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:...

Online Retail Transaction Records

Online Retail Sales: Product Transactions and Customer Details

By Ali Prasla [source]

About this dataset

The Online Retail Sales Dataset, often referred to as the Online Retail.csv file, is an extensive and comprehensive collection of data points relating to e-commerce transactions. This dataset provides a detailed view of sales activities within the online retail sector, covering numerous essential attributes necessary for a quantitative understanding of consumer behavior and the overall business performance.

One of the key elements covered in this dataset is 'InvoiceNo', which is a unique identifier for each transaction taking place in this retail environment. Given its uniqueness, it serves as a primary key for distinguishing individual transactions. It's worthwhile to note that these Invoice Numbers are numerical values.

Another important attribute included here is 'StockCode'. Each product listed or sold on this online retail platform has been assigned with its unique identification code or StockCode. These codes are also numerical values that offer another layer to clearly classify items and distinguish one from another.

For further understanding, every product comes with a basic description noted under the 'Description' column. In textual form, these descriptions provide insights into what exactly each product item entails. Aside from aiding identification efforts, they can potentially open avenues for text-based analysis such as sentiment analysis or keyword flagging based on product trends.

'Moving onto details about transactions themselves', we have two crucial columns: 'Quantity' and 'UnitPrice'. As their names suggest, these show respectively how many particular units of an item were sold per transaction and at what price per unit was sold at.

Further adding detail to our transactions information comes 'InvoiceDate', which records when each separate purchase occurred down to accurate date & time records. This data can be pivotal in recognizing sales patterns throughout different periods or predicting future trends based on historical timing behavior.

Finally yet importantly comes our global indicator - The ‘Country’ column specifies various countries where customers reside who interacts with this particular online platform regularly by making purchases. This application allows us insights into the geographical dispersion of user base across various countries, potentially providing us insights into regional preferences or global market segmentation.

Ith such a wealth of detailed transaction records and customer information, the Online Retail.csv dataset stands as an invaluable tool for those looking to delve deep into online retail sales data analysis. The possibilities with this dataset are vast, ranging from shaping efficient marketing strategies based on geographical data to predicting sales & growth metrics using historical behavior and much more

How to use the dataset

Here's how to make best use of this dataset:

Getting Started Before you start analyzing your data – you'll have to load it into statistical software such as Python (using pandas library) or R. The dataset is saved in .csv file format which supports easy reading into most data manipulation software.

Understand The Fields

• InvoiceNo: Each transaction made has an associated unique numerical identifier called InvoiceNo. Consider it like a receipt code - these allow for tracking individual transactions.

• StockCode: To identify each product uniquely during analysis, refer to each StockCode value which is essentially a product identification code.

• Description: A brief textual description about each product that can be invaluable when dealing with categories for market-basket type analysis.

• Quantity: Each row lists out how many units of a particular item were involved in a single transaction - watch out for very large values as they might represent bulk orders.

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By 2034, the Online Retail Platforms market is expected to have grown to a size and share of about USD 764.64 billion, with a projected CAGR of 14.5%.

Mobile phones dominate global digital commerce website visits and contribute to the largest share of online orders. As of the second quarter of 2025, smartphones constituted around ** percent of retail site traffic globally, responsible for generating ** percent of online shopping orders. Marketplace momentum Retail e-commerce has significantly increased globally over the past few years. Currently, the leading countries in retail e-commerce growth, such as the Philippines, have seen an increase of up to ** percent. In 2024, the majority of online purchases worldwide were made on online marketplaces, incurring around a ** percent share of consumer purchases. The top four retail websites for consumers to visit globally were all marketplaces, with the leading website being Amazon.com. Converting clicks When shopping online, website visits often do not end in purchases. This can be due to having second thoughts when online shopping, or simply due to consumers using the platforms to search for products. In 2025, the conversion rate of online shoppers globally was under * percent, with beauty & skincare incurring the highest conversion rate from online purchases. Across the globe, more ** percent of all retail sales were conducted online. This figure is forecast to increase to ***percent by 2030.

Global Online Retail Services Market is estimated to see healthy growth, pegged at a CAGR of 10% during the forecast period 2023-2031.

Graph and download economic data for E-Commerce Retail Sales as a Percent of Total Sales (ECOMPCTSA) from Q4 1999 to Q2 2025 about e-commerce, retail trade, percent, sales, retail, and USA.

Overview:

This dataset contains 1000 rows of synthetic online retail sales data, mimicking transactions from an e-commerce platform. It includes information about customer demographics, product details, purchase history, and (optional) reviews. This dataset is suitable for a variety of data analysis, data visualization and machine learning tasks, including but not limited to: customer segmentation, product recommendation, sales forecasting, market basket analysis, and exploring general e-commerce trends. The data was generated using the Python Faker library, ensuring realistic values and distributions, while maintaining no privacy concerns as it contains no real customer information.

