Corporate Profits in the United States decreased to 3203.60 USD Billion in the first quarter of 2025 from 3312 USD Billion in the fourth quarter of 2024. This dataset provides the latest reported value for - United States Corporate Profits - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

The Economic Census is the U.S. Government's official five-year measure of American business and the economy. It is conducted by the U.S. Census Bureau, and response is required by law. In October through December of the census year, forms are sent out to nearly 4 million businesses, including large, medium and small companies representing all U.S. locations and industries. Respondents were asked to provide a range of operational and performance data for their companies.This dataset presents data on major categories of products sold/services rendered for establishments of firms with payroll by kind of business.

The Social Security Rate For Companies in the United States stands at 7.65 percent. This dataset provides - United States Social Security Rate For Companies - actual values, historical data, forecast, chart, statistics, economic calendar and news.

This private company dataset provides an in-depth view of any specific company’s truck-based supply chain and its relationships with other facilities and companies within the continental US.

Also, using robust supply chain data you will be able to map US facilities (including factories, warehouses, and retail outlets).

With this private company dataset, it is possible to track the movement of trucks and devices between locations to identify supply chain connections and company data insights.

Our Machine learning algorithms ingest 7-15bn daily events to estimate the volume of goods transported between locations. Consequently, we can map supply chain connections between:

•Different companies (expressed as a percentage of volume transported).

•Locations owned by the same company (e.g. warehouse to shop).

With this novel geolocation approach, it is possible to "draw" a knowledge graph of any private or public company´s relations with other companies within the country.

This solution, in the form of a dataset, provides an in-depth view of any specific company’s truck-based supply chain and its relationships with other facilities and companies within the continental United States.

Use cases:

• Identification and understanding of relations company-to-company: It helps to identify and infer relationships and connections between specific companies or facilities and between sectors/industries.

• Identification and understanding of relations place-to-place: A logistics and domestic distribution supply chain can be mapped, both nationwide and state-wide in the US, and across countries in Europe.

• Visualization and mapping of an entire supply chain network.

• Tracking of products in any distribution or supply chain.

• Risk assessment

• Correlation analysis.

• Disruption analysis.

• Analysis of illicit networks and tracking of illegal use of corporate assets.

• Improvement of casualty risk management.

• Optimization of supply chain risk management.

• Security and compliance.

• Identification of not only the first tier of suppliers in the value chain, but also 2nd and 3rd tier suppliers, and more.

Current largest use case: global corporation using it to model risk at a facility level (+100,000 locations).

Why should you trust PREDIK Data-Driven? In 2023, we were listed as Datarade's top providers. Why? Our solutions for private company data, supply chain data, and B2B data adapt according to the specific needs of companies. Also, PREDIK methodology focuses on the client and the necessary elements for the success of their projects.

A survey conducted from April to May 2022 found that six in 10 organizations in the United States designated an internal project manager or owner to manage compliance with state-level privacy laws. Around half of the organizations conducted data mapping and had an understanding of data practices across the organization. A further 41 percent said they updated privacy policies, while 40 percent said they were in the process of doing so.

United States - Total Business Sales was 1733841.00000 Mil. of $ in February of 2025, according to the United States Federal Reserve. Historically, United States - Total Business Sales reached a record high of 1974148.00000 in December of 2024 and a record low of 478951.00000 in January of 1992. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Total Business Sales - last updated from the United States Federal Reserve on May of 2025.

Overview:

This dataset provides a comprehensive look into the financial expenditures and profits of 50 startups based in the United States. It is an invaluable resource for analysts, economists, and business strategists seeking to understand the correlation between different types of spending and profitability in startup ventures.

Attributes: 1. R&D Spend: - Description: The amount of money each company has invested in Research and Development activities. - Data Type: Numeric (US dollars) - Importance: Indicates the company's commitment to innovation and technological advancement. 2. Administration: - Description: Expenditure on administrative functions and operations. - Data Type: Numeric (US dollars) - Relevance: Reflects the overhead costs associated with managing the company. 3. Marketing Spend: - Description: Investment in marketing and promotional activities. - Data Type: Numeric (US dollars) - Significance: A key factor in revenue generation and market penetration. 4. State: - Description: The U.S. state where the company is operating. - Data Type: Categorical (California, New York, or Florida) - Purpose: Provides geographical context and allows for regional analysis. 5. Profit: - Description: The net profit earned by the company. - Data Type: Numeric (US dollars) - Utility: A direct measure of the company’s financial success.

Potential Uses: - Business Analysis: Understanding how different types of spending (R&D, administration, marketing) affect profitability. - Regional Studies: Examining the impact of geographical location on business success. - Startup Growth: Insights into the financial practices of successful startups. - Economic Research: Data-driven study of the startup ecosystem in the U.S.

Target Audience: - Business Analysts and Economists - Marketing Strategists - Startup Consultants - Data Science Enthusiasts - Academic Researchers

Conclusion: This dataset is a rich resource for anyone looking to delve into the financial dynamics of startups in the U.S. It offers a unique perspective on how different types of investments correlate with company success across various states.

Please note that the data is anonymized and does not include any confidential information about the companies listed. The dataset is intended for educational and research purposes.

