Our Web Data dataset includes such data points as company name, location, headcount, industry, and size, among others. It offers extensive fresh and historical data, including even companies that operate in stealth mode.

For lead generation

With millions of companies worldwide, Web Company Database helps you filter potential clients based on custom criteria and speed up the conversion process.

Use cases

1. Filter potential clients according to location, size, and other criteria
2. Enrich your existing database
3. Improve conversion rates
4. Use predictive models to identify potential leads
5. Group your leads in segments for more accurate targeting

For market and business analysis

Our Web Company Data provides information about millions of companies, allowing you to find your competitors and see their weaknesses and strengths.

Use cases

1. Pinpoint your competitors
2. Learn about your competitors' size, headcount, and revenue
3. Prepare a data-driven plan for the next quarter

For Investors

We recommend B2B Web Data for investors to discover and evaluate businesses with the highest potential.

Gain strategic business insights, enhance decision-making, and maintain algorithms that signal investment opportunities with Coresignal’s global B2B Web Dataset.

Use cases

1. Screen startups and industries showing early signs of growth
2. Identify companies hungry for the next investment
3. Check if a startup is about to reach the next maturity phase
4. Identify and predict a startup's potential at the founding moment
5. Choose companies that fit you in terms of size and headcount

For sales prospecting

B2B Web Database saves time your employees would otherwise use to search for potential clients manually.

Use cases

1. Make a short list of the top prospects
2. Define which companies are large or small enough to buy your product
3. Based on the revenue, determine which companies are ready to convert
4. Sort the companies by their distance from your warehouse to draw a line where selling won't result in satisfactory profit

LinkedIn companies use datasets to access public company data for machine learning, ecosystem mapping, and strategic decisions. Popular use cases include competitive analysis, CRM enrichment, and lead generation.

Use our LinkedIn Companies Information dataset to access comprehensive data on companies worldwide, including business size, industry, employee profiles, and corporate activity. This dataset provides key company insights, organizational structure, and competitive landscape, tailored for market researchers, HR professionals, business analysts, and recruiters.

Leverage the LinkedIn Companies dataset to track company growth, analyze industry trends, and refine your recruitment strategies. By understanding company dynamics and employee movements, you can optimize sourcing efforts, enhance business development opportunities, and gain a strategic edge in your market. Stay informed and make data-backed decisions with this essential resource for understanding global company ecosystems.

Dataset Features

• timestamp: Represents the date and time when the company data was collected.
• id: Unique identifier for each company in the dataset.
• company_id: Identifier linking the company to an external database or internal system.
• url: Website or URL for more information about the company.
• name: The name of the company.
• about: Brief description of the company.
• description: More detailed information about the company's operations and offerings.
• organization_type: Type of the organization (e.g., private, public).
• industries: List of industries the company operates in.
• followers: Number of followers on the company's platform.
• headquarters: Location of the company's headquarters.
• country_code: Code for the country where the company is located.
• country_codes_array: List of country codes associated with the company (may represent various locations or markets).
• locations: Locations where the company operates.
• get_directions_url: URL to get directions to the company's location(s).
• formatted_locations: Human-readable format of the company's locations.
• website: The official website of the company.
• website_simplified: A simplified version of the company's website URL.
• company_size: Number of employees or company size.
• employees_in_linkedin: Number of employees listed on LinkedIn.
• employees: URL of employees.
• specialties: List of the company’s specializations or services.
• updates: Recent updates or news related to the company.
• crunchbase_url: Link to the company’s profile on Crunchbase.
• founded: Year when the company was founded.
• funding: Information on funding rounds or financial data.
• investors: Investors who have funded the company.
• alumni: Notable alumni from the company.
• alumni_information: Details about the alumni, their roles, or achievements.
• stock_info: Stock market information for publicly traded companies.
• affiliated: Companies or organizations affiliated with the company.
• image: Image representing the company.
• logo: URL of the official logo of the company.
• slogan: Company’s slogan or tagline.
• similar: URL of companies similar to this one.

Distribution

• Data Volume: 56.51M rows and 35 columns.
• Structure: Tabular format (CSV, Excel).

