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.

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

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?

1. Verified Profiles for Precision Engagement

   • Access verified profiles, business locations, employee counts, and decision-maker details for e-commerce businesses across APAC.
   • AI-driven validation ensures 99% accuracy, improving engagement rates and reducing outreach inefficiencies.

2. Comprehensive Coverage of the APAC E-commerce Sector

   • Includes businesses from major e-commerce hubs such as China, India, Japan, South Korea, Australia, and Southeast Asia.
   • Gain insights into regional e-commerce trends, digital transformation efforts, and logistics innovations.

3. Continuously Updated Datasets

   • Real-time updates ensure that business profiles, employee roles, and operational insights remain accurate and relevant.
   • Stay aligned with dynamic market conditions and emerging opportunities in the APAC region.

4. Ethical and Compliant

   • Fully adheres to GDPR, CCPA, and other global data privacy regulations, ensuring responsible and lawful data usage.

Data Highlights:

• 700M+ Verified Global Profiles: Access business profiles for e-commerce professionals and organizations across APAC.
• Firmographic Insights: Gain detailed information, including business locations, employee counts, and operational details.
• Decision-maker Profiles: Connect with key e-commerce leaders, managers, and strategists driving online retail innovation.
• Industry Trends: Understand emerging e-commerce trends, consumer behavior, and market dynamics in the APAC region.

Key Features of the Dataset:

1. Comprehensive E-commerce Business Profiles

   • Identify and connect with businesses specializing in online retail, marketplace management, and digital commerce logistics.
   • Target decision-makers involved in supply chain optimization, digital marketing, and platform development.

2. Advanced Filters for Precision Campaigns

   • Filter businesses and professionals by industry focus (fashion, electronics, grocery), geographic location, or employee size.
   • Tailor campaigns to address specific goals, such as promoting technology adoption, enhancing customer engagement, or expanding supply chains.

3. Regional and Sector-specific Insights

   • Leverage data on APAC’s fast-growing e-commerce markets, consumer purchasing trends, and regional challenges.
   • Refine your marketing strategies and outreach efforts to align with market priorities.

4. AI-Driven Enrichment

   • Profiles enriched with actionable data allow for personalized messaging, highlight unique value propositions, and improve engagement outcomes.

Strategic Use Cases:

1. Marketing Campaigns and Outreach

   • Promote e-commerce solutions, logistics services, or digital commerce tools to businesses and professionals in the APAC region.
   • Use verified contact data for multi-channel outreach, including email, phone, and social media campaigns.

2. Partnership Development and Vendor Collaboration

   • Build relationships with e-commerce marketplaces, logistics providers, and payment solution companies seeking strategic partnerships.
   • Foster collaborations that drive operational efficiency, enhance customer experiences, or expand market reach.

3. Market Research and Competitive Analysis

   • Analyze regional e-commerce trends, consumer preferences, and logistics challenges to refine product offerings and business strategies.
   • Benchmark against competitors to identify growth opportunities and high-demand solutions.

4. Recruitment and Talent Acquisition

   • Target HR professionals and hiring managers in the e-commerce industry recruiting for roles in operations, logistics, and digital marketing.
   • Provide workforce optimization platforms or training solutions tailored to the digital commerce sector.

Why Choose Success.ai?

1. Best Price Guarantee

   • Access premium-quality e-commerce store data at competitive prices, ensuring strong ROI for your marketing, sales, and strategic initiatives.

2. Seamless Integration

   • Integrate verified e-commerce data into CRM systems, analytics platforms, or market...

Context

In the field of e-commerce, the datasets are typically considered as proprietary, meaning they are owned and controlled by individual organizations and are not often made publicly available due to privacy and business considerations. In spite of this, The UCI Machine Learning Repository, known for its extensive collection of datasets beneficial for machine learning and data mining research, has curated and made accessible a unique dataset. This dataset comprises actual transactional data spanning from the year 2010 to 2011. For those interested, the dataset is maintained and readily available on the UCI Machine Learning Repository's site under the title "Online Retail".

