The awareness among worldwide consumers about companies selling their personal data to third parties has grown in recent years. As of July 2022, three in four consumers in selected countries worldwide said they knew that companies sell personal information. In comparison, in 2020, this share was a little over 60 percent.

Although a majority of internet users aged between 18 and 75 years in the United Kingdom (UK) are still skeptical when it comes to personal data being collected by companies, a small share (36 percent) would be willing to share this data in return for financial compensation. These types of data mainly included purchase history and location data, while a slightly smaller percentage stated they were willing to sell their browsing history and online media consumption to companies.

According to an analysis conducted in 2023 of over 200 companies targeting children and families in the United States, only 25 percent of the businesses had a privacy-protective mindset and did not sell data. Under the California Privacy Rights Act amendment, companies are supposed to disclose if they sell users' personal data. Around 13 percent of companies did not disclose whether they engaged in such practices.

A survey conducted online in the United Kingdom (UK) in 2020 revealed that over 70 percent of 18 to 24 year olds would be willing to share their personal data with companies in return for payment. Conversely, only slightly more than 40 percent of those over 65 years of age said they would do the same. As a whole, 38 percent of UK respondents were against the idea of sharing personal data for financial compensation.

As of February 2025, 19 U.S. states had state-level data privacy laws signed. While the core content in these regulations was similar, they varied in addressing certain business obligations regarding data privacy. According to all state-level laws, businesses are obligated to notify consumers about certain data privacy operations. Furthermore, all signed laws require companies to treat consumers under a certain age with an opt-in default for the sale of their personal information.

Question Paper Solutions of chapter Personal Selling and Direct Marketing of Integrated Marketing Communication, 3rd semester , Master of Business Administration (2023-24)

Names of Businesses Selling Second Hand Goods Update Frequency: Semi-Annually

China Industrial Enterprise: Private: Selling & Distribution Cost data was reported at 825,520.000 RMB mn in 2018. This records a decrease from the previous number of 921,747.000 RMB mn for 2017. China Industrial Enterprise: Private: Selling & Distribution Cost data is updated yearly, averaging 330,778.478 RMB mn from Dec 1998 (Median) to 2018, with 20 observations. The data reached an all-time high of 921,747.000 RMB mn in 2017 and a record low of 7,402.767 RMB mn in 1998. China Industrial Enterprise: Private: Selling & Distribution Cost data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Industrial Sector – Table CN.BF: Industrial Financial Data: Private Enterprise.

Online Retail Transaction Data

UK Online Retail Sales and Customer Transaction Data

By UCI [source]

About this dataset

Comprehensive Dataset on Online Retail Sales and Customer Data

Welcome to this comprehensive dataset offering a wide array of information related to online retail sales. This data set provides an in-depth look at transactions, product details, and customer information documented by an online retail company based in the UK. The scope of the data spans vastly, from granular details about each product sold to extensive customer data sets from different countries.

This transnational data set is a treasure trove of vital business insights as it meticulously catalogues all the transactions that happened during its span. It houses rich transactional records curated by a renowned non-store online retail company based in the UK known for selling unique all-occasion gifts. A considerable portion of its clientele includes wholesalers; ergo, this dataset can prove instrumental for companies looking for patterns or studying purchasing trends among such businesses.

The available attributes within this dataset offer valuable pieces of information:

• InvoiceNo: This attribute refers to invoice numbers that are six-digit integral numbers uniquely assigned to every transaction logged in this system. Transactions marked with 'c' at the beginning signify cancellations - adding yet another dimension for purchase pattern analysis.

• StockCode: Stock Code corresponds with specific items as they're represented within the inventory system via 5-digit integral numbers; these allow easy identification and distinction between products.

• Description: This refers to product names, giving users qualitative knowledge about what kind of items are being bought and sold frequently.

• Quantity: These figures ascertain the volume of each product per transaction – important figures that can help understand buying trends better.

• InvoiceDate: Invoice Dates detail when each transaction was generated down to precise timestamps – invaluable when conducting time-based trend analysis or segmentation studies.

