In 2024, global retail e-commerce sales reached an estimated ************ U.S. dollars. Projections indicate a ** percent growth in this figure over the coming years, with expectations to come close to ************** dollars by 2028. World players Among the key players on the world stage, the American marketplace giant Amazon holds the title of the largest e-commerce player globally, with a gross merchandise value of nearly *********** U.S. dollars in 2024. Amazon was also the most valuable retail brand globally, followed by mostly American competitors such as Walmart and the Home Depot. Leading e-tailing regions E-commerce is a dormant channel globally, but nowhere has it been as successful as in Asia. In 2024, the e-commerce revenue in that continent alone was measured at nearly ************ U.S. dollars, outperforming the Americas and Europe. That year, the up-and-coming e-commerce markets also centered around Asia. The Philippines and India stood out as the swiftest-growing e-commerce markets based on online sales, anticipating a growth rate surpassing ** percent.

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.

The E-Retail Market is Segmented by Product (home Appliances and Electronics, and Other), by Platform Type (Marketplace Platforms, Direct-To-Consumer Brand Stores, and Other), by Device ( Mobile, Desktop & Tablet, and Other), by Geography (North America, and Other). The Market Forecasts are Provided in Terms of Value (USD).

Online Retail Sales and Customer Data

Transactional Data with Product and Customer Details in Online Retail

By Marc Szafraniec [source]

About this dataset

The InvoiceNo column holds unique identifiers for each transaction conducted. This numerical code serves a twofold purpose: it facilitates effortless identification of individual sales or purchases while simultaneously enabling treasury management by offering a repository for record keeping.

In concordance with the invoice number is the InvoiceDate column. It provides a date-time stamp associated with every transaction, which can reveal patterns in purchasing behaviour over time and assists with record-keeping requirements.

The StockCode acts as an integral part of this dataset; it encompasses alphanumeric sequences allocated distinctively to every item in stock. Such a system aids unequivocally identifying individual products making inventory records seamless.

The Description field offers brief elucidations about each listed product, adding layers beyond just stock codes to aid potential customers' understanding of products better and make more informed choices.

Detailed logs concerning sold quantities come under the Quantity banner - it lists the units involved per transaction alongside aiding calculations regarding total costs incurred during each sale/purchase offering significant help tracking inventory levels based on products' outflow dynamics within given periods.

Retail isn't merely about what you sell but also at what price you sell- A point acknowledged via our inclusion of unit prices exerted on items sold within transactions inside our dataset's UnitPrice column which puts forth pertinent pricing details serving as pivotal factors driving metrics such as gross revenue calculation etc

Finally yet importantly is our dive into foreign waters - literally! With impressive international outreach we're looking into segmentation bases like geographical locations via documenting countries (under the name Country) where transactions are conducted & consumers reside extending opportunities for businesses to map their customer bases, track regional performance metrics, extend localization efforts and overall contributing to the formulation of efficient segmentation strategies.

All this invaluable information can be found in a sortable CSV file titled online_retail.csv. This dataset will prove incredibly advantageous for anyone interested in or researching online sales trends, developing customer profiles, or gaining insights into effective inventory management practices

How to use the dataset

Identifying Products: StockCode is the unique identifier for each product. You can use it to identify individual products, track their sales, or discover patterns related to specific items.

Assessing Sales Volume: Quantity column tells you about the number of units of a product involved in each transaction. Along with InvoiceNo, you can analyze overall sales volume or specific purchases throughout your selected period.

Observing Price Fluctuations: By using the UnitPrice, not only can the total cost per transaction be calculated (by multiplying with Quantity), but also insightful observations like price fluctuations over time or determining most profitable items could be derived.

Analyzing Description Patterns/Trends: The Description field sheds light upon what kind of products are being traded. This could provide some inspiration for text analysis like term frequency-inverse document frequency (TF-IDF), sentiment analysis on descriptions, etc., to figure out popular trends at given times.