Content

The dataset is a transnational one, capturing every transaction made from December 1, 2010, through December 9, 2011, by a UK-based non-store online retail company. As an online retail entity, the company doesn't have a physical store presence, and its operations and sales are conducted purely online. The company's primary product offering includes unique gifts for all occasions. While the company serves a diverse range of customers, a significant number of its clientele includes wholesalers.

Acknowledgements

In collaboration with the UCI Machine Learning Repository, the dataset was provided and made available by Dr. Daqing Chen. Dr. Chen is the Director of the Public Analytics group at London South Bank University, UK. Any correspondence regarding this dataset can be sent to Dr. Chen at 'chend' at 'lsbu.ac.uk'. We are grateful to him for providing such an invaluable resource for researchers and data science enthusiasts.

The image used has been sourced from Canva

Inspiration

The rich and extensive data within this dataset opens the door for a multitude of potential analyses. It lends itself well to various methods and techniques in data science, including but not limited to time series analysis, clustering, and classification. By exploring this dataset, one could derive key insights into customer behavior, transaction trends, and product performance, providing ample opportunities for deep and insightful explorations.

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?

1. Verified Contact Data for Precision Outreach

   • Access verified work emails, phone numbers, and LinkedIn profiles of e-commerce professionals across South-east Asia.
   • AI-driven validation ensures 99% accuracy, reducing communication inefficiencies and enhancing engagement rates.

2. Comprehensive Coverage of South-east Asia’s E-commerce Market

   • Includes professionals from key e-commerce hubs such as Singapore, Indonesia, Thailand, Vietnam, Malaysia, and the Philippines.
   • Gain insights into regional consumer trends, logistics challenges, and online marketplace dynamics.

3. Continuously Updated Datasets

   • Real-time updates capture changes in professional roles, company expansions, and market conditions.
   • Stay aligned with industry trends and emerging opportunities in South-east Asia’s e-commerce sector.

4. Ethical and Compliant

   • Fully adheres to GDPR, CCPA, and other global data privacy regulations, ensuring responsible and lawful data usage.

Data Highlights:

• 170M+ Verified Global Profiles: Engage with e-commerce professionals and decision-makers across South-east Asia.
• Verified Contact Details: Gain work emails, phone numbers, and LinkedIn profiles for precision targeting.
• Regional Insights: Understand key trends in e-commerce, logistics, and consumer preferences in South-east Asia.
• Leadership Insights: Connect with online marketplace leaders, logistics managers, and digital marketing professionals driving innovation in the sector.

Key Features of the Dataset:

1. Comprehensive Professional Profiles in E-commerce

   • Identify and connect with professionals managing e-commerce platforms, online marketplaces, and logistics operations.
   • Target individuals responsible for digital marketing, supply chain management, and e-commerce strategies.

2. Advanced Filters for Precision Campaigns

   • Filter professionals by industry focus (apparel, electronics, food delivery), geographic location, or job function.
   • Tailor campaigns to align with specific business goals, such as logistics optimization, consumer engagement, or market entry.

3. Regional and Market-specific Insights

   • Leverage data on e-commerce trends, regional consumer behaviors, and logistics challenges unique to South-east Asia.
   • Refine marketing strategies and business plans based on actionable insights from the region.

4. AI-Driven Enrichment

   • Profiles enriched with actionable data enable personalized messaging, highlight unique value propositions, and improve engagement outcomes.

Strategic Use Cases:

1. Marketing Campaigns and Digital Outreach

   • Promote e-commerce solutions, logistics services, or online marketing tools to professionals in South-east Asia’s e-commerce industry.
   • Use verified contact data for multi-channel outreach, including email, phone, and digital campaigns.

2. Market Research and Competitive Analysis

   • Analyze e-commerce trends and consumer preferences across South-east Asia to refine product offerings and marketing strategies.
   • Benchmark against competitors to identify growth opportunities and high-demand solutions.

3. Partnership Development and Vendor Collaboration

   • Build relationships with e-commerce platforms, logistics providers, and digital marketing agencies exploring strategic partnerships.
   • Foster collaborations that enhance consumer experiences, improve delivery efficiency, or expand market reach.

