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...

Context

E-commerce has become a new channel to support businesses development. Through e-commerce, businesses can get access and establish a wider market presence by providing cheaper and more efficient distribution channels for their products or services. E-commerce has also changed the way people shop and consume products and services. Many people are turning to their computers or smart devices to order goods, which can easily be delivered to their homes.

Content

This is a sales transaction data set of UK-based e-commerce (online retail) for one year. This London-based shop has been selling gifts and homewares for adults and children through the website since 2007. Their customers come from all over the world and usually make direct purchases for themselves. There are also small businesses that buy in bulk and sell to other customers through retail outlet channels.

The data set contains 500K rows and 8 columns. The following is the description of each column. 1. TransactionNo (categorical): a six-digit unique number that defines each transaction. The letter “C” in the code indicates a cancellation. 2. Date (numeric): the date when each transaction was generated. 3. ProductNo (categorical): a five or six-digit unique character used to identify a specific product. 4. Product (categorical): product/item name. 5. Price (numeric): the price of each product per unit in pound sterling (£). 6. Quantity (numeric): the quantity of each product per transaction. Negative values related to cancelled transactions. 7. CustomerNo (categorical): a five-digit unique number that defines each customer. 8. Country (categorical): name of the country where the customer resides.

There is a small percentage of order cancellation in the data set. Most of these cancellations were due to out-of-stock conditions on some products. Under this situation, customers tend to cancel an order as they want all products delivered all at once.

Inspiration

Information is a main asset of businesses nowadays. The success of a business in a competitive environment depends on its ability to acquire, store, and utilize information. Data is one of the main sources of information. Therefore, data analysis is an important activity for acquiring new and useful information. Analyze this dataset and try to answer the following questions. 1. How was the sales trend over the months? 2. What are the most frequently purchased products? 3. How many products does the customer purchase in each transaction? 4. What are the most profitable segment customers? 5. Based on your findings, what strategy could you recommend to the business to gain more profit?

Photo by CardMapr on Unsplash

In 2024, global retail e-commerce sales reached an estimated six trillion U.S. dollars. Projections indicate a 31 percent growth in this figure over the coming years, with expectations to come close to eight trillion 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 800 billion 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 two trillion 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 20 percent.

Mobile phones dominate global digital commerce website visits and contribute to the largest share of online orders. As of the fourth quarter of 2024, smartphones constituted around 78 percent of retail site traffic globally, responsible for generating 68 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 24 percent. In 2024, the majority of online purchases worldwide were made on online marketplaces, incurring around a 30 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 2024, the conversion rate of online shoppers globally was just over two percent, with food and beverages incurring the highest conversion rate from online purchases. Across the globe, almost 20 percent of all retail sales were conducted online. This figure is forecast to increase to at least 21 percent by 2027.

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).

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. Data was obtained from the UCI Machine Learning public repository

Internet sales have played an increasingly significant role in retailing. In 2024, e-commerce accounted for over ** percent of retail sales worldwide. Forecasts indicate that by 2029, the online segment will make up close to over ** 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 exceed **** trillion U.S. dollars by 2028. Digital development in Latin America boomed during the COVID-19 pandemic, generating unprecedented e-commerce growth in various economies across the region. So much so that Brazil and Argentina appear to lead the world's fastest-growing online retail markets. This trend correlates strongly with the constantly improving online access, especially in "mobile-first" online communities, which have long struggled with traditioe-comernal fixed broadband connections due to financial or infrastructure constraints but enjoy the advantages of cheap mobile broadband connections. M-commerce on the rise The average order value of online shopping via smartphones and tablets still lags traditional e-commerce via desktop computers. However, 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 2021, Malaysia 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. South Korea, Taiwan, and the Philippines completed the top of the ranking.

Snapshot img

E-Commerce Retail Market Size 2024-2028

The e-commerce retail market size is forecast to increase by USD 4061.3 billion at a CAGR of 11.2% between 2023 and 2028.

