Unlock the door to business expansion by investing in our real-time eCommerce leads list. Gain direct access to store owners and make informed decisions with data fields including Store Name, Website, Contact First Name, Contact Last Name, Email Address, Physical Address, City, State, Country, Zip Code, Phone Number, Revenue Size, Employee Size, and more on demand.
Ensure a lifetime of access for continuous growth and tailor your campaigns with accurate and reliable information, initiating targeted efforts that align with your marketing goals. Whether you're targeting specific industries or global locations, our database provides up-to-date and valuable insights to support your business journey.
• 4M+ eCommerce Companies • 40M+ Worldwide eCommerce Leads • Direct Contact Info for Shop Owners • 47+ eCommerce Platforms • 40+ Data Points • Lifetime Access • 10+ Data Segmentations • Sample Data
Discover the unparalleled potential of our comprehensive eCommerce leads database, featuring essential data fields such as Store Name, Website, Contact First Name, Contact Last Name, Email Address, Physical Address, City, State, Country, Zip Code, Phone Number, Revenue Size, Employee Size, and more on demand.
With a focus on Shopify, Amazon, eBay, and other global retail stores, this database equips you with accurate information for successful marketing campaigns. Supercharge your marketing efforts with our enriched contact and company database, providing real-time, verified data insights for strategic market assessments and effective buyer engagement across digital and traditional channels.
• 4M+ eCommerce Companies • 40M+ Worldwide eCommerce Leads • Direct Contact Info for Shop Owners • 47+ eCommerce Platforms • 40+ Data Points • Lifetime Access • 10+ Data Segmentations • Sample Data"
MIT Licensehttps://opensource.org/licenses/MIT
License information was derived automatically
• I leveraged advanced data visualization techniques to extract valuable insights from a comprehensive dataset. By visualizing sales patterns, customer behavior, and product trends, I identified key growth opportunities and provided actionable recommendations to optimize business strategies and enhance overall performance. you can find the GitHub repo here Link to GitHub Repository.
there are exactly 6 table and 1 is a fact table and the rest of them are dimension tables: Fact Table:
payment_key:
Description: An identifier representing the payment transaction associated with the fact.
Use Case: This key links to a payment dimension table, providing details about the payment method and related information.
customer_key:
Description: An identifier representing the customer associated with the fact.
Use Case: This key links to a customer dimension table, providing details about the customer, such as name, address, and other customer-specific information.
time_key:
Description: An identifier representing the time dimension associated with the fact.
Use Case: This key links to a time dimension table, providing details about the time of the transaction, such as date, day of the week, and month.
item_key:
Description: An identifier representing the item or product associated with the fact.
Use Case: This key links to an item dimension table, providing details about the product, such as category, sub-category, and product name.
store_key:
Description: An identifier representing the store or location associated with the fact.
Use Case: This key links to a store dimension table, providing details about the store, such as location, store name, and other store-specific information.
quantity:
Description: The quantity of items sold or involved in the transaction.
Use Case: Represents the amount or number of items associated with the transaction.
unit:
Description: The unit or measurement associated with the quantity (e.g., pieces, kilograms).
Use Case: Specifies the unit of measurement for the quantity.
unit_price:
Description: The price per unit of the item.
Use Case: Represents the cost or price associated with each unit of the item.
total_price:
Description: The total price of the transaction, calculated as the product of quantity and unit price.
Use Case: Represents the overall cost or revenue generated by the transaction.
Customer Table: customer_key:
Description: An identifier representing a unique customer.
Use Case: Serves as the primary key to link with the fact table, allowing for easy and efficient retrieval of customer-specific information.
name:
Description: The name of the customer.
Use Case: Captures the personal or business name of the customer for identification and reference purposes.
contact_no:
Description: The contact number associated with the customer.
Use Case: Stores the phone number or contact details for communication or outreach purposes.
nid:
Description: The National ID (NID) or a unique identification number for the customer.
Item Table: item_key:
Description: An identifier representing a unique item or product.
Use Case: Serves as the primary key to link with the fact table, enabling retrieval of detailed information about specific items in transactions.
item_name:
Description: The name or title of the item.
Use Case: Captures the descriptive name of the item, providing a recognizable label for the product.
desc:
Description: A description of the item.
Use Case: Contains additional details about the item, such as features, specifications, or any relevant information.
unit_price:
Description: The price per unit of the item.
Use Case: Represents the cost or price associated with each unit of the item.
man_country:
Description: The country where the item is manufactured.
Use Case: Captures the origin or manufacturing location of the item.
supplier:
Description: The supplier or vendor providing the item.