Analysing Geographical Trends: With the help of Country column, geographical trends in sales volumes across different nations can easily be analyzed i.e., which location has more customers or which country orders more quantity or expensive units based on unit price and quantity columns respectively.

Keep in mind that proper extraction and transformation methodology should be applied while handling data from different columns as per their datatypes (textual/alphanumeric/numeric) requirements.

This dataset not only allows retailers to gain an immediate understanding into their operations but could also serve as a base dataset for those interested in machine learning regarding predicting future transactions

Research Ideas

• Inventory Management: By tracking the 'Quantity' and 'StockCode' over time, a business could use this data to notice if certain products are frequently purchased together or in specific seasons, allowing them to better stock their inventory.
• Pricing Strategy:...

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.

Snapshot img

E-Commerce Retail Market Size 2025-2029

The e-commerce retail market size is forecast to increase by USD 4,833.5 billion at a CAGR of 12% between 2024 and 2029.

The market is experiencing significant growth, driven by the advent of personalized shopping experiences. Consumers increasingly expect tailored recommendations and seamless interactions, leading retailers to integrate advanced technologies such as Artificial Intelligence (AI) to enhance the shopping journey. However, this market is not without challenges. Strict regulatory policies related to compliance and customer protection pose obstacles for retailers, requiring continuous investment in technology and resources to ensure adherence.
Retailers must navigate these challenges to effectively capitalize on the market's potential and deliver value to customers. By focusing on personalization and regulatory compliance, e-commerce retailers can differentiate themselves, build customer loyalty, and ultimately thrive in this dynamic market. Balancing the need for innovation with regulatory requirements is a delicate task, necessitating strategic planning and operational agility. Fraud prevention and customer retention are crucial aspects of e-commerce, with payment gateways ensuring secure transactions.

What will be the Size of the E-Commerce Retail Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
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In the dynamic market, shopping carts and checkout processes streamline transactions, while sales forecasting and marketing automation help businesses anticipate consumer demand and optimize promotions. SMS marketing and targeted advertising reach customers effectively, driving sales growth. Warranty claims and customer support chatbots ensure post-purchase satisfaction, bolstering customer loyalty. Retail technology advances, including sustainable packaging, green logistics, and mobile optimization, cater to environmentally-conscious consumers. Legal compliance, data encryption, and fraud detection safeguard businesses and consumer trust. Product reviews, search functionality, and personalized recommendations enhance the shopping experience, fostering customer engagement.
Dynamic pricing and delivery networks adapt to market fluctuations and consumer preferences, respectively. E-commerce software integrates various functionalities, from circular economy initiatives and website accessibility to email automation and real-time order tracking. Overall, the e-commerce landscape continues to evolve, with businesses adopting innovative strategies to meet the needs of diverse customer segments and stay competitive.

How is this E-Commerce Retail Industry segmented?

The e-commerce retail industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Product

  Apparel and accessories
  Groceries
  Footwear
  Personal and beauty care
  Others


Modality

  Business to business (B2B)
  Business to consumer (B2C)
  Consumer to consumer (C2C)


Device

  Mobile
  Desktop


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    Italy
    UK


  APAC

    China
    India
    Japan
    South Korea


  Rest of World (ROW)

By Product Insights

The apparel and accessories segment is estimated to witness significant growth during the forecast period. The market for apparel and accessories is experiencing significant growth, fueled by several key trends. Increasing consumer affluence and a shift toward premiumization are driving this expansion, with the organized retail sector seeing particular growth. Influenced by social media trends, the Gen Z demographic is a major contributor to this rise in online shopping. This demographic is known for their preference for the latest fashion trends and their willingness to invest in premium products, making them a valuable market segment. Machine learning and artificial intelligence are increasingly being used for returns management and personalized recommendations, enhancing the customer experience.