The market is experiencing growth, driven by the advent of personalized shopping experiences and the integration of Artificial Intelligence (AI) technologies. Consumers increasingly demand customized offerings, leading retailers to invest heavily in AI-powered solutions for product recommendations, inventory management, and customer service. However, this market is not without challenges. Strict regulatory policies related to compliance and customer protection continue to pose significant hurdles for retailers. Compliance with data privacy regulations, such as GDPR and CCPA, and ensuring secure payment gateways are essential for maintaining customer trust and avoiding hefty fines. Companies seeking to capitalize on this market's opportunities must prioritize investments in AI and personalization while navigating the complex regulatory landscape. Effective implementation of these strategies will enable retailers to differentiate themselves from competitors and thrive in the evolving the market.

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

Request Free SampleThe market in the United States continues to experience growth, driven by increasing internet penetration and the convenience of online shopping. According to recent studies, retail e-commerce sales are projected to reach record levels, surpassing USD800 billion by 2025. This growth is fueled by several factors, including the proliferation of digital payment methods, such as mobile wallets and buy now, pay later options, and the integration of payment systems into e-commerce platforms for seamless transaction processing. Moreover, the market is witnessing a shift towards business-to-business (B2B) and cross-border e-commerce, as well as the adoption of advanced technologies like augmented reality and voice orders to enhance the shopping experience. The market is also witnessing a rise in direct selling through social media and marketplaces, with daily essentials, computer devices, and luxury items being popular categories. Inventory management and data security remain critical concerns for e-commerce retailers, with responsive websites and mobile applications becoming essential for reaching a wider customer base. The use of smartphones and tablet devices for online shopping continues to grow, making mobile technologies a significant trend in the market.

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 2024-2028, as well as historical data from 2018-2022 for the following segments. ProductApparel and accessoriesGroceriesFootwearPersonal and beauty careOthersModalityBusiness to business (B2B)Business to consumer (B2C)Consumer to consumer (C2C)GeographyAPACChinaIndiaJapanSouth KoreaNorth AmericaUSCanadaEuropeFranceGermanyItalyUKSouth AmericaMiddle East and Africa

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, driven by several key factors. Increasing financial institutions' support for online platforms, the trend toward business-to-business (B2B) and consumer-to-consumer (C2C) transactions, and the shift toward organized retail are major contributors to this expansion. The market for apparels and accessories, including footwear, is projected to reach substantial growth, especially in emerging markets. For instance, in India, the domestic lifestyle industry, which includes apparel, beauty, accessories, and footwear, is expected to reach USD210 billion by 2028. A significant driver of this growth is the Gen Z demographic, which is heavily influenced by social media trends and prefers the convenience of online shopping. This generation's preference for the latest fashion trends and willingness to spend on premium products makes them a crucial segment for e-commerce retailers. However, the market also faces challenges such as digital fraud and cybercrime, requiring digital infrastructure and cybersecurity measures. E-commerce platforms are incorporating security features, such as AI technologies, digital wallets, and payment integration, to ensure a safe and personalized shopping experience for consumers. The market is also witnessing the adoption of headless e-commerce, responsive websites, voice orders, and mobile applications to cater to the increasing use of tablet devices and smartphone devices for online shopping. Additionally, the market is seeing the emergence of cross-border e-commerce, daily essentials, and luxury items, requiring advanced inventory management

Abstract: A real online retail transaction data set of two years.

Data Set Information: This Online Retail II data set contains all the transactions occurring for a UK-based and registered, non-store online retail between 01/12/2009 and 09/12/2011.The company mainly sells unique all-occasion gift-ware. Many customers of the company are wholesalers.

Attribute Information: InvoiceNo: Invoice number. Nominal. A 6-digit integral number uniquely assigned to each transaction. If this code starts with the letter 'c', it indicates a cancellation. StockCode: Product (item) code. Nominal. A 5-digit integral number uniquely assigned to each distinct product. Description: Product (item) name. Nominal. Quantity: The quantities of each product (item) per transaction. Numeric. InvoiceDate: Invice date and time. Numeric. The day and time when a transaction was generated. UnitPrice: Unit price. Numeric. Product price per unit in sterling (£). CustomerID: Customer number. Nominal. A 5-digit integral number uniquely assigned to each customer. Country: Country name. Nominal. The name of the country where a customer resides.