• UnitPrice: Unit prices represent how much each unit retails at — crucial for revenue calculations or cost-related analyses.

Finally,

• Country: This locational attribute shows where each customer hails from, adding geographical segmentation to your data investigation toolkit.

This dataset was originally collated by Dr Daqing Chen, Director of the Public Analytics group based at the School of Engineering, London South Bank University. His research studies and business cases with this dataset have been published in various papers contributing to establishing a solid theoretical basis for direct, data and digital marketing strategies.

Access to such records can ensure enriching explorations or formulating insightful hypotheses about consumer behavior patterns among wholesalers. Whether it's managing inventory or studying transactional trends over time or spotting cancellation patterns - this dataset is apt for multiple forms of retail analysis

How to use the dataset

1. Sales Analysis:

Sales data forms the backbone of this dataset, and it allows users to delve into various aspects of sales performance. You can use the Quantity and UnitPrice fields to calculate metrics like revenue, and further combine it with InvoiceNo information to understand sales over individual transactions.

2. Product Analysis:

Each product in this dataset comes with its unique identifier (StockCode) and its name (Description). You could analyse which products are most popular based on Quantity sold or look at popularity per transaction by considering both Quantity and InvoiceNo.

3. Customer Segmentation:

If you associated specific business logic onto the transactions (such as calculating total amounts), then you could use standard machine learning methods or even RFM (Recency, Frequency, Monetary) segmentation techniques combining it with 'CustomerID' for your customer base to understand customer behavior better. Concatenating invoice numbers (which stand for separate transactions) per client will give insights about your clients as well.

4. Geographical Analysis:

The Country column enables analysts to study purchase patterns across different geographical locations.

Practical applications

Understand what products sell best where - It can help drive tailored marketing strategies. Anomalies detection – Identify unusual behaviors that might lead frau...

Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

Amazon Best Seller data contains information about the best-selling products on Amazon; this information is very useful for monitoring the best-selling products in various categories and sub-categories.

A. Usecase/Applications possible with the data:

1. Competition Monitoring: Amazon's Best Sellers Data contains the data of best-selling goods on Amazon, which features a lot about the top e-commerce trends. Direct competition with these items might be challenging, but the Best Sellers list can be a source of inspiration for new products and help e-commerce merchants keep ahead of the game. Getting your item onto the Best Sellers list and keeping it there is one of the most reliable strategies to ensure sales for your company. Once a product makes the Best Sellers list, e-commerce businesses increasingly use web scraping to keep track of new items and change their own to compete.

2. New Product Launch: Amazon Best Sellers Data is critical when it comes to launching a new product or repositioning existing products. Indeed, Amazon's best seller rank data can be used as a guide, indicating when you and your products are on the right track.

How does it work?

• Analyze sample data
• Customize parameters to suit your needs
• Add to your projects
• Contact support for further customization

China Industrial Enterprise: Private: Selling & Distribution Cost: Year to Date data was reported at 344.160 RMB bn in May 2018. This records an increase from the previous number of 273.330 RMB bn for Apr 2018. China Industrial Enterprise: Private: Selling & Distribution Cost: Year to Date data is updated monthly, averaging 123.700 RMB bn from Jan 2001 (Median) to May 2018, with 185 observations. The data reached an all-time high of 941.750 RMB bn in Dec 2017 and a record low of 2.544 RMB bn in Feb 2001. China Industrial Enterprise: Private: Selling & Distribution Cost: Year to Date data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Industrial Sector – Table CN.BF: Industrial Financial Data: Private Enterprise.

Edgewell Personal Care reported $169.8M in Selling and Administration Expenses for its fiscal quarter ending in March of 2025. Data for Edgewell Personal Care | EPC - Selling And Administration Expenses including historical, tables and charts were last updated by Trading Economics this last July in 2025.