Ethical sourcing and supply chain optimization are also essential, as consumers demand transparency and sustainability. Cybersecurity threats continue to pose challenges, requiring robust strategies and technologies. B2C and C2C e-commerce are thriving, with influencer marketing and e-commerce analytics playing significant roles. Customer reviews are essential for building trust and brand loyalty, while reputation management and affiliate marketing help expand reach. Sustainable e-commerce and b2b e-commerce are also gaining traction, with third-party logistics and social commerce offering new opportunities. Augment

Online Retail E-Commerce Data Hey everyone! 👋

This dataset contains real e-commerce transaction data from 2009 to 2011. It comes from a UK-based online store that sells a variety of products. The data includes details like invoices, product codes, descriptions, prices, and even customer IDs.

What’s Inside? Each row represents a transaction, and the dataset has the following key columns: 🛒 Invoice – Unique order ID 📦 StockCode – Product code 📝 Description – Name of the product 📊 Quantity – Number of units sold ⏳ InvoiceDate – When the purchase happened 💰 Price – Unit price of the product 👤 Customer ID – Unique identifier for each customer 🌍 Country – Where the customer is from

Why is this dataset useful? This dataset is great for exploring: Customer Segmentation (Find high-value customers) Customer Lifetime Value (LTV) Analysis Sales & Revenue Trends Market Basket Analysis (Which products are bought together?) Predicting Churn & Retention Strategies

How Can You Use It? If you're into data science, machine learning, or business analytics, this dataset is perfect for hands-on projects. You can analyze customer behavior, predict sales, or even build recommendation systems.

Hope this dataset helps with your projects! Let me know if you find something interesting.

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

Online Retail Transaction Data

UK Online Retail Sales and Customer Transaction Data

By UCI [source]

About this dataset

Comprehensive Dataset on Online Retail Sales and Customer Data

Welcome to this comprehensive dataset offering a wide array of information related to online retail sales. This data set provides an in-depth look at transactions, product details, and customer information documented by an online retail company based in the UK. The scope of the data spans vastly, from granular details about each product sold to extensive customer data sets from different countries.

This transnational data set is a treasure trove of vital business insights as it meticulously catalogues all the transactions that happened during its span. It houses rich transactional records curated by a renowned non-store online retail company based in the UK known for selling unique all-occasion gifts. A considerable portion of its clientele includes wholesalers; ergo, this dataset can prove instrumental for companies looking for patterns or studying purchasing trends among such businesses.

The available attributes within this dataset offer valuable pieces of information:

• InvoiceNo: This attribute refers to invoice numbers that are six-digit integral numbers uniquely assigned to every transaction logged in this system. Transactions marked with 'c' at the beginning signify cancellations - adding yet another dimension for purchase pattern analysis.

• StockCode: Stock Code corresponds with specific items as they're represented within the inventory system via 5-digit integral numbers; these allow easy identification and distinction between products.

• Description: This refers to product names, giving users qualitative knowledge about what kind of items are being bought and sold frequently.

• Quantity: These figures ascertain the volume of each product per transaction – important figures that can help understand buying trends better.

• InvoiceDate: Invoice Dates detail when each transaction was generated down to precise timestamps – invaluable when conducting time-based trend analysis or segmentation studies.

• UnitPrice: Unit prices represent how much each unit retails at — crucial for revenue calculations or cost-related analyses.

Finally,

• Country: This locational attribute shows where each customer hails from, adding geographical segmentation to your data investigation toolkit.

This dataset was originally collated by Dr Daqing Chen, Director of the Public Analytics group based at the School of Engineering, London South Bank University. His research studies and business cases with this dataset have been published in various papers contributing to establishing a solid theoretical basis for direct, data and digital marketing strategies.

Access to such records can ensure enriching explorations or formulating insightful hypotheses about consumer behavior patterns among wholesalers. Whether it's managing inventory or studying transactional trends over time or spotting cancellation patterns - this dataset is apt for multiple forms of retail analysis

How to use the dataset

1. Sales Analysis:

Sales data forms the backbone of this dataset, and it allows users to delve into various aspects of sales performance. You can use the Quantity and UnitPrice fields to calculate metrics like revenue, and further combine it with InvoiceNo information to understand sales over individual transactions.