Data Source:

This dataset is entirely synthetic. It was generated using the Python Faker library and does not represent any real individuals or transactions.

Data Content:

Potential Use Cases (Inspiration):

Customer Segmentation: Group customers based on demographics, purchasing behavior, and preferences.

Product Recommendation: Build a recommendation system to suggest products to customers based on their past purchases and browsing history.

Sales Forecasting: Predict future sales based on historical trends.

Market Basket Analysis: Identify products that are frequently purchased together.

Price Optimization: Analyze the relationship between price and demand.

Geographic Analysis: Explore sales patterns across different cities.

Time Series Analysis: Investigate sales trends over time.

Educational Purposes: Great for practicing data cleaning, EDA, feature engineering, and modeling.

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

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.

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.

With nearly **** of its retail sales conducted over the internet, China is forecast to be the world's most penetrated e-commerce market in 2023. Indonesia and the UK follow, with roughly ** percent and **** percent, respectively, of retail sales expected to take place online.

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.

The global Online Retail Market is poised for substantial expansion, projecting a market size of $6.27 billion with a Compound Annual Growth Rate (CAGR) of 6.23% from 2019 to 2033. This robust growth is fueled by a confluence of compelling drivers, including the increasing internet penetration and smartphone adoption worldwide, coupled with evolving consumer preferences for convenience and personalized shopping experiences. The younger demographic, in particular, is increasingly embracing e-commerce for its vast product selection and competitive pricing. Emerging markets, especially in the Asia Pacific region, are anticipated to be significant contributors to this growth due to rapid digitalization and a burgeoning middle class. The market's trajectory is further bolstered by advancements in logistics and payment technologies, which are enhancing the overall online shopping journey. The Online Retail Market is characterized by a diverse range of product segments, with Home Appliances and Electronics, and Clothing, Footwear, and Accessories leading the charge in terms of consumer spending. Food and Personal Care items are also experiencing a significant surge in online sales as consumers become more comfortable purchasing everyday essentials online. The Furniture and Home Decor segment is witnessing a positive trend as virtual showrooms and advanced visualization tools gain traction. Key industry players such as Amazon Inc., Alibaba Group Holding Ltd., and Walmart Inc. are continuously innovating with new strategies, including same-day delivery, subscription services, and personalized recommendations, to capture a larger market share. However, the market also faces restraints such as concerns over data security and privacy, the logistical complexities of last-mile delivery, and the competitive pressure of maintaining attractive pricing while ensuring profitability. Geographically, North America and Europe currently hold dominant positions, but the Asia Pacific region is rapidly catching up and is expected to be a major growth engine in the coming years. This report provides a comprehensive analysis of the global Online Retail Market, projecting a substantial growth trajectory driven by evolving consumer behaviors and technological advancements. The market is characterized by its dynamic nature, constant innovation, and increasing consolidation among key players. Notable trends are: The Fashion and Apparel Sector Thrives in the Global E-Retail Boom.

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.

Australia Online Retail Sales data was reported at 4,207.200 AUD mn in Mar 2025. This records an increase from the previous number of 3,758.800 AUD mn for Feb 2025. Australia Online Retail Sales data is updated monthly, averaging 1,659.100 AUD mn from Mar 2013 (Median) to Mar 2025, with 145 observations. The data reached an all-time high of 5,349.400 AUD mn in Dec 2024 and a record low of 417.400 AUD mn in Mar 2013. Australia Online Retail Sales data remains active status in CEIC and is reported by Australian Bureau of Statistics. The data is categorized under Global Database’s Australia – Table AU.H020: Online Retail Sales. [COVID-19-IMPACT]

Explore the booming Cross-Border B2C E-Commerce market, projected to exceed $1.5 trillion by 2025 with a 12% CAGR. Discover key drivers, trends, and regional growth in global online retail.

This shift will continue as global consumers remain cautious of what they are spending their money on and how much, especially with inflationary pressures and rising costs of living. As a result, consumers will look for the best deals online and across borders, making global online shopping events a critical strategic tool for manufacturers and brands everywhere.

With e-commerce rising as a key retail channel generating strong revenue, manufacturers and brands are now encountering a new question of how to boost online sales and continue this growth momentum. Global online shopping festivals and events can be the next area to transform under the e-commerce evolution.

Underestimating them as a “one-time” event in the yearly sales calendar to generate “additional revenue” is a mistake. In fact, participating in these global online shopping festivals and events can be beneficial for brands in many ways, especially if they are looking for cross-border opportunities. Thanks to e-commerce and its technology, brands can easily set up their online space on global platforms without having to invest the same amount of money required when building physical stores —while avoiding any potential risks this strategy presents.

With the right data brands can test and track how their products perform by platform and market, which can help decide where to allocate resources and invest in advertising and promotions to improve overall ROI for their business.