Introduction

Online Business Statistics: Today, shopping online is the most popular choice. eCommerce has made it much easier to buy everything from clothes and beauty products to home items and groceries. With just a few clicks, you can place an order and have it delivered right to your door, all without leaving your home. Many companies have gone digital, with some running entirely online.

This shift has led to a huge increase in online shopping. Nowadays, almost everyone buys something online at least once a day. To give you a better understanding of online shopping, we’ve gathered some interesting Online Business Statistics for 2025.

According to a survey conducted in the United States in January 2023, within the last year, ** percent of consumers used the internet to find a local business on a daily basis. Overall, ** percent of respondents stated that they used the internet for this purpose multiple times every week. Additionally, just two percent of those surveyed said that they didn't search for local businesses online.

Introduction

Small Business Statistics: To balance out every country's economy, small businesses are termed the backbone. Small businesses are types of corporations, partnerships, or sole proprietorships that are independently owned companies with fewer employees and lower revenue than large companies. Many small businesses are now utilising the internet and various digital tools to connect with customers, and many of them generate income by selling online.

This article includes several statistical analyses from different sources that will guide you in understanding the importance of small businesses' effectiveness in recent years.

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

A league table of the 120 cryptocurrencies with the highest market cap reveals how diverse each crypto is and potentially how much risk is involved when investing in one. Bitcoin (BTC), for instance, had a so-called "high cap" - a market cap worth more than 10 billion U.S. dollars - indicating this crypto project has a certain track record or, at the very least, is considered a major player in the cryptocurrency space. This is different in Decentralize Finance (DeFi), where Bitcoin is only a relatively new player. A concentrated market The number of existing cryptocurrencies is several thousands, even if most have a limited significance. Indeed, Bitcoin and Ethereum account for nearly 75 percent of the entire crypto market capitalization. As crypto is relatively easy to create, the range of projects varies significantly - from improving payments to solving real-world issues, but also meme coins and more speculative investments. Crypto is not considered a payment method While often talked about as an investment vehicle, cryptocurrencies have not yet established a clear use case in day-to-day life. Central bankers found that usefulness of crypto in domestic payments or remittances to be negligible. A forecast for the world's main online payment methods took a similar stance: It predicts that cryptocurrency would only take up 0.2 percent of total transaction value by 2027.

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

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.

Short-term business statistics (STS) give information on a wide range of economic activities. All STS data are index data. Additionally, annual absolute values are released for building permits indicators. Percentage changes are also available for each indicator: Infra-annual percentage changes - changes between two consecutive months or quarters - are calculated on the basis of non-adjusted data (prices) or calendar and seasonally adjusted data (volume and value indicators) and year-on-year changes - comparing a period to the same period one year ago - are calculated on the basis of non-adjusted data (prices and employment) or calendar adjusted data (volume and value indicators).

The index data are generally presented in the following forms:

• unadjusted
• calendar adjusted
• calendar and seasonally adjusted.

Depending on the EBS Regulation data are accessible as monthly, quarterly and annual data.

The STS indicators are listed below in five different sectors, reflecting the dissemination of these data in Eurostat’s online database “Eurobase”.

Based on the national data, Eurostat compiles short-term indicators for the EU and euro area. Among these, a list of indicators, called Principal European Economic Indicators (PEEIs) has been identified by key users as being of primary importance for the conduct of monetary and economic policy of the euro area. The PEEIs contributed by STS are marked with * in the text below.

The euro indicators are released through Eurostat's website.

INDUSTRY

• production (volume)*
• turnover: Total, Domestic market and Non-domestic market. A further breakdown of the non-domestic turnover into euro area and non-euro area is available for the euro area countries.
• producer prices (output prices)*: Total, Domestic market and Non-domestic market. A further breakdown of the non-domestic producer prices into euro area and non-euro area is available for the euro area countries.
• import prices*: Total, euro area market, Non euro area market (euro area countries only)
• labour input indicators: Number of employees and self-employed persons, Hours worked by employees, Gross wages and salaries

CONSTRUCTION

• production (volume)*
• building permits indicators*: number of dwellings, square meters of useful floor
• producer (output) prices in construction (if not available, they can be approximated by the construction costs variable)
• labour input indicators: number of employees and self-employed persons, hours worked by employees, gross wages and salaries

TRADE

• volume of sales (deflated turnover)*
• turnover (value)
• labour input indicators: number of employees and self-employed persons, hours worked by employees, gross wages and salaries

SERVICES

• production (volume)*
• turnover (in value)
• labour input indicators: number of employees and self-employed persons, hours worked by employees, gross wages and salaries
• producer prices (output prices)*

MARKET ECONOMY

• total market production (volume)
• registrations
• bankruptcies

National reference metadata of the reporting countries are available in the Annexes to this metadata file.

Online store owners across different regions have varying preferences when investing in apps. Our data reveals that United States is the leading destination for online businesses using apps, spending an impressive $1.58B per month. Online business owners in United Kingdom and Canada are also passionate about leveraging apps, with monthly app expenditure of $267.55M and $204.96M respectively. Additionally, Australia and Germany contribute significantly as well, representing a combined 8.41% of global monthly app spending.

Short-term business statistics (STS) give information on a wide range of economic activities. All STS data are index data. Additionally, annual absolute values are released for building permits indicators. Percentage changes are also available for each indicator: Infra-annual percentage changes - changes between two consecutive months or quarters - are calculated on the basis of non-adjusted data (prices) or calendar and seasonally adjusted data (volume and value indicators) and year-on-year changes - comparing a period to the same period one year ago - are calculated on the basis of non-adjusted data (prices and employment) or calendar adjusted data (volume and value indicators).

The index data are generally presented in the following forms:

• unadjusted
• calendar adjusted
• calendar and seasonally adjusted.

