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.

Asia leads globally in e-commerce, exceeding *** trillion U.S. dollars in volume in 2024. The United States ranked second with over ************ U.S. dollars in market volume, and Europe came next, with a market volume of *** billion U.S. dollars in the same year. U.S. e-commerce: A growing slice of the retail pie While the United States maintains a strong position in the global e-retail market, there's still considerable room for expansion. E-commerce sales in the U.S. reached a record high of over *** billion dollars in the second quarter of 2024, accounting for ** percent of total retail sales. This represents a steady increase from previous years, yet indicates that traditional brick-and-mortar retail still dominates the American market. Latin America: An emerging e-commerce frontier Latin America is rapidly emerging as a key player in the global e-retail landscape, with a projected market volume of *** billion U.S. dollars by 2024. Brazil and Mexico lead the region, accounting for ** percent and ** percent of the Latin American e-commerce market, respectively. The region is also seeing a gradual increase in cross-border online sales, expected to reach ** percent of total e-commerce by 2025. Mobile commerce is proving to be a game-changer in Latin America, with m-commerce sales tripling since 2019 to reach approximately ** billion U.S. dollars by the end of 2024.

Graph and download economic data for E-Commerce Retail Sales (ECOMSA) from Q4 1999 to Q2 2025 about e-commerce, retail trade, sales, retail, and USA.

Synthetic E-Commerce Sales Dataset (2025) Realistic, clean, and ready-to-use synthetic dataset for machine learning, forecasting, and data analysis. Overview

This dataset contains 100,000 simulated e-commerce transactions generated with Python’s Faker and NumPy libraries. It replicates realistic global online shopping behavior between 2023 and 2025, including product categories, customer feedback, payment preferences, and delivery times.

The dataset is fully synthetic — no real user data, privacy-friendly, and designed for AI, analytics, and visualization projects.

Dataset Highlights

Global coverage: Sales from six regions (Europe, Asia, North America, etc.)

Diverse payment methods: CreditCard, PayPal, BankTransfer, Cash

Product variety: 7 major categories such as Electronics, Fashion, and Home

Seasonal patterns: November sales spike (Black Friday effect)

Realistic return rates: Fashion products have a higher return ratio

Date range: January 2023 – December 2025

Suitable for: Regression, classification, feature engineering, and forecasting

In 2024, global e-commerce sales grew by *** percent compared to the previous year. In that period, e-commerce accounted for approximately ** percent of all retail sales worldwide. Asian countries lead the way According to an estimate, China and Indonesia ranked **************** respectively on the list of countries with the greatest share of retail sales projected to take place online in 2023. Following the same trend, estimates also revealed that the three fastest-growing retail e-commerce countries in the world are all in Asia. Amazon on top When looking at the leading e-commerce companies worldwide, as opposed to the leading e-commerce countries, ****** is the clear market leader with a market cap of over************n U.S. dollars as of March 2025. Not only that, but the *************************** company is also by far the***** visited online marketplace in the world, with approximately *** billion monthly visits.

Use of information and communication technology (ICT) and e-commerce activity by UK businesses. Annual data on e-commerce sales and how businesses are using the internet.

E-Commerce Sales Dataset

Analyzing and Maximizing Online Business Performance

By ANil [source]

About this dataset

This dataset provides an in-depth look at the profitability of e-commerce sales. It contains data on a variety of sales channels, including Shiprocket and INCREFF, as well as financial information on related expenses and profits. The columns contain data such as SKU codes, design numbers, stock levels, product categories, sizes and colors. In addition to this we have included the MRPs across multiple stores like Ajio MRP , Amazon MRP , Amazon FBA MRP , Flipkart MRP , Limeroad MRP Myntra MRP and PaytmMRP along with other key parameters like amount paid by customer for the purchase , rate per piece for every individual transaction Also we have added transactional parameters like Date of sale months category fulfilledby B2b Status Qty Currency Gross amt . This is a must-have dataset for anyone trying to uncover the profitability of e-commerce sales in today's marketplace

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How to use the dataset

This dataset provides a comprehensive overview of e-commerce sales data from different channels covering a variety of products. Using this dataset, retailers and digital marketers can measure the performance of their campaigns more accurately and efficiently.