4. Recruitment and Talent Acquisition

   • Target HR professionals and hiring managers in the e-commerce industry seeking candidates for logistics, digital marketing, and platform management roles.
   • Provide workforce optimization platforms or training solutions tailored to the sector.

Why Choose Success.ai?

1. Best Price Guarantee

   • Access premium-quality e-commerce market data at competitive prices, ensuring strong ROI for your marketing, sales, and business development initiatives.

2. Seamless Integration

   • Integrate verified e-commerce data into CRM systems, analytics ...

Monthly dataset showing change in sales and jobs recorded by Xero, an online accounting software platform. This dataset is updated on a quarterly basis. These are official statistics in development. Source: Xero.

Dataset available only to University of Arizona affiliates. To obtain access, you must log in to ReDATA with your NetID. Data is for research use by each individual downloader only. Sharing and/or redistribution of any portion of this dataset is prohibited.The ReferenceUSA datasets from Data Axle (formerly Infogroup) contain establishment-level data about US businesses in annual snapshots from 1997-2021 and can help users create marketing plans and conduct competitive analyses. Each year has 53-94 indicators, with documentation for layouts found in Documentation.zip. Codebooks for 2015, 2017, and 2019 are missing, but all file layouts for 2014-2021 are identical.The University of Arizona University Libraries also subscribe to Data Axle Reference Solutions which provides this data in a searchable, online database with historical data available going back to 2003.NOTE: The uncompressed datasets are very large.Detailed file descriptions and MD5 hash values for each file can be found in the README.txt file.For inquiries regarding the contents of this dataset, please contact the Corresponding Author listed in the README.txt file. Administrative inquiries (e.g., removal requests, trouble downloading, etc.) can be directed to data-management@arizona.edu

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...