2. Product Analysis:

Each product in this dataset comes with its unique identifier (StockCode) and its name (Description). You could analyse which products are most popular based on Quantity sold or look at popularity per transaction by considering both Quantity and InvoiceNo.

3. Customer Segmentation:

If you associated specific business logic onto the transactions (such as calculating total amounts), then you could use standard machine learning methods or even RFM (Recency, Frequency, Monetary) segmentation techniques combining it with 'CustomerID' for your customer base to understand customer behavior better. Concatenating invoice numbers (which stand for separate transactions) per client will give insights about your clients as well.

4. Geographical Analysis:

The Country column enables analysts to study purchase patterns across different geographical locations.

Practical applications

Understand what products sell best where - It can help drive tailored marketing strategies. Anomalies detection – Identify unusual behaviors that might lead frau...

Online retail in the United Kingdom has been gaining ground in the past decade. With the onset of the coronavirus (COVID-19) crisis, the value of online retail sales in the United Kingdom peaked at around 129.5 billion British pounds in 2021. In 2022, the figure decreased to ***** billion British pounds. However, they then went through another recovery and achieved around ***** billion British pounds in 2024. What ranks high in UK e-commerce? In the United Kingdom, clothing and household goods were the most popular retail items consumers purchased through the internet in 2020. Data published by the Office for National Statistics (UK) showed that other leisure activities and services such as booking holiday accommodations, travel arrangements and event tickets were other areas consumers depended on the internet to buy. German e-commerce market The UK might have the highest share of online sales in retail trade, but other European countries such as Germany and France have had impressive track records over the years as well. According to the forecasts provided by German E-commerce and Distance Selling Trade Association (bevh), the market volume of Germany’s e-commerce sector was projected to see over ** billion euros in 2021.

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

China Online Retail Sales: YoY: Year to Date: Goods data was reported at 5.700 % in Mar 2025. This records an increase from the previous number of 5.000 % for Feb 2025. China Online Retail Sales: YoY: Year to Date: Goods data is updated monthly, averaging 19.900 % from Jun 2014 (Median) to Mar 2025, with 115 observations. The data reached an all-time high of 49.900 % in Sep 2014 and a record low of 3.000 % in Feb 2020. China Online Retail Sales: YoY: Year to Date: Goods data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Consumer Goods and Services – Table CN.HA: Online Retail Sales.

Context

Typically e-commerce datasets are proprietary and consequently hard to find among publicly available data. However, The UCI Machine Learning Repository has made this dataset containing actual transactions from 2010 and 2011. The dataset is maintained on their site, where it can be found by the title "Online Retail".

Content

"This is a transnational data set which contains all the transactions occurring between 01/12/2010 and 09/12/2011 for a UK-based and registered non-store online retail.The company mainly sells unique all-occasion gifts. Many customers of the company are wholesalers."

Acknowledgements

Per the UCI Machine Learning Repository, this data was made available by Dr Daqing Chen, Director: Public Analytics group. chend '@' lsbu.ac.uk, School of Engineering, London South Bank University, London SE1 0AA, UK.

Image from stocksnap.io.

Inspiration

Analyses for this dataset could include time series, clustering, classification and more.

China Online Retail Sales: YoY: Year to Date: Goods and Service data was reported at 7.900 % in Mar 2025. This records an increase from the previous number of 7.300 % for Feb 2025. China Online Retail Sales: YoY: Year to Date: Goods and Service data is updated monthly, averaging 17.100 % from Feb 2015 (Median) to Mar 2025, with 112 observations. The data reached an all-time high of 44.600 % in Feb 2015 and a record low of -3.000 % in Feb 2020. China Online Retail Sales: YoY: Year to Date: Goods and Service data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Consumer Goods and Services – Table CN.HA: Online Retail Sales.