Use Case: Stores the name or identifier of the supplier, facilitating tracking of item sources.
unit:
Description: The unit of measurement associated with the item (e.g., pieces, kilograms).
Store Table: store_key:
Description: An identifier representing a unique store or location.
Use Case: Serves as the primary key to link with the fact table, allowing for easy retrieval of information about transactions associated with specific stores.
division:
Description: The administrative division or region where the store is located.
Use Case: Captures the broader geographical area in which...
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
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.
By ANil [source]
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
For more datasets, click here.
- 🚨 Your notebook can be here! 🚨!
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
- 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...
Success.ai’s Ecommerce Store Data for the APAC E-commerce Sector provides a reliable and accurate dataset tailored for businesses aiming to connect with e-commerce professionals and organizations across the Asia-Pacific region. Covering roles and businesses involved in online retail, marketplace management, logistics, and digital commerce, this dataset includes verified business profiles, decision-maker contact details, and actionable insights.
With access to continuously updated, AI-validated data and over 700 million global profiles, Success.ai ensures your outreach, market analysis, and partnership strategies are effective and data-driven. Backed by our Best Price Guarantee, this solution helps you excel in one of the world’s fastest-growing e-commerce markets.
Why Choose Success.ai’s Ecommerce Store Data?
Verified Profiles for Precision Engagement
Comprehensive Coverage of the APAC E-commerce Sector
Continuously Updated Datasets
Ethical and Compliant
Data Highlights:
Key Features of the Dataset:
Comprehensive E-commerce Business Profiles
Advanced Filters for Precision Campaigns
Regional and Sector-specific Insights
AI-Driven Enrichment
Strategic Use Cases:
Marketing Campaigns and Outreach
Partnership Development and Vendor Collaboration
Market Research and Competitive Analysis
Recruitment and Talent Acquisition
Why Choose Success.ai?
Best Price Guarantee
Seamless Integration
Revolutionize Customer Engagement with Our Comprehensive Ecommerce Data
Our Ecommerce Data is designed to elevate your customer engagement strategies, providing you with unparalleled insights and precision targeting capabilities. With over 61 million global contacts, this dataset goes beyond conventional data, offering a unique blend of shopping cart links, business emails, phone numbers, and LinkedIn profiles. This comprehensive approach ensures that your marketing strategies are not just effective but also highly personalized, enabling you to connect with your audience on a deeper level.
What Makes Our Ecommerce Data Stand Out?
Unique Features for Enhanced Targeting
Our Ecommerce Data is distinguished by its depth and precision. Unlike many other datasets, it includes shopping cart links—a rare and valuable feature that provides you with direct insights into consumer behavior and purchasing intent. This information allows you to tailor your marketing efforts with unprecedented accuracy. Additionally, the integration of business emails, phone numbers, and LinkedIn profiles adds multiple layers to traditional contact data, enriching your understanding of clients and enabling more personalized engagement.
Robust and Reliable Data Sourcing
We pride ourselves on our dual-sourcing strategy that ensures the highest levels of data accuracy and relevance:
Primary Use Cases Across Industries
Our Ecommerce Data is versatile and can be leveraged across various industries for multiple applications: - Precision Targeting in Marketing: Create personalized marketing campaigns based on detailed shopping cart activities, ensuring that your outreach resonates with individual customer preferences. - Sales Enrichment: Sales teams can benefit from enriched client profiles that include comprehensive contact information, enabling them to connect with key decision-makers more effectively. - Market Research and Analytics: Research and analytics departments can use this data for in-depth market studies and trend analyses, gaining valuable insights into consumer behavior and market dynamics.
Global Coverage for Comprehensive Engagement
Our Ecommerce Data spans across the globe, providing you with extensive reach and the ability to engage with customers in diverse regions: - North America: United States, Canada, Mexico - Europe: United Kingdom, Germany, France, Italy, Spain, Netherlands, Sweden, and more - Asia: China, Japan, India, South Korea, Singapore, Malaysia, and more - South America: Brazil, Argentina, Chile, Colombia, and more - Africa: South Africa, Nigeria, Kenya, Egypt, and more - Australia and Oceania: Australia, New Zealand - Middle East: United Arab Emirates, Saudi Arabia, Israel, Qatar, and more
Comprehensive Employee and Revenue Size Information
Our dataset also includes detailed information on: - Employee Size: Whether you’re targeting small businesses or large corporations, our data covers all employee sizes, from startups to global enterprises. - Revenue Size: Gain insights into companies across various revenue brackets, enabling you to segment the market more effectively and target your efforts where they will have the most impact.