Data from the second quarter of 2024 revealed that the top 25 beauty and personal care products sold on Amazon were skincare items (32 percent). Hair products were next, accounting for around one-fifth of the best-selling beauty articles on Amazon. Beauty sales on the rise Online sales of beauty products heavily depend on consumers digital shopping behavior. When shopping for beauty products online, the vast majority of consumers prefer to use leading marketplaces, such as Amazon, to place their orders in 2023. This could be due to Amazon also being ranked the second most frequently appearing marketplace when searching for beauty brands on Google. Amazon ranks second after Alibaba as the world's leading health, beauty, and personal care online retailer by sales. Amazon is expected to almost double its estimated sales of health, beauty and personal care products, from around 44 billion U.S. dollars in 2022 to 79.4 billion U.S. dollars by 2027. Amazon’s take on beauty products Beauty product preferences can vary from country to country. Worldwide the top-rated beauty product on Amazon by number of reviews was an Essence mascara. Brand preference also varies depending on the country, for example in the United States, in the first quarter of 2023, L’Oréal Paris was the best-selling beauty and personal care brand on Amazon.com. This changed throughout the year, and by the end of July, CeraVe took the top spot.

This fact sheet will help business owners create promotional information about their products or services in the format of a one-page “sell sheet.” Business owners will learn how to define their target audience, convey the key benefits they are selling and create an effective sell sheet.

Records agencies create when disposing of excess or surplus personal property by sale, donation, or destruction. Includes:rn- excess property inventories and listsrn- lists and other records identifying approved receivers of excess propertyrn- donation receipts rn- destruction certificatesrn- documentation of vehicle transfer by sale, donation, or exchange, including Standard Form 97, United States Government Certificate to Obtain Title to a Motor Vehiclern- related correspondence

Description

The datasets demonstrate the malware economy and the value chain published in our paper, Malware Finances and Operations: a Data-Driven Study of the Value Chain for Infections and Compromised Access, at the 12th International Workshop on Cyber Crime (IWCC 2023), part of the ARES Conference, published by the International Conference Proceedings Series of the ACM ICPS.

Using the well-documented scripts, it is straightforward to reproduce our findings. It takes an estimated 1 hour of human time and 3 hours of computing time to duplicate our key findings from MalwareInfectionSet; around one hour with VictimAccessSet; and minutes to replicate the price calculations using AccountAccessSet. See the included README.md files and Python scripts.

We choose to represent each victim by a single JavaScript Object Notation (JSON) data file. Data sources provide sets of victim JSON data files from which we've extracted the essential information and omitted Personally Identifiable Information (PII). We collected, curated, and modelled three datasets, which we publish under the Creative Commons Attribution 4.0 International License.

1. MalwareInfectionSet
We discover (and, to the best of our knowledge, document scientifically for the first time) that malware networks appear to dump their data collections online. We collected these infostealer malware logs available for free. We utilise 245 malware log dumps from 2019 and 2020 originating from 14 malware networks. The dataset contains 1.8 million victim files, with a dataset size of 15 GB.

2. VictimAccessSet
We demonstrate how Infostealer malware networks sell access to infected victims. Genesis Market focuses on user-friendliness and continuous supply of compromised data. Marketplace listings include everything necessary to gain access to the victim's online accounts, including passwords and usernames, but also detailed collection of information which provides a clone of the victim's browser session. Indeed, Genesis Market simplifies the import of compromised victim authentication data into a web browser session. We measure the prices on Genesis Market and how compromised device prices are determined. We crawled the website between April 2019 and May 2022, collecting the web pages offering the resources for sale. The dataset contains 0.5 million victim files, with a dataset size of 3.5 GB.

3. AccountAccessSet
The Database marketplace operates inside the anonymous Tor network. Vendors offer their goods for sale, and customers can purchase them with Bitcoins. The marketplace sells online accounts, such as PayPal and Spotify, as well as private datasets, such as driver's licence photographs and tax forms. We then collect data from Database Market, where vendors sell online credentials, and investigate similarly. To build our dataset, we crawled the website between November 2021 and June 2022, collecting the web pages offering the credentials for sale. The dataset contains 33,896 victim files, with a dataset size of 400 MB.

Credits Authors

• Billy Bob Brumley (Tampere University, Tampere, Finland)
• Juha Nurmi (Tampere University, Tampere, Finland)
• Mikko Niemelä (Cyber Intelligence House, Singapore)

Funding

This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme under project numbers 804476 (SCARE) and 952622 (SPIRS).