Usage

This dataset is ideal for:
- Market Research: Identifying key trends and patterns across different industries and geographies.
- Business Development: Analyzing potential partners, competitors, or customers.
- Investment Analysis: Assessing investment potential based on company size, funding, and industries.
- Recruitment & Talent Analytics: Understanding the workforce size and specialties of various companies.

Coverage

• Geographic Coverage: Global, with company locations and headquarters spanning multiple countries.
• Time Range: Data likely covers both current and historical information about companies.
• Demographics: Focuses on company attributes rather than demographics, but may contain information about the company's workforce.

License

CUSTOM

Please review the respective licenses below:

1. Data Provider's License
   • Bright Data Master Service Agreement

Who Can Use It

• Data Scientists: For building models, conducting research, or enhancing machine learning algorithms with business data.
• Researchers: For academic analysis in fields like economics, business, or technology.
• Businesses: For analysis, competitive benchmarking, and strategic development.
• Investors: For identifying and evaluating potential investment opportunities.

Dataset Name Ideas

• Global Company Profile Database
• **Business Intellige

Comprehensive dataset of 231 Web hosting companies in Missouri, United States as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Comprehensive dataset of 4 Web hosting companies in Astrakhan Oblast, Russia as of June, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Comprehensive dataset of 4,183 Web hosting companies in Netherlands as of June, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Crunchbase dataset to map your business ecosystem, make strategic decisions, and gather information on private and public companies. Common use cases include identifying investment opportunities, tracking company growth, and analyzing industry trends.

Use our Crunchbase Companies Information dataset to gain detailed insights into global startups and established companies across various industries. This dataset provides valuable company profiles, funding details, key executives, industry trends, and business performance, tailored for venture capitalists, market analysts, business development teams, and researchers.

By leveraging the Crunchbase Companies dataset, users can discover emerging startups, evaluate investment opportunities, track market growth, and perform competitive analysis. Whether you're seeking to enhance due diligence processes, identify new business prospects, or explore industry developments, this dataset empowers you to make data-driven decisions with confidence. Gain a deeper understanding of the business landscape and stay ahead in the competitive market by utilizing this essential dataset.

Dataset Features

Below is a breakdown of key dataset columns:
- name: The name of the company.
- url: Website or Crunchbase link for the company.
- id: Unique identifier for the company.
- cb_rank: Crunchbase ranking based on relevance and popularity.
- region: Geographic region where the company operates.
- about: Brief description of the company.
- industries: List of industries the company belongs to (e.g., photography, events, professional services).
- operating_status: Whether the company is active or inactive.
- company_type: Classification (e.g., for-profit, nonprofit).
- social_media_links: URLs to the company’s social media profiles.
- founded_date: Year or exact date when the company was founded.
- num_employees: Number of employees in the company.
- country_code: Country where the company is based.
- website: Official company website.
- contact_email: Contact email for the company.
- contact_phone: Contact phone number for the company.
- featured_list: Lists the company has been featured.
- full_description: Extended description of the company’s services or products.
- type: Type of organization (company, startup, etc.).
- uuid: Unique identifier for database tracking.
- active_tech_count: Number of technologies actively used by the company.
- builtwith_num_technologies_used: Number of technologies detected using BuiltWith.
- builtwith_tech: List of technologies used.
- ipo_status: Whether the company is public or private.
- similar_companies: URL of other companies similar to this one.
- image: Link to the company’s image or logo.
- monthly_visits: Estimated monthly web traffic.
- semrush_visits_latest_month: Website visits in the latest month according to SEMrush.
- semrush_last_updated: Last updated date for SEMrush traffic data.
- monthly_visits_growth: Change in web traffic over time.
- semrush_visits_mom_pct: Month-over-month percentage change in visits.
- num_contacts: Number of available contacts for the company.
- num_contacts_linkedin: Number of LinkedIn contacts.
- num_employee_profiles: Number of employee profiles available.
- total_active_products: Number of active products/services offered by the company.
- num_news: Number of news articles about the company.
- funding_rounds: Number of funding rounds the company has gone through.
- Bombora_last_updated: Bombora last updated date on website.
- num_investors: Number of investors associated with the company.
- legal_name: Official legal name of the company.
- num_event_appearances: Number of events the company has appeared in.
- num_acquisitions: Number of acquisitions made by the company.
- num_investments: Number of investments made by the company.
- num_advisor_positions: Number of advisor positions in the company.
- num_exits: Number of times the company has exited an investment.
- num_investments_lead: Number of times the company has led an investment round.
- num_sub_organizations: Number of sub-organizations under the company.
- num_alumni: Number of notable alumni from the company.
- Num_diversity_spotlight_investments: Number of diversity-focused investments.
- num_founder_alumni: Number of company founders who are alumni of a certain institution.
- num_funds: Number of investment funds the company has created.
- stock_symbol: Stock ticker symbol (if public).
- location: City and country where the company is headquartered.
- address: Full business address.
- contacts: List of business contacts.
- current_employees: Number of current employees.
- **semrush_loc