Displays a representation of where all the surveyed businesses across York Region are located. This data is collected through the Region’s annual comprehensive employment survey and each record contains employment and business contact information about each business with the exception of home and farm-based businesses. Home-based businesses are not included as they are distributed throughout residential communities within the Region and are difficult to survey. Employment data for farm-based businesses are collected through the Census of Agriculture conducted by Statistics Canada, and are not included in the York Region Employment Survey dataset.Update Frequency: Not PlannedDate Created: 17/03/2023Date Modified: 17/03/2023Metadata Date: 17/03/2023Citation Contacts: York Region, Long Range Planning Attribute Definitions BUSINESSID: Unique key to identify a business.NAME: The common business name used in everyday transactions. FULL_ADDRESS: Full street address of the physical address. (This field concatenates the following fields: Street Number, Street Name, Street Type, Street Direction)STREET_NUM: Street number of the physical addressSTREET_NAME: Street name of the physical addressSTREET_TYPE: Street type of the physical addressSTREET_DIR: Street direction of the physical addressUNIT_NUM: Unit number of the physical addressCOMMUNITY: Community name where the business is physically locatedMUNICIPALITY: Municipality where the business is physically locatedPOST_CODE: Postal code corresponding to the physical street addressEMPLOYEE_RANGE: The numerical range of employees working in a given firm. PRIM_NAICS, PRIM_NAICS_DESC: The Primary 5-digit NAIC code defines the main business activity that occurs at that particular physical business location.SEC_NAICS, SEC_NAICS_DESC: If there is more than one business activity occurring at a particular business location (that is substantially different from the primary business activity), then a secondary NAIC is assigned.PRIM_BUS_CLUSTER, SEC_BUS_CLUSTER: A business cluster is defined as a geographic concentration of interconnected businesses and institutions in a common industry that both compete and cooperate. As defined by York Region, this field indicates the primary business cluster that this business belongs to.BUS_ACTIVITY_DESC: This is a comment box with a detailed text description of the business activity. TRAFFIC_ZONE: Specifies the traffic zone in which the business is located. MANUFACTURER: Indicates whether or not the business manufactures at the physical business location. CAN_HEADOFFICE: The business at this location is considered the Canadian head office.HEADOFFICEPROVSTATE: Indicates which state or province the head office is located if the head office is located in Canada (outside of Ontario) or in the United StatesHEADOFFICECOUNTRY: Indicates which country the head office is locatedYR_CURRENTLOC: Indicates the year that the business moved into its current address.MAIL_FULL_ADDRESS: The mailing address is the address through which a business receives postal service. This may or may not be the same as the physical street address.MAIL_STREET_NUM, MAIL_STREET_NAME, MAIL_STREET_TYPE, MAIL_STREET_DIR, MAIL_UNIT_NUM, MAIL_COMMUNITY, MAIL_MUNICIPALITY, MAIL_PROVINCE, MAIL_COUNTRY, MAIL_POST_CODE, MAIL_POBOX: Mailing address fields are similar to street address fields and in most cases will be the same as the Street Address. Some examples where the two addresses might not be the same include, multiple location businesses, home-based businesses, or when a business receives mail through a P.O. Box.WEBSITE: The General/Main business website.GEN_BUS_EMAIL: The general/main business e-mail address for that location.PHONE_NO: The general/main phone number for the business location.PHONE_EXT: The extension (if any) for the general/main business phone number.LAST_SURVEYED: The date the record was last surveyedLAST_UPDATED: The date the record was last updatedUPDATEMETHOD: Displays how the business was last updated, based on a predetermined list.X_COORD, Y_COORD: The x,y coordinates of the surveyed business location Frequently Asked QuestionsHow many businesses are included in the 2022 York Region Business Directory? The 2022 York Region Business Directory contains just over 34,000 business listings. In the past, businesses were annually surveyed, either in person or by telephone to improve the accuracy of the directory. Due to the COVID-19 Pandemic, a survey was not complete in 2020 and 2021. The Region may return to annual surveying in future years, however the next employment survey will be in 2024. This listing also includes home-based businesses that participated in the 2022 employment survey. What is a NAIC code?The North American Industrial Classification (NAIC) coding system is a hierarchical classification system developed in Canada, Mexico and the United States. It was developed to allow for the comparison of business and employment information across a variety of industry categories. The NAICS has a hierarchical structure, designed as follows: Two-digits = sector (e.g., 31-33 contain the Manufacturing sectors) Three-digits = subsector (e.g., 336 = Transportation Equipment Manufacturing) Four-digits = industry group (e.g., 3361 = Motor Vehicle Manufacturing) Five-digits = industry (e.g., 33611 = Automobile and Light Duty Motor Vehicle Manufacturing) For more information on the NAIC coding system click here How do I add or update my business information in the York Region Business Directory? To add or update your business information, please select one of the following methods: • Email: Please email businessdirectory@york.ca to request to be added to the Business Directory.• Online: Go to www.york.ca/employmentsurvey and participate in the employment survey - note, this will only be active in 2024 when the Region performs its next employment surveyThere is no charge for obtaining a basic listing of your business in the York Region Business Directory. How up-to-date is the information?This directory is based on the 2022 York Region Employment Survey, a survey of businesses which attempts to gather information from all businesses across York Region. In instances where we were unable to gather information, the most recent data was used. Farm-based businesses have not been included in the survey and home-based businesses that participated in the 2022 survey are included in the dataset. The date that the business listing was last updated is located in the LastUpdate column in the attached spreadsheet. Are different versions of the York Region Business Directory available?Yes, the directory is available in two online formats:• An interactive, map-based directory searchable by company name, street address, municipality and industry sector.• The entire dataset in downloadable Microsoft Excel format via York Region's Open Data Portal. This version of the York Region Business Directory 2022 is offered free of charge. The Directory allows for the detailed analysis of business and employment trends, as well as the construction of targeted contact lists. To view the map-based directory and dataset, go to:2022 Business Directory - Map Is there any analysis of business and employment trends in York Region?Yes. The "2022 Employment and Industry Report" contains information on employment trends in York Region and is based on results from the employment survey. please visit www.york.ca/york-region/plans-reports-and-strategies/employment-and-industry-report to view the report. What other resources are available for York Region businesses?York Region offers an export advisory service and a number of other business development programs and seminars for interested individuals.For details, consult the York Region Economic Strategy Branch. Who do I contact to obtain more information about the Directory?For more information on the York Region Business Directory, contact the Planning and Economic Development Branch at:businessdirectory@york.ca.