Depending on the EBS Regulation data are accessible as monthly, quarterly and annual data.

The STS indicators are listed below in five different sectors, reflecting the dissemination of these data in Eurostat’s online database “Eurobase”.

Based on the national data, Eurostat compiles short-term indicators for the EU and euro area. Among these, a list of indicators, called Principal European Economic Indicators (PEEIs) has been identified by key users as being of primary importance for the conduct of monetary and economic policy of the euro area. The PEEIs contributed by STS are marked with * in the text below.

The euro indicators are released through Eurostat's website.

INDUSTRY

• production (volume)*
• turnover: Total, Domestic market and Non-domestic market. A further breakdown of the non-domestic turnover into euro area and non-euro area is available for the euro area countries.
• producer prices (output prices)*: Total, Domestic market and Non-domestic market. A further breakdown of the non-domestic producer prices into euro area and non-euro area is available for the euro area countries.
• import prices*: Total, euro area market, Non euro area market (euro area countries only)
• labour input indicators: Number of employees and self-employed persons, Hours worked by employees, Gross wages and salaries

CONSTRUCTION

• production (volume)*
• building permits indicators*: number of dwellings, square meters of useful floor
• producer (output) prices in construction (if not available, they can be approximated by the construction costs variable)
• labour input indicators: number of employees and self-employed persons, hours worked by employees, gross wages and salaries

TRADE

• volume of sales (deflated turnover)*
• turnover (value)
• labour input indicators: number of employees and self-employed persons, hours worked by employees, gross wages and salaries

SERVICES

• production (volume)*
• turnover (in value)
• labour input indicators: number of employees and self-employed persons, hours worked by employees, gross wages and salaries
• producer prices (output prices)*

MARKET ECONOMY

• total market production (volume)
• registrations
• bankruptcies

National reference metadata of the reporting countries are available in the Annexes to this metadata file.

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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.

Business Software Alliance is a trade association that represents the world's leading software companies, including Autodesk, IBM, and Symantec. The organization's members are committed to promoting the use of legitimate software and ensuring the integrity of their intellectual property.

As a result, the data housed on BSA's website is rich in information related to the software industry, including software licensing, anti-piracy efforts, and digital piracy statistics. The data includes information on software usage, software development, and the impact of piracy on the technology industry. With its focus on promoting legitimate software use, the data on BSA's website provides valuable insights into the global software industry.

Short-term business statistics (STS) give information on a wide range of economic activities. All STS data are index data. Additionally, annual absolute values are released for building permits indicators. Percentage changes are also available for each indicator: Infra-annual percentage changes - changes between two consecutive months or quarters - are calculated on the basis of non-adjusted data (prices) or calendar and seasonally adjusted data (volume and value indicators) and year-on-year changes - comparing a period to the same period one year ago - are calculated on the basis of non-adjusted data (prices and employment) or calendar adjusted data (volume and value indicators).

The index data are generally presented in the following forms:

• unadjusted
• calendar adjusted
• calendar and seasonally adjusted.

Depending on the EBS Regulation data are accessible as monthly, quarterly and annual data.

The STS indicators are listed below in five different sectors, reflecting the dissemination of these data in Eurostat’s online database “Eurobase”.

Based on the national data, Eurostat compiles short-term indicators for the EU and euro area. Among these, a list of indicators, called Principal European Economic Indicators (PEEIs) has been identified by key users as being of primary importance for the conduct of monetary and economic policy of the euro area. The PEEIs contributed by STS are marked with * in the text below.

The euro indicators are released through Eurostat's website.

INDUSTRY

• production (volume)*
• turnover: Total, Domestic market and Non-domestic market. A further breakdown of the non-domestic turnover into euro area and non-euro area is available for the euro area countries.
• producer prices (output prices)*: Total, Domestic market and Non-domestic market. A further breakdown of the non-domestic producer prices into euro area and non-euro area is available for the euro area countries.
• import prices*: Total, euro area market, Non euro area market (euro area countries only)
• labour input indicators: Number of employees and self-employed persons, Hours worked by employees, Gross wages and salaries

CONSTRUCTION

• production (volume)*
• building permits indicators*: number of dwellings, square meters of useful floor
• producer (output) prices in construction (if not available, they can be approximated by the construction costs variable)
• labour input indicators: number of employees and self-employed persons, hours worked by employees, gross wages and salaries

TRADE

• volume of sales (deflated turnover)*
• turnover (value)
• labour input indicators: number of employees and self-employed persons, hours worked by employees, gross wages and salaries

SERVICES

• production (volume)*
• turnover (in value)
• labour input indicators: number of employees and self-employed persons, hours worked by employees, gross wages and salaries
• producer prices (output prices)*

MARKET ECONOMY

• total market production (volume)
• registrations
• bankruptcies

National reference metadata of the reporting countries are available in the Annexes to this metadata file.

Comprehensive dataset containing 2,341 verified Internet shop businesses in United States with complete contact information, ratings, reviews, and location data.

Increase the percentage of business filing transactions processed online from 33% in 2014 to 50% by 2018.

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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For more datasets, click here.

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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...

Discover the booming global dropshipping market! This comprehensive analysis reveals a $337.46 million market in 2025, projected to reach billions by 2033, driven by e-commerce growth and low barriers to entry. Explore key trends, segments (electronics, fashion, toys), top companies, and regional insights to understand this lucrative opportunity. Key drivers for this market are: 4., Increasing International Trade Driving the Market4.; Increasing online users driving the market. Potential restraints include: 4., Regulatory Compliance Affecting the Market4.; High Competition in the Market. Notable trends are: Immense Growth is Projected for the Electronics and Media Segment.

Comprehensive dataset containing 39,070 verified Internet marketing service businesses in United States with complete contact information, ratings, reviews, and location data.