This dataset is about books. It has 36 rows and is filtered where the book subjects is Corporations-United States-Finance. It features 9 columns including author, publication date, language, and book publisher.

United States US: Start-Up Procedures to Register a Business data was reported at 6.000 Number in 2017. This stayed constant from the previous number of 6.000 Number for 2016. United States US: Start-Up Procedures to Register a Business data is updated yearly, averaging 6.000 Number from Dec 2013 (Median) to 2017, with 5 observations. The data reached an all-time high of 6.000 Number in 2017 and a record low of 6.000 Number in 2017. United States US: Start-Up Procedures to Register a Business data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Company Statistics. Start-up procedures are those required to start a business, including interactions to obtain necessary permits and licenses and to complete all inscriptions, verifications, and notifications to start operations. Data are for businesses with specific characteristics of ownership, size, and type of production.; ; World Bank, Doing Business project (http://www.doingbusiness.org/).; Unweighted average; Data are presented for the survey year instead of publication year.

Techsalerator covers all firmographic data of businesses in United States of America. Through our diligent local sourcing, we are able to provide firmographic data on businesses in United States of America.

This includes: Sales Volume/Revenue Number of employees, Number of locations / Years in Business

Companies use our firmographic data to enhance their databases and to do Telemarketing. They also use it to gain insight on other businesses.

Product contains one data file (.txt format) for each year from 1997-2023 containing 11-15 million records per year. Records provide information about business location (including address, census block, census tract & lat/long coordinates), number of employees, sales volume, NAICS & SIC codes, unique identifier across time for businesses and parent entities.

The Department of State keeps a record of every filing for every incorporated business in the state of New York. This dataset contains information on all active corporations as of the last business day of the specified month and year.

A survey conducted in April and May 2023 found that 60 percent of the companies that do business in the United States find it challenging to track the status of the data privacy legislation and the differences between state laws when preparing for changes in the data privacy laws. The challenge for around 50 percent of the respondents were increasing their budget because of the changes.

United States New Security Issues: US Corporations data was reported at 132.525 USD bn in May 2018. This records a decrease from the previous number of 132.763 USD bn for Apr 2018. United States New Security Issues: US Corporations data is updated monthly, averaging 138.365 USD bn from Feb 2003 (Median) to May 2018, with 184 observations. The data reached an all-time high of 328.777 USD bn in Mar 2007 and a record low of 42.698 USD bn in Aug 2008. United States New Security Issues: US Corporations data remains active status in CEIC and is reported by Federal Reserve Board. The data is categorized under Global Database’s USA – Table US.Z030: New Security Issues: Corporations.

Graph and download economic data for Quarterly Financial Report: U.S. Corporations: All Manufacturing: Total Assets (QFR223MFGUSNO) from Q4 2000 to Q1 2025 about finance, corporate, assets, manufacturing, industry, and USA.

This dataset provides an in-depth view of any specific company’s truck-based supply chain and its relationships with other facilities and companies within the continental US. We map US facilities (including factories, warehouses, and retail outlets) to companies. With this dataset, it is possible to track the movement of trucks and devices between locations to identify supply chain connections. Machine learning algorithms ingest 7-15bn daily events to estimate the volume of goods transported between locations. Consequently, we can map supply chain connections between: •Different companies (expressed as a percentage of volume transported). •Locations owned by the same company (e.g. warehouse to shop). With this novel geolocation approach, it is possible to "draw" a knowledge graph of any private or public company´s relations with other companies within the country. This solution, in the form of a dataset, provides an in-depth view into any specific company’s truck-based supply chain and its relationships with other facilities and companies within the continental United States. Use cases: - Identification and understanding of relations company-to-company: It helps to identify and infer relationships and connections between specific companies or facilities and between sectors/industries. - Identification and understanding of relations place-to-place: A logistics and domestic distribution supply chain can be mapped, both nationwide and state-wide in the US, and across countries in Europe. - Visualization and mapping of an entire supply chain network. - Tracking of products in any distribution or supply chain. - Risk assessment - Correlation analysis. - Disruption analysis. - Analysis of illicit networks and tracking of illegal use of corporate assets. - Improvement of casualty risk management. - Optimization of supply chain risk management. - Security and compliance. - Identification of not only the first tier of suppliers in the value chain, but also 2nd and 3rd tier suppliers, and more. Current largest use case: global corporation using it to model risk at a facility level (+100,000 locations).

The Corporate Financial Fraud project is a study of company and top-executive characteristics of firms that ultimately violated Securities and Exchange Commission (SEC) financial accounting and securities fraud provisions compared to a sample of public companies that did not. The fraud firm sample was identified through systematic review of SEC accounting enforcement releases from 2005-2010, which included administrative and civil actions, and referrals for criminal prosecution that were identified through mentions in enforcement release, indictments, and news searches. The non-fraud firms were randomly selected from among nearly 10,000 US public companies censused and active during at least one year between 2005-2010 in Standard and Poor's Compustat data. The Company and Top-Executive (CEO) databases combine information from numerous publicly available sources, many in raw form that were hand-coded (e.g., for fraud firms: Accounting and Auditing Enforcement Releases (AAER) enforcement releases, investigation summaries, SEC-filed complaints, litigation proceedings and case outcomes). Financial and structural information on companies for the year leading up to the financial fraud (or around