Comprehensive dataset of 2 Web hosting companies in Sichuan, China as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Graph and download economic data for All Employees: Information: Publishing Industries (Except Internet) in Denver-Aurora-Lakewood, CO (MSA) (SMU08197405051100001SA) from Jan 1990 to Dec 2022 about internet, printing, Denver, information, CO, employment, industry, and USA.

PredictLeads Key Customers Data provides essential business intelligence by analyzing company relationships, uncovering vendor partnerships, client connections, and strategic affiliations through advanced web scraping and logo recognition. This dataset captures business interactions directly from company websites, offering valuable insights into market positioning, competitive landscapes, and growth opportunities.

Use Cases:

✅ Account Profiling – Gain a 360-degree customer view by mapping company relationships and partnerships. ✅ Competitive Intelligence – Track vendor-client connections and business affiliations to identify key industry players. ✅ B2B Lead Targeting – Prioritize leads based on their business relationships, improving sales and marketing efficiency. ✅ CRM Data Enrichment – Enhance company records with detailed key customer data, ensuring data accuracy. ✅ Market Research – Identify emerging trends and industry networks to optimize strategic planning.

Key API Attributes:

• id (string, UUID) – Unique identifier for the company connection.
• category (string) – Type of relationship (e.g., vendor, client, partner).
• source_category (string) – Where the connection was detected (e.g., partner page, case study).
• source_url (string, URL) – Website where the relationship was found.
• individual_source_url (string, URL) – Specific page confirming the connection.
• context (string) – Extracted description of the business relationship (e.g., "Company X - partners with Company Y to enhance payment processing").
• first_seen_at (ISO 8601 date-time) – Date the connection was first detected.
• last_seen_at (ISO 8601 date-time) – Most recent confirmation of the relationship.
• company1 & company2 (objects) – Details of the two connected companies, including:
• - domain (string) – Company website domain.
• - company_name (string) – Official company name.
• - ticker (string, nullable) – Stock ticker, if available.

📌 PredictLeads Key Customers Data is an indispensable tool for B2B sales, marketing, and market intelligence teams, providing actionable relationship insights to drive targeted outreach, competitor tracking, and strategic decision-making.

PredictLeads Docs: https://docs.predictleads.com/v3/guide/connections_dataset

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

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

In 2021, French companies were able to present different types of online content to their customers. The information about the company came in first with 96 percent of enterprises creating this type of content. Furthermore, 78 percent of them posted opening times and contact information on their online channels.

In 2024, global online platform Alphabet generated ****** billion U.S. dollars in revenues. Online retail company Amazon was ranked first with over *** billion U.S. dollars in annual revenues, up from around *** billion U.S. dollars in the previous year.

As of March 2025, Google represented 79.1 percent of the global online search engine market on desktop devices. Despite being much ahead of its competitors, this represents the lowest share ever recorded by the search engine in these devices for over two decades. Meanwhile, its long-time competitor Bing accounted for 12.21 percent, as tools like Yahoo and Yandex held shares of over 2.9 percent each. Google and the global search market Ever since the introduction of Google Search in 1997, the company has dominated the search engine market, while the shares of all other tools has been rather lopsided. The majority of Google revenues are generated through advertising. Its parent corporation, Alphabet, was one of the biggest internet companies worldwide as of 2024, with a market capitalization of 2.02 trillion U.S. dollars. The company has also expanded its services to mail, productivity tools, enterprise products, mobile devices, and other ventures. As a result, Google earned one of the highest tech company revenues in 2024 with roughly 348.16 billion U.S. dollars. Search engine usage in different countries Google is the most frequently used search engine worldwide. But in some countries, its alternatives are leading or competing with it to some extent. As of the last quarter of 2023, more than 63 percent of internet users in Russia used Yandex, whereas Google users represented little over 33 percent. Meanwhile, Baidu was the most used search engine in China, despite a strong decrease in the percentage of internet users in the country accessing it. In other countries, like Japan and Mexico, people tend to use Yahoo along with Google. By the end of 2024, nearly half of the respondents in Japan said that they had used Yahoo in the past four weeks. In the same year, over 21 percent of users in Mexico said they used Yahoo.