The following steps help users make the most out of this dataset: - Analyze the general sales trends by examining info such as month, category, currency, stock level, and customer for each sale. This will give you an idea about how your e-commerce business is performing in each channel.
- Review the Shiprocket and INCREF data to compare and analyze profitability via different fulfilment methods. This comparison would enable you to make better decisions towards maximizing profit while minimizing costs associated with each method’s referral fees and fulfillment rates.
- Compare prices between various channels such as Amazon FBA MRP, Myntra MRP, Ajio MRP etc using the corresponding columns for each store (Amazon MRP etc). You can judge which stores are offering more profitable margins without compromising on quality by analyzing these pricing points in combination with other information related to product sales (TP1/TP2 - cost per piece).
- Look at customer specific data such as TP 1/TP 2 combination wise Gross Amount or Rate info in terms price per piece or total gross amount generated by any SKU dispersed over multiple customers with relevant dates associated to track individual item performance relative to others within its category over time periods shortlisted/filtered appropriately.. Have an eye on items commonly utilized against offers or promotional discounts offered hence crafting strategies towards inventory optimization leading up-selling operations.?
- Finally Use Overall ‘Stock’ details along all the P & L Data including Yearly Expenses_IIGF information record for takeaways which might be aimed towards essential cost cutting measures like switching amongst delivery options carefully chosen out of Shiprocket & INCREFF leadings away from manual inspections catering savings under support personnel outsourcing structures.?

By employing a comprehensive understanding on how our internal subsidiaries perform globally unless attached respective audits may provide us remarkably lower operational costs servicing confidence; costing far lesser than being incurred taking into account entire pallet shipments tracking sheets representing current level supply chains efficiencies achieved internally., then one may finally scale profits exponentially increases cut down unseen losses followed up introducing newer marketing campaigns necessarily tailored according playing around multiple goods based spectrums due powerful backing suitable transportation boundaries set carefully

Research Ideas

• Analysing the difference in profitability between sales made through Shiprocket and INCREFF. This data can be used to see where the biggest profit margins lie, and strategize accordingly.
• Examining the Complete Cost structure of a product with all its components and their contribution towards revenue or profitability, i.e., TP 1 & 2, MRP Old & Final MRP Old together with Platform based MRP - Amazon, Myntra and Paytm etc., Currency based Profit Margin etc.
• Building a predictive model using Machine Learning by leveraging historical data to predict future sales volume and profits for e-commerce products across multiple categories/devices/platforms such as Amazon, Flipkart, Myntra etc as well providing m...

According to Cognitive Market Research, the global cross-border e-commerce market size is USD 791542.2 million in 2024 and will expand at a compound annual growth rate (CAGR) of 30.50% from 2024 to 2031.

North America held the major market of more than 40%of the global revenue with a market size of USD 316616.88million in 2024 and will grow at a compound annual growth rate (CAGR) of 28.7%from 2024 to 2031.
Europe accounted for a share of over 30% of the global market size of USD 237462.66million.
Asia Pacific held the market of around 23% of the global revenue with a market size of USD 182054.71million in 2024 and will grow at a compound annual growth rate (CAGR) of 32.5%from 2024 to 2031.
Latin America's market will have more than 5% of the global revenue with a market size of USD 39577.11million in 2024 and will grow at a compound annual growth rate (CAGR) of 29.9%from 2024 to 2031.
Middle East and Africa are the major markets of around 2% of the global revenue with a market size of USD 15830.84 million in 2024 and will grow at a compound annual growth rate (CAGR) of 30.2%from 2024 to 2031.
The Credit/Debit Cards held the highest Cross border E commerce market revenue share in 2024.

Key Drivers of Cross border E commerce Market

Increasing Internet Penetration and Smartphone Adoption to Increase the Demand Globally

One of the key drivers in the cross-border e-commerce market is the increasing internet penetration and smartphone adoption worldwide. As more people gain access to the internet and smartphones, the potential customer base for online shopping expands, leading to a surge in cross-border e-commerce activities. The convenience of shopping online from international retailers, coupled with the availability of a wide range of products and competitive prices, has fueled the growth of cross-border e-commerce. Moreover, the ease of payment through digital wallets and online payment platforms has further facilitated cross-border transactions. This trend is expected to continue as internet infrastructure improves and smartphone technology becomes more affordable, driving the growth of cross-border e-commerce.

Growing Preference for Global Brands and Product Variety to Propel Market Growth

Another key driver in the cross-border e-commerce market is the growing preference among consumers for global brands and a wider variety of products. Cross-border e-commerce allows consumers to access products that may not be available in their local markets, giving them access to a broader selection of goods from around the world. This has led to an increase in demand for international brands and niche products that cater to specific interests and preferences. Additionally, cross-border e-commerce offers consumers the opportunity to compare prices and quality across different markets, empowering them to make informed purchasing decisions. As a result, retailers are increasingly focusing on expanding their product offerings and improving the shopping experience for cross-border shoppers, driving the growth of cross-border e-commerce.