Source: Dr. Daqing Chen, Course Director: MSc Data Science. chend '@' lsbu.ac.uk, School of Engineering, London South Bank University, London SE1 0AA, UK.

Please find more information refer the below link, https://archive.ics.uci.edu/ml/datasets/Online+Retail+II

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.

In 2024, it was estimated that roughly six percent of online retail sales in the United States were generated using social networks as a channel. With the number of social commerce buyers expected to increase over the next few years, this segment is forecast to account for about 8.4 percent of total e-commerce retail sales in the U.S. market by 2028.

In the fourth quarter 2024, the share of e-commerce in total U.S. retail sales stood at 16.4 percent, up from the previous quarter. From October to December 2024, retail e-commerce sales in the United States hit over 309 billion U.S. dollars, the highest quarterly revenue in history. How e-commerce measures up in total U.S. retail In 2023, the reported total value of retail e-commerce sales in the United States amounted to over one trillion U.S. dollars—impressive, but the figure pales compared to the total annual retail trade value of seven trillion U.S. dollars. E-commerce still accounts for a mere 15.4 percent of total retail sales in the United States. 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 55 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 38 percent of the overall online spending in the United States.

In 2023, e-commerce comprised over 15.6 percent of total retail sales in the United States. Forecasts suggest that this proportion will continue to rise steadily in the coming years, reaching approximately 20.6 percent by 2027.

Fashion fever

The digital revolution has significantly changed how retail is done, impacting a wide range of product categories. Out of all e-commerce product categories, apparel and accessories are the most purchased online in the United States. As of February 2023, roughly 18 percent of all fashion retail sales took place online. Furniture and home furnishing, as well as computer and consumer electronics, ranked second, with over 15 percent of each product category purchased via the internet. The product categories that are least purchased online are office equipment and supplies (1.4 percent) and books, music, and video (5.1 percent).

Shopping hotspots

Amazon dominates the e-commerce industry in the United States, though other competitors still have significant market share. In December 2023, amazon.com was the most-visited e-commerce and shopping site in the United States. That month, around 45 percent of all visits to e-commerce sites were made to Amazon. Other popular shopping sites include ebay.com, walmart.com, etsy.com, and target.com. The staggering proportion of online retail sales in the country attributed to Amazon is quite remarkable. In 2023, Amazon's website accounted for almost half of all online computer and consumer electronics sales. Similarly, nearly one-third of online fashion purchases in the country were made on Amazon.

Data Set Information:

This Online Retail II data set contains all the transactions occurring for a UK-based and registered, non-store online retail between 01/12/2009 and 09/12/2011.The company mainly sells unique all-occasion gift-ware. Many customers of the company are wholesalers.

Attribute Information:

InvoiceNo: Invoice number. Nominal. A 6-digit integral number uniquely assigned to each transaction. If this code starts with the letter 'c', it indicates a cancellation. StockCode: Product (item) code. Nominal. A 5-digit integral number uniquely assigned to each distinct product. Description: Product (item) name. Nominal. Quantity: The quantities of each product (item) per transaction. Numeric.
InvoiceDate: Invice date and time. Numeric. The day and time when a transaction was generated. UnitPrice: Unit price. Numeric. Product price per unit in sterling (£). CustomerID: Customer number. Nominal. A 5-digit integral number uniquely assigned to each customer. Country: Country name. Nominal. The name of the country where a customer resides.

Graph and download economic data for E-Commerce Retail Sales as a Percent of Total Sales (ECOMPCTNSA) from Q4 1999 to Q1 2025 about e-commerce, retail trade, percent, sales, retail, and USA.

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]

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

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.

China Online Retail Sales: Year to Date: Goods data was reported at 2,994.820 RMB bn in Mar 2025. This records an increase from the previous number of 1,863.260 RMB bn for Feb 2025. China Online Retail Sales: Year to Date: Goods data is updated monthly, averaging 3,682.600 RMB bn from Jun 2013 (Median) to Mar 2025, with 117 observations. The data reached an all-time high of 13,081.570 RMB bn in Dec 2024 and a record low of 399.100 RMB bn in Feb 2015. China Online Retail Sales: 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.

North America Online Retail Mobile Payment Transactions Market is expected to grow during 2025-2031