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.

• Utilize GTM strategies to deliver personalized marketing experiences through
  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.

Research companies/Investors- Insights into the financial investments received by a company, including funding rounds, amounts, and investor details.

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...

Comprehensive dataset of 8 Web hosting companies in Erzurum, Turkey as of June, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

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...

Comprehensive dataset of 17 Web hosting companies in Province of Chieti, Italy as of June, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

General data recollected for the studio " Analysis of the Quantitative Impact of Social Networks on Web Traffic of Cybermedia in the 27 Countries of the European Union". Four research questions are posed: what percentage of the total web traffic generated by cybermedia in the European Union comes from social networks? Is said percentage higher or lower than that provided through direct traffic and through the use of search engines via SEO positioning? Which social networks have a greater impact? And is there any degree of relationship between the specific weight of social networks in the web traffic of a cybermedia and circumstances such as the average duration of the user's visit, the number of page views or the bounce rate understood in its formal aspect of not performing any kind of interaction on the visited page beyond reading its content? To answer these questions, we have first proceeded to a selection of the cybermedia with the highest web traffic of the 27 countries that are currently part of the European Union after the United Kingdom left on December 31, 2020. In each nation we have selected five media using a combination of the global web traffic metrics provided by the tools Alexa (https://www.alexa.com/), which ceased to be operational on May 1, 2022, and SimilarWeb (https:// www.similarweb.com/). We have not used local metrics by country since the results obtained with these first two tools were sufficiently significant and our objective is not to establish a ranking of cybermedia by nation but to examine the relevance of social networks in their web traffic. In all cases, cybermedia whose property corresponds to a journalistic company have been selected, ruling out those belonging to telecommunications portals or service providers; in some cases they correspond to classic information companies (both newspapers and televisions) while in others they refer to digital natives, without this circumstance affecting the nature of the research proposed. Below we have proceeded to examine the web traffic data of said cybermedia. The period corresponding to the months of October, November and December 2021 and January, February and March 2022 has been selected. We believe that this six-month stretch allows possible one-time variations to be overcome for a month, reinforcing the precision of the data obtained. To secure this data, we have used the SimilarWeb tool, currently the most precise tool that exists when examining the web traffic of a portal, although it is limited to that coming from desktops and laptops, without taking into account those that come from mobile devices, currently impossible to determine with existing measurement tools on the market. It includes: Web traffic general data: average visit duration, pages per visit and bounce rate Web traffic origin by country Percentage of traffic generated from social media over total web traffic Distribution of web traffic generated from social networks Comparison of web traffic generated from social netwoks with direct and search procedures

Uncover historical ownership history and changes over time by performing a reverse Whois lookup for the company Fujian-Tianzhi-Internet-Information-Technology-Stock-Co.-Ltd.

China Internet: Sales Revenue: Year to Date: Information Service data was reported at 618,800.000 RMB mn in Sep 2018. This records an increase from the previous number of 539,500.000 RMB mn for Aug 2018. China Internet: Sales Revenue: Year to Date: Information Service data is updated monthly, averaging 414,700.000 RMB mn from Jun 2017 (Median) to Sep 2018, with 15 observations. The data reached an all-time high of 646,900.000 RMB mn in Dec 2017 and a record low of 125,100.000 RMB mn in Feb 2018. China Internet: Sales Revenue: Year to Date: Information Service data remains active status in CEIC and is reported by Ministry of Industry and Information Technology. The data is categorized under China Premium Database’s Information and Communication Sector – Table CN.ICE: Internet: Internet Business.