Seamless Integration into Broader Data Offerings
Our Ecommerce Data is not just a standalone product; it is a critical piece of our broader data ecosystem. It seamlessly integrates with our comprehensive suite of business and consumer datasets, offering you a holistic approach to data-driven decision-making: - Tailored Packages: Choose customized data packages that meet your specific business needs, combining Ecommerce Data with other relevant datasets for a complete view of your market. - Holistic Insights: Whether you are looking for industry-specific details or a broader market overview, our integrated data solutions provide you with the insights necessary to stay ahead of the competition and make informed business decisions.
Elevate Your Business Decisions with Our Ecommerce Data
In essence, our Ecommerce Data is more than just a collection of contacts—it’s a strategic tool designed to give you a competitive edge in understanding and engaging your target audience. By leveraging the power of this comprehensive dataset, you can elevate your business decisions, enhance customer interactions, and navigate the digital landscape with confidence and insight.
With a market cap of over two trillion U.S. dollars, Amazon ranks first among the leading large cap e-commerce companies worldwide. According to March 2025 data, the e-commerce giant ranks ahead of Alibaba and Pinduoduo. During the measured period, Alibaba's market cap amounted to over 300 billion U.S. dollars. Amazon is one of the most valuable brands worldwide Ranked fourth out of the leading brands worldwide, Amazon continues to grow, with its brand value estimated at 577 billion U.S. dollars. Amazon.com was founded in 1994 and has since become one of the world’s largest e-commerce retailers selling goods like books, clothing, electronics, and even having its own subscription service, Amazon Prime. In 2024, the company achieved a net sales revenue of 638 billion U.S. dollars, showing its continued profitability. Despite its worldwide popularity, Amazon’s annual net sales revenue is remarkably higher in North America (388 billion U.S. dollars) when compared to how the company performs internationally (143 billion U.S. dollars). A closer look at Amazon's third-party sellers Most of Amazon's units (62 percent) are sold by third-party (3P) sellers, meaning independent sellers who list and sell products on the marketplace but do not sell the products to the platform itself. In 2024, Amazon made 156 billion U.S. dollars in global net revenue from 3P sales alone. However, in Amazon's biggest market, the United States, most sellers use a hybrid model (74 percent), this includes both 3P and first-party (1P) sellers, with the latter being a business or manufacturer that sells its products directly to a retailer or platform.
Success.ai’s Ecommerce Market Data for South-east Asia E-commerce Contacts provides a robust and accurate dataset tailored for businesses and organizations looking to connect with professionals in the fast-growing e-commerce industry across South-east Asia. Covering roles such as e-commerce managers, digital strategists, logistics experts, and online marketplace leaders, this dataset offers verified contact details, professional insights, and actionable market data.
With access to over 170 million verified profiles globally, Success.ai ensures your outreach, marketing, and research strategies are powered by accurate, continuously updated, and AI-validated data. Backed by our Best Price Guarantee, this solution empowers you to excel in one of the world’s most dynamic e-commerce regions.
Why Choose Success.ai’s Ecommerce Market Data?
Verified Contact Data for Precision Outreach
Comprehensive Coverage of South-east Asia’s E-commerce Market
Continuously Updated Datasets
Ethical and Compliant
Data Highlights:
Key Features of the Dataset:
Comprehensive Professional Profiles in E-commerce
Advanced Filters for Precision Campaigns
Regional and Market-specific Insights
AI-Driven Enrichment
Strategic Use Cases:
Marketing Campaigns and Digital Outreach
Market Research and Competitive Analysis
Partnership Development and Vendor Collaboration
Recruitment and Talent Acquisition
Why Choose Success.ai?
Best Price Guarantee
Seamless Integration
Based on June 2023 data, JD Health claimed the top spot among global e-commerce companies dedicated to a single vertical or sector, with a market capitalization of around ** billion U.S. dollars. Following closely behind was Wayfair, with a market cap of *** billion dollars, trailed by Ocado at nearly *** billion dollars and HelloFresh at approximately *** billion.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
United Kingdom E Commerce: Business With Website data was reported at 82.000 % in 2017. This records a decrease from the previous number of 83.700 % for 2016. United Kingdom E Commerce: Business With Website data is updated yearly, averaging 80.300 % from Dec 2007 (Median) to 2017, with 11 observations. The data reached an all-time high of 83.700 % in 2016 and a record low of 70.000 % in 2007. United Kingdom E Commerce: Business With Website data remains active status in CEIC and is reported by Office for National Statistics. The data is categorized under Global Database’s United Kingdom – Table UK.S033: E Commerce: Proportion of Businesses With a Website.
https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain
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.