Restraint Factors Of Cross border E commerce Market

Complex Regulatory Environment to Limit the Sales

One of the key restraints in the cross-border e-commerce market is the complex regulatory environment governing international trade and e-commerce. Different countries have varying regulations and policies regarding taxes, customs duties, import/export restrictions, and consumer protection laws, which can create barriers for cross-border e-commerce businesses. Adhering to these regulations can be challenging for e-commerce companies, especially smaller businesses that may not have the resources to navigate the complexities of international trade laws. This can result in delays, additional costs, and legal issues, limiting the growth of cross-border e-commerce.

Logistics Challenges and High International Shipping Costs

A major restraint in the cross-border e-commerce market is the inefficiency and high cost of international logistics. Delivering products across borders involves dealing with multiple carriers, customs delays, varying delivery standards, and return complications—all of which increase the total shipping time and expense. For consumers, this often translates into higher prices and uncertainty around delivery timelines, which can discourage repeat purchases. For sellers...

In 2019, Amazon was estimated to have generated over 346 billion U.S. dollars in retail e-commerce sales annually. E-retail sales of the company are projected to reach 468.78 billion U.S. dollars in 2021.Amazon is the world's largest online marketplace as measured by revenue and market capitalization.

Mexico leads the eCommerce industry, achieving remarkable success with monthly sales of $5.49T. This solidifies its dominant market position, capturing a significant 20.01% share. Following closely behind is Nicaragua, which achieved monthly sales of $5.08T, accounting for 18.52% of the global eCommerce market. Ranking third among the top performers is United States, contributing 10.84% to the monthly eCommerce sales worldwide. Noteworthy mentions go to Italy, Canada and India, as they also hold substantial market shares.

CE Vision is the premier alternative data set tracking credit & debit consumer spend in Europe. Clients use CE Vision global retail & ecommerce sales data for market research and competitive intelligence analysis public & private company growth and macro trends by country.

China E-commerce: Sales Revenue: YoY: Year to Date: Business to Business data was reported at 25.400 % in Jun 2017. This records an increase from the previous number of 18.180 % for Dec 2016. China E-commerce: Sales Revenue: YoY: Year to Date: Business to Business data is updated quarterly, averaging 25.650 % from Dec 2010 (Median) to Jun 2017, with 14 observations. The data reached an all-time high of 36.000 % in Dec 2011 and a record low of -13.700 % in Dec 2015. China E-commerce: Sales Revenue: YoY: Year to Date: Business to Business data remains active status in CEIC and is reported by China e-business Research Center. The data is categorized under China Premium Database’s Information and Communication Sector – Table CN.ICG: E-commerce: Business Sales Revenue.

Canada Retail E-Commerce Sales data was reported at 4,425,564.000 CAD th in Dec 2022. This records a decrease from the previous number of 4,499,923.000 CAD th for Nov 2022. Canada Retail E-Commerce Sales data is updated monthly, averaging 1,878,200.500 CAD th from Jan 2016 (Median) to Dec 2022, with 84 observations. The data reached an all-time high of 4,943,411.000 CAD th in Dec 2020 and a record low of 789,553.000 CAD th in Feb 2016. Canada Retail E-Commerce Sales data remains active status in CEIC and is reported by Statistics Canada. The data is categorized under Global Database’s Canada – Table CA.H021: Retail E-Commerce Sales.

In 2024, the United States ranked first by revenue in the e-commerce market among the 10 countries presented in the ranking. United States' revenue amounted to ************* U.S. dollars, while China and Japan, the second and third countries, had records amounting to ************* U.S. dollars and ************** U.S. dollars, respectively.Further information about the methodology, more market segments, and metrics can be found on the dedicated Market Insights page on eCommerce.

China E-commerce: Sales Revenue: Year to Date: Business to Business data was reported at 16.800 RMB bn in Jun 2017. This records a decrease from the previous number of 26.000 RMB bn for Dec 2016. China E-commerce: Sales Revenue: Year to Date: Business to Business data is updated quarterly, averaging 11.500 RMB bn from Jun 2010 (Median) to Jun 2017, with 19 observations. The data reached an all-time high of 26.000 RMB bn in Dec 2016 and a record low of 2.960 RMB bn in Mar 2011. China E-commerce: Sales Revenue: Year to Date: Business to Business data remains active status in CEIC and is reported by China e-business Research Center. The data is categorized under China Premium Database’s Information and Communication Sector – Table CN.ICG: E-commerce: Business Sales Revenue.