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.

Increase the proportion of businesses that receive orders online from 24% to 40% by 2014 and continue growth each year to 2020.

Exploring E-commerce Trends: A Guide to Leveraging Dummy Dataset

Introduction: In the world of e-commerce, data is a powerful asset that can be leveraged to understand customer behavior, improve sales strategies, and enhance overall business performance. This guide explores how to effectively utilize a dummy dataset generated to simulate various aspects of an e-commerce platform. By analyzing this dataset, businesses can gain valuable insights into product trends, customer preferences, and market dynamics.

1. Dataset Overview: The dummy dataset contains information on 1000 products across different categories such as electronics, clothing, home & kitchen, books, toys & games, and more. Each product is associated with attributes such as price, rating, number of reviews, stock quantity, discounts, sales, and date added to inventory. This comprehensive dataset provides a rich source of information for analysis and exploration.

2. Data Analysis: Using tools like Pandas, NumPy, and visualization libraries like Matplotlib or Seaborn, businesses can perform in-depth analysis of the dataset. Key insights such as top-selling products, popular product categories, pricing trends, and seasonal variations can be extracted through exploratory data analysis (EDA). Visualization techniques can be employed to create intuitive graphs and charts for better understanding and communication of findings.

3. Machine Learning Applications: The dataset can be used to train machine learning models for various e-commerce tasks such as product recommendation, sales prediction, customer segmentation, and sentiment analysis. By applying algorithms like linear regression, decision trees, or neural networks, businesses can develop predictive models to optimize inventory management, personalize customer experiences, and drive sales growth.

4. Testing and Prototyping: Businesses can utilize the dummy dataset to test new algorithms, prototype new features, or conduct A/B testing experiments without impacting real user data. This enables rapid iteration and experimentation to validate hypotheses and refine strategies before implementation in a live environment.

5. Educational Resources: The dummy dataset serves as an invaluable educational resource for students, researchers, and professionals interested in learning about e-commerce data analysis and machine learning. Tutorials, workshops, and online courses can be developed using the dataset to teach concepts such as data manipulation, statistical analysis, and model training in the context of e-commerce.

6. Decision Support and Strategy Development: Insights derived from the dataset can inform strategic decision-making processes and guide business strategy development. By understanding customer preferences, market trends, and competitor behavior, businesses can make informed decisions regarding product assortment, pricing strategies, marketing campaigns, and resource allocation.

Conclusion: In conclusion, the dummy dataset provides a versatile and valuable resource for exploring e-commerce trends, understanding customer behavior, and driving business growth. By leveraging this dataset effectively, businesses can unlock actionable insights, optimize operations, and stay ahead in today's competitive e-commerce landscape

Qatar number dataset can directly send your offers, and it will indeed promote your business at the highest level. Even more, you can use this database on any CRM platform. All of these parts working together will give you a respectable profit margin. We can provide lists based on your needs and uphold all business rules. Qatar number dataset only contains authentic data. List to Data is one of the websites that can provide you with the most reliable information, as was previously said. Therefore, it is guaranteed that you will receive nearly no bounce-back data from this source. We are here to help our clients grow their online businesses. Also, you can get a good and instant return on investment(ROI). Qatar phone data is now a basic need for businesses. Without telemarketing and SMS marketing no one can grow at this time. So, this database is heavily required at this time. From all across the world, our organization has gathered millions of phone number lists for both businesses and consumers. To launch your business in Qatar, you can acquire this dataset. Qatar phone data will come to you at an extremely low budget and will solve your marketing issue. To make it more simple you can choose your targeted database while launching your items. We also create contact directories using business area categories. List to Data is aware of updating the database, therefore if any false information was ever added, we promptly removed it. Qatar phone number list is a genuine dataset. This will provide you with the best and most increasingly effective details when you conduct internet marketing. After purchase, you can instantly download the file, which will come to you in an Excel or CSV format. If anyone wants to make a huge profit they can ignore the Qatar phone number list. In the end, Qatar phone number list is the product that you need now. You can also view the other products on our website and get more information there. Although the product is an easy-to-buy service, the price is also fixed. This contact address will indeed generate more revenue for you, and you can see your business at the top in a short amount of time.