In 2024, half of the B2B e-commerce companies collected and analysed data in the Nordics, a survey revealed. However, around 20 percent of B2B e-commerce companies taking part in the survey did not make active use of user data.
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.
Discover Retail Store Data for Asia’s retail and e-commerce industries. Includes verified contact data, business histories, and market insights from 70M+ businesses. Best price guaranteed.
https://www.ibisworld.com/about/termsofuse/https://www.ibisworld.com/about/termsofuse/
E-commerce companies sell various goods and associated services through online portals, either on websites, mobile apps or integrated into social media platforms. Internet access across Europe continues to accelerate, with the vast majority of countries boasting usage rates of over 80% of the population. The spread of fast broadband and mobile data has enabled rising numbers of Europeans to engage in e-shopping. Over the five years through 2025, e-commerce revenue is slated to climb at a compound annual rate of 4% to reach €352.5 billion. E-tailers benefit from lower overhead costs than bricks-and-mortar stores, enabling them to offer highly competitive prices and draw sales away from traditionally popular establishments like department stores. E-tailers have taken off by leveraging these cost advantages to appeal to an increasingly price-conscious consumer base. The expansion of value-added services like buy now, pay later and fast, flexible delivery options have contributed to strong industry growth. However, the industry hasn’t been immune to recent cos-of-living pressures; sky-high inflation across much of Europe severely dented Europeans’ spending power, with drops in sales volumes affecting many online stores in 2023. Despite this, revenue continues on an upwards trajectory as inflation outweighs the drop in volume sales, contributing to forecast revenue growth of 3.9% in 2025. Looking forwards, rising internet penetration will continue to provide a growing market for e-tailers, driving revenue upwards at a projected compound annual rate of 6.3% over the five years through 2030 to reach €478.9 billion. E-tailers will continue to adapt their business practices and product selections to reflect the ever-growing level of environmental awareness. Delivery fleets will become fully electrified for many companies, while increasingly stringent waste regulations will force companies to adopt biodegradable or recyclable packaging in the coming years. Still, online retailers must innovate to compete with rival Asian companies like Temu as these competitors increasingly penetrate European markets. The integration of Gen AI and data analytics will transform business operations, making them more efficient and helping to lower wage costs, supporting profitability.
Success.ai empowers businesses with dynamic, enterprise-grade B2B company datasets, enabling deep insights into over 28 million verified company profiles, including specialized segments like e-commerce and private companies. Ideal for those targeting diverse company types, our data supports strategic initiatives from sales to competitor analysis.
Key Use Cases Enhanced by Success.ai:
Why Choose Success.ai?
Get Started with Success.ai Today: Partner with us to harness the power of detailed and expansive company data. Whether for enriching your sales processes, conducting in-depth competitor analysis, or enhancing your overall data strategy, Success.ai provides the tools and insights necessary to propel your business to new heights.
Contact us to explore how our tailored data solutions can transform your business operations and strategic initiatives.
Remember, with Success.ai, no one beats us on price. Period.
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.
There are many potential insights one can draw from this dataset. The ecommerce data provided contains information about sales orders, including the order ID, order date, shipping date, customer names, location (country, city, state), product categories, product names, sales amount, and profit amount. The dataset covers a range of orders over several years, with information on different product categories and their associated sales. It also provides insights into the distribution of orders across cities and states. After importing the data into Tableau, one can sort to see which states have the most total sales (CA, WA, AZ), which product categories have the highest profit (chairs, phones, machines), and various other intersections of data. The analysis from this data can be used to make decisions about what products to increase or reduce stock of, which states to focus on to push sales, and how to maximize profits by looking at which product categories have the highest profit margins.
If you’re interested, please take a look!
Dataset originally from https://www.kaggle.com/datasets/imgowthamg/walmart-sales-dataset
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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.
Unlock the door to business expansion by investing in our real-time eCommerce leads list. Gain direct access to store owners and make informed decisions with data fields including Store Name, Website, Contact First Name, Contact Last Name, Email Address, Physical Address, City, State, Country, Zip Code, Phone Number, Revenue Size, Employee Size, and more on demand.
Ensure a lifetime of access for continuous growth and tailor your campaigns with accurate and reliable information, initiating targeted efforts that align with your marketing goals. Whether you're targeting specific industries or global locations, our database provides up-to-date and valuable insights to support your business journey.
• 4M+ eCommerce Companies • 40M+ Worldwide eCommerce Leads • Direct Contact Info for Shop Owners • 47+ eCommerce Platforms • 40+ Data Points • Lifetime Access • 10+ Data Segmentations • Sample Data