Introduction

This dataset is a synthetic e-commerce dataset designed to provide a comprehensive view of transaction, customer, product, and advertising data in a dynamic marketplace. It simulates real-world scenarios with seasonal effects, regional variations, advertising metrics, and customer purchasing behaviors. This dataset can serve as a valuable resource for exploring e-commerce analytics, customer segmentation, product performance, and marketing effectiveness.

The dataset includes detailed transaction-level data featuring product categories, customer demographics, discounts, revenue, and advertising metrics such as impressions, clicks, conversion rates, and ad spend. Seasonal trends and regional multipliers are integrated into the data to create realistic patterns that mimic consumer behavior across different times of the year and geographic regions.

Potential Analyses

1. Customer Insights

• Perform customer segmentation based on demographics, lifetime value, and purchase behavior.
• Analyze trends in customer behavior across regions or product categories.

2. Product Performance

• Identify top-performing products by revenue or units sold.
• Evaluate the impact of discounts and promotions on product sales.

3. Marketing Analytics

• Measure the effectiveness of advertising using CTR, CPC, and conversion rates.
• Assess how ad spend correlates with revenue and impressions.

4. Seasonal Trends

• Analyze seasonality effects on sales volume and revenue.
• Explore spikes in revenue or sales during holiday periods.

5. Regional Analysis

• Investigate regional performance trends using the regional multipliers.
• Examine customer preferences across different regions.

6. Data Science Applications

• Build predictive models for sales forecasting.
• Create clustering models for customer segmentation or product categorization.
• Develop optimization strategies for advertising spend or inventory management.

This dataset provides ample opportunities for data exploration, machine learning, and business analysis. We hope you find it insightful and useful for your projects!

😍Upvote and share this would help me alot Thank You!

Description: The E-commerce Sales Data dataset provides a comprehensive collection of information related to user profiles, product details, and user-product interactions. It is a valuable resource for understanding customer behavior, preferences, and purchasing trends on an e-commerce platform.

Dataset Structure:

User Sheet: This sheet contains user profiles, including details such as user ID, name, age, location, and other relevant information. It helps in understanding the demographics and characteristics of the platform's users.

Product Sheet: The product sheet offers insights into the various products available on the e-commerce platform. It includes product IDs, names, categories, prices, descriptions, and other product-specific attributes.

Interactions Sheet: The interactions sheet is a crucial component of the dataset, capturing the interactions between users and products. It records details of user actions, such as product views, purchases, reviews, and ratings. This data is essential for building recommendation systems and understanding user preferences.

Potential Use Cases:

Recommendation Systems: With the user-product interaction data, this dataset is ideal for building recommendation systems. It allows the development of personalized product recommendations to enhance the user experience.

Market Basket Analysis: The dataset can be used for market basket analysis to understand which products are frequently purchased together, aiding in inventory management and targeted marketing.

User Behavior Analysis: By analyzing user interactions, you can gain insights into user behavior, such as popular product categories, browsing patterns, and the impact of user reviews and ratings on purchasing decisions.

Targeted Marketing: The dataset can inform marketing strategies, enabling businesses to tailor promotions and advertisements to specific user segments and product categories.

This E-commerce Sales Data dataset is a valuable resource for e-commerce platforms and data scientists seeking to optimize the shopping experience, enhance customer satisfaction, and drive business growth through data-driven insights.

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

Global e-commerce market worth at USD 16790.46 Billion in 2024, is expected to surpass USD 67926.78 Billion by 2034, CAGR of 15% from 2025 to 2034.

China E-commerce: Sales Revenue: Year to Date data was reported at 6,790.000 RMB bn in 2022. This records an increase from the previous number of 6,400.000 RMB bn for 2021. China E-commerce: Sales Revenue: Year to Date data is updated yearly, averaging 3,520.000 RMB bn from Dec 2014 (Median) to 2022, with 9 observations. The data reached an all-time high of 6,790.000 RMB bn in 2022 and a record low of 1,250.000 RMB bn in 2014. China E-commerce: Sales Revenue: Year to Date data remains active status in CEIC and is reported by Ministry of Commerce. The data is categorized under China Premium Database’s Information and Communication Sector – Table CN.ICG: E-commerce: Business Sales Revenue.