Dec 2019. Japan Large Scale Retailers Sales: YoY: Miyazaki data is updated monthly, averaging -0.500 % from Jan 2015 (Median) to Jan 2020, with 61 observations. The data reached an all-time high of 73.700 % in Sep 2019 and a record low of -40.100 % in Mar 2015. Japan Large Scale Retailers Sales: YoY: Miyazaki data remains active status in CEIC and is reported by Ministry of Economy, Trade and Industry. The data is categorized under Global Database’s Japan – Table JP.H009: Large Scale Specialty Retail Stores: Sales.

Computer stores are undergoing a significant transformation, shaped by the rapid rise of e-commerce and evolving consumer preferences. In 2025, the industry is projected to generate $39.6 billion in revenue, reflecting a modest 0.4% CAGR expansion, including a projected increase of 0.7% in 2025. Traditional brick-and-mortar retailers face mounting competition from direct-to-consumer channels and major online platforms, which offer greater convenience and selection. This shift is forcing stores to adapt by investing in digital capabilities, value-added services and unique in-store experiences. At the same time, supply chain uncertainties, such as tariffs on Chinese imports, require agile inventory and pricing strategies. Structurally, the industry is marked by intense competition, with manufacturers and online giants increasingly bypassing traditional retailers. The market is also being reshaped by changing consumer demands, as laptops and high-performance portable devices outpace desktops, driven by trends in remote work, gaming and digital learning. Retailers must now prioritize stocking the latest devices, invest in knowledgeable staff and offer interactive experiences to maintain market share. The emergence of AI-powered PCs is poised to further redefine the competitive landscape, as consumers seek smarter, more adaptive technology. Retailers are responding by enhancing customer education, offering exclusive products and developing robust omnichannel models that blend in-store and online experiences. Looking ahead, the industry’s outlook is cautiously optimistic, with a projected CAGR of 0.6% and anticipated revenues reaching $40.8 billion by 2030. Retailers will increasingly adopt omnichannel strategies, invest in digital infrastructure and experiment with new service models to meet evolving customer expectations. Economic growth is expected to drive higher consumer spending on computers and related products, presenting opportunities for increased revenue and profit through upselling and premium offerings. Additionally, sustainability and circular-economy initiatives, such as buy-back programs and upcycling, will become central to retail strategies, helping stores differentiate themselves and build lasting customer loyalty in an increasingly competitive and environmentally conscious market.

Korea Retail Sales: Major Department Stores: Food data was reported at -5.200 % in Oct 2018. This records a decrease from the previous number of 6.700 % for Sep 2018. Korea Retail Sales: Major Department Stores: Food data is updated monthly, averaging 3.300 % from Feb 2003 (Median) to Oct 2018, with 189 observations. The data reached an all-time high of 89.800 % in Feb 2007 and a record low of -50.700 % in Feb 2003. Korea Retail Sales: Major Department Stores: Food data remains active status in CEIC and is reported by Ministry of Trade, Industry and Energy. The data is categorized under Global Database’s South Korea – Table KR.H019: Retail Sales: YoY%.