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

The dataset contains questionnaire answers to find out the effectivity of paid advertising in e-commerce for SMEs in Indonesia.

With the phone book era far in the past, database and directory publishers have been forced to transform their business approach, focusing on their digital presence. Despite many publishers rapidly moving away from print services, they are experiencing immovable competition from online search engines and social media platforms within the digital space, negatively affecting revenue growth potential. Industry revenue has been eroding at a CAGR of 4.4% over the past five years and in 2024, a 3.9% drop has led to the industry revenue totaling $4.4 billion. Profit continues to drop in line with revenue, accounting for 4.7% of revenue as publishers invest more in their digital platforms. Interest in printed directories has disappeared as institutional clients and consumers have continued their shift to convenient online resources. Declining demand for print advertising has curbed revenue growth and online revenue has only slightly mitigated this downturn. Though many traditional publishers, such as Yellow Pages, now operate under parent companies with digital resources, directory publishers remain low on the list of options businesses have to choose from in digital advertising. Due to the convenience and connectivity that Facebook and Google services offer, traditional directory publishers have a limited ability to compete. Many providers have rebranded and tailored their services toward client needs, though these efforts have only had a marginal impact on revenue growth. The industry is forecast to decline at an accelerated CAGR of 5.2% over the next five years, reaching an estimated $3.4 billion in 2029, as businesses and consumers continually turn to digital alternatives for information and advertising opportunities. As AI and digital technology innovation expands, social media company products will likely improve at a faster rate than the digital offerings that directory publishers can provide. Though these companies will seek external partnerships to cut costs, they face an uphill battle to boost their visibility and reverse consumer habit trends.

Success.ai’s Ecommerce Leads Data for Retail, E-commerce & Consumer Goods Executives Worldwide delivers a robust and comprehensive dataset designed to help businesses connect with decision-makers and professionals in the global retail and e-commerce sectors. Covering industry leaders, marketing strategists, product managers, and logistics executives, this dataset offers verified contact details, business locations, and decision-maker insights.

With access to over 700 million verified global profiles and actionable data from retail and consumer goods companies, Success.ai ensures your outreach, market research, and business development initiatives are powered by accurate, continuously updated, and AI-validated data. Supported by our Best Price Guarantee, this solution equips you to succeed in the competitive e-commerce landscape.

Why Choose Success.ai’s Ecommerce Leads Data?

1. Verified Contact Data for Precision Outreach

   • Access verified work emails, phone numbers, and LinkedIn profiles of e-commerce executives, retail leaders, and consumer goods professionals worldwide.
   • AI-driven validation ensures 99% accuracy, optimizing outreach efforts and minimizing errors in communication.

2. Comprehensive Global Coverage

   • Includes profiles of professionals from major e-commerce hubs such as North America, Europe, Asia-Pacific, and the Middle East.
   • Gain insights into global trends in online retail, logistics, and consumer goods.

3. Continuously Updated Datasets

   • Real-time updates capture leadership changes, business expansions, and emerging e-commerce strategies.
   • Stay ahead of industry trends and align your efforts with evolving market conditions.

4. Ethical and Compliant

   • Fully adheres to GDPR, CCPA, and other global data privacy regulations, ensuring responsible use and compliance with legal standards.

Data Highlights:

• 700M+ Verified Global Profiles: Connect with retail, e-commerce, and consumer goods professionals worldwide.
• Leadership and Decision-Maker Insights: Engage with C-suite executives, product managers, and logistics leaders driving the e-commerce industry.
• Verified Contact Details: Access work emails, phone numbers, and business addresses for targeted engagement.
• Market Intelligence: Gain visibility into e-commerce trends, customer engagement strategies, and emerging technologies.

Key Features of the Dataset:

1. Professional Profiles in E-commerce and Retail

   • Identify and connect with decision-makers responsible for product development, logistics, marketing strategies, and digital transformations.
   • Target professionals managing online marketplaces, omnichannel retail strategies, and supply chain efficiencies.

2. Advanced Filters for Precision Campaigns

   • Filter professionals by industry focus (apparel, consumer electronics, food and beverage), geographic location, or job function.
   • Tailor campaigns to address specific market needs such as logistics optimization, digital marketing, or inventory management.

3. Industry and Regional Insights

   • Leverage data on market trends, consumer preferences, and e-commerce growth across key regions.
   • Align your strategies with regional demands and opportunities to maximize impact.

4. AI-Driven Enrichment

   • Profiles enriched with actionable data allow for personalized messaging, highlight unique value propositions, and improve engagement outcomes.

Strategic Use Cases:

1. Marketing Campaigns and Lead Generation

   • Design targeted campaigns to promote logistics solutions, digital marketing tools, or consumer goods to professionals in retail and e-commerce.
   • Use verified contact data for multi-channel outreach, including email, phone, and digital marketing.

2. Product Development and Innovation

   • Utilize e-commerce insights to guide product development and align offerings with global consumer demands.
   • Collaborate with product managers and marketing strategists to refine product lines or launch new initiatives.

3. Partnership Development and Collaboration

   • Build relationships with e-commerce platforms, logistics providers, and retail brands seeking strategic alliances.
   • Foster partnerships that expand market reach, enhance customer experiences, or improve operational efficiencies.

4. Market Research and Competitive Analysis

   • Analyze global trends in e-commerce, retail, and consumer goods to refine your business strategies.
   • Benchmark against competitors to identify market gaps, growth opportunities, and emerging technologies.

Why Choose Success.ai?

1. Best Price Guarantee

   • Access premium-quality e-commerce leads data at competitive prices, ensuring strong ROI for your marketing, sales, and product development efforts.

2. Seamless Integration

   • Integrate verified e-commerce data into CRM systems, analytics tools, or marketing pla...

The Yelp dataset is a subset of businesses, reviews, and user data for use in personal, educational, and academic purposes. It contains 6.9M online reviews for 150k businesses. It also includes more than 200,000 images related to the reviews.

The data consists of multiple sub datasets:

1. Yelp Business data: Contains business data including location data, attributes, and categories.
2. Yelp Review data: Contains full review text data including the user_id that wrote the review and the business_id the review is written for.
3. Yelp User data: User data including the user's friend mapping and all the metadata associated with the user.
4. Yelp Checkin data: Checkins on a business.
5. Yelp Tip data: Tips written by a user on a business. Tips are shorter than reviews and tend to convey quick suggestions.
6. Yelp Photo data: Contains photo data including the caption and classification (one of "food", "drink", "menu", "inside" or "outside").

Available as JSON files, use can use it to teach students about databases, to learn NLP, or for sample production data while you learn how to make mobile apps.

The global number of Facebook users was forecast to continuously increase between 2023 and 2027 by in total 391 million users (+14.36 percent). After the fourth consecutive increasing year, the Facebook user base is estimated to reach 3.1 billion users and therefore a new peak in 2027. Notably, the number of Facebook users was continuously increasing over the past years. User figures, shown here regarding the platform Facebook, have been estimated by taking into account company filings or press material, secondary research, app downloads and traffic data. They refer to the average monthly active users over the period and count multiple accounts by persons only once.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).

Enterprise-Value-To-Sales-Ratio Time Series for Cafe24 Corp. Cafe24 Corp. operates an e-commerce platform worldwide. Its e-commerce platform, cafe24, which offers various services, including shopping mall solution, advertising, marketing, and hosting infrastructure. The company also provides shared office space for online businesses, education and training, and design market services. In addition, it offers payments service for online stores, and shipping and logistics services. The company was formerly known as SimpleX Internet, Inc. and changed its name to Cafe24 Corp. in 2017. Cafe24 Corp. was founded in 1999 and is headquartered in Seoul, South Korea.