Alternative links to download: AccountAccessSet, MalwareInfectionSet, and VictimAccessSet.

Risha gas selling prices for the private sector 2023

Empower Your Business With Professional Data Licensing Services

Discover a 360-Degree View of Worldwide Solution Buyers and Their Needs Leverage over 70 insights that will help you make better decisions to manage your sales pipeline, target key accounts with customized messaging, and focus your sales and marketing efforts:

Here are some of the types of Insights, our data licensing services can provide are:

Technology Insights: Discover companies’ technology preferences, including their tech stack for essential investments such as CRM systems, marketing and sales automation, email security and hosting, data analytics, and cloud security and providers.

Departmental Roles and Openings: Access real-time data on the number of roles and job openings across various departments, including IT, Development, Security, Marketing, Sales, and Customer Success. This information helps you gauge the company’s growth trajectory and possible needs.

Funding Insights: Keep updated of the latest funding, dates, types, and lead investors, providing you with a clear understanding of a company’s potential for growth investments.

Mobile Application Insights: Find out if the company has a mobile app or web app, enabling you to tailor your pitch effectively.

Website traffic and advertising spend metrics: Customers can leverage website traffic and advertising data to gain insights into competitor performance, allowing them to refine their marketing strategies and optimize ad spending.

Access unlimited data and improve conversation by 3X

• Leverage the data for your Account-Based Marketing (ABM) strategy

• Leverage ICP (industry, company size, location etc) to identify high- potential Accounts.

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  Multi-channel outreach (email, Cell, social media) that resonate with the target audience.

Who can leverage our Data:

B2B marketing Teams- Increase marketing leads and enhance conversions.

B2B sales teams- Build a stronger pipeline and increase your deal wins.

Talent sourcing/Staffing companies- Leverage our data to identify and engage top talent, streamlining your recruitment process and finding the best candidates faster.

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Technology companies: Leverage our Technographic data to reveal the technology stack and tools used by companies, helping tailor marketing and sales efforts.

Data Source:

The Database, sourced through multiple sources and validated using proprietary methods on an ongoing basis, is highly customizable. It contains parameters such as employee size, job title, domain, industry, Technography, Ad spends, Funding data, and more, which can be tailored to create segments that perfectly align with your targeting needs. That is exactly why our Database is perfect for licensing!

FAQs

1. Can licensed data be resold or redistributed? Answer: No, The customer shall not, directly or indirectly, sell, distribute, license, or otherwise make available the licensed data to any third party that intends to resell, sublicense, or redistribute the data. The Customer must take reasonable steps to ensure that any recipient of the licensed data is using it for internal purposes only and not for resale or redistribution. Any breach of this provision shall be considered a material breach of this Order Form and may result in the immediate termination of the Customer's rights under this agreement, as well as any applicable remedies available under law.

2. What is the duration of the data license and usage terms? Answer: The data license is valid for 12 months (1 year) for unlimited usage. Customers also have the option to license the data for multiple years. At the end of the first year, Customers can renew the license to maintain continued access.

3. What happens if the customer misuses the data? Answer: The data can be used without limits for a period of one year or multiple years (depending on the contract tenure); however, Thomson Data actively monitors its usage. If any unusual activity is detected, Thomson Data reserves the right to terminate the account.

4. How frequently is the data updated? Answer: The data is updated on a quarterly basis and fresh records added on a monthly basis

5. What is the accuracy rate of the data? Answer: Customers can expect 90% accuracy for all data points, with email accuracy ranging between 85% and 90%. Cell phone data accuracy is around 80%.

6. What types of information are included in the data? Answer: Thomson Data provides over 70+ data points, including contact details (name, job title, LinkedIn profile, cell number, email address, education, certifications, work experience, etc.), company information, department/team sizes, SIC and NAICS codes, industry classification, technographic detai...

This dataset is about books. It has 6 rows and is filtered where the book is Sell your way to success. It features 7 columns including author, publication date, language, and book publisher.