The online retail market, valued at $6.27 billion in 2025, is projected to experience robust growth, fueled by a Compound Annual Growth Rate (CAGR) of 6.23% from 2025 to 2033. This expansion is driven by several key factors. Increasing internet and smartphone penetration globally, particularly in developing economies, provides access to a vastly expanding customer base. Convenience, wider product selection, and competitive pricing offered by online retailers are significant drivers. Furthermore, the rise of e-commerce platforms offering personalized experiences, seamless payment gateways, and efficient delivery services are contributing to market growth. The shift in consumer preferences towards online shopping, accelerated by the recent pandemic, solidifies the long-term growth trajectory of this sector. Significant segments within the market include home appliances and electronics, clothing, footwear, and accessories, food and personal care, and furniture and home décor. Leading players such as Amazon, eBay, Alibaba, and Walmart are constantly innovating to maintain their market share, leading to increased competition and further market dynamism. The geographic distribution of the online retail market reveals significant regional variations. North America and Europe currently hold substantial market shares, driven by high internet penetration and established e-commerce infrastructure. However, the Asia-Pacific region, particularly India and China, demonstrates immense growth potential due to its burgeoning middle class and rapidly expanding digital economy. While challenges remain, such as concerns over data security and cybersecurity, the overall trend points towards sustained and substantial growth for the online retail sector over the forecast period. Effective strategies for businesses will involve adapting to evolving consumer preferences, investing in technological advancements, and navigating the complexities of global logistics and regulations. This will ensure continued success in this dynamic and competitive marketplace. This insightful report provides a detailed analysis of the dynamic online retail market, projecting its trajectory from 2019 to 2033. With a base year of 2025 and an estimated year of 2025, this comprehensive study covers the historical period (2019-2024) and forecasts the market's growth from 2025 to 2033. We delve into key segments like home appliances & electronics, clothing, footwear & accessories, food & personal care, furniture & home décor, and other products, examining market size in millions and exploring the impact of major players including Amazon, eBay, Alibaba, and more. This report is essential for businesses seeking to understand the competitive landscape and capitalize on emerging trends in this multi-billion dollar industry. Recent developments include: In November 2023, Amazon inked a partnership with Meta. This strategic partnership will combine Meta's well-known social media platforms, Facebook and Instagram, with Amazon's enormous product selection to completely transform online shopping., In July 2023, eBay acquired Certilogo, an AI-powered apparel and fashion goods authentication provider.. Notable trends are: The Fashion and Apparel Sector Thrives in the Global E-Retail Boom.

Comprehensive dataset tracking Amazon's market share and competitor performance in US e-commerce from 2020-2024, including revenue figures, market trends, and category breakdowns.

According to estimates, Amazon claimed the top spot among online retailers in the United States in 2023, capturing 37.6 percent of the market. Second place was occupied by the e-commerce site of the retail chain Walmart, with a 6.4 percent market share, followed in third place by Apple, with 3.6 percent.

Amazon’s continued success

Amazon has long dominated the e-commerce market as the world’s favorite online marketplace. In 2022, company hit over half a trillion U.S. dollars in net sales. The United States is by far Amazon’s most profitable market, as the U.S. branch generated over 356 billion U.S. dollars in sales in 2022. Germany ranked second, with 33 billion dollars, followed closely by the United Kingdom with 30 billion dollars.

Online shopping on the rise

Online shopping has grown significantly over the past decade, with more people turning to the internet for their shopping needs. The proof is in the numbers: the U.S. e-commerce industry was worth almost a trillion dollars in 2023. By 2027, forecasts show that the online market will grow to more than 50 percent. U.S. online shoppers purchase fashion and food and beverages the most via the internet.

This table contains 3 series, with data for years 2016 - 2017 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: Canada); Sales (3 items: Retail trade; Electronic shopping and mail-order houses; Retail E-commerce sales).

Ukraine E-Commerce & Online Retail Market valued at USD 7 Bn, driven by internet penetration, mobile commerce, and consumer shifts. Key segments include fashion and individual consumers.

Dataset from Singapore Department of Statistics. For more information, visit https://data.gov.sg/datasets/d_65e4d47c3616d251f9a84ec1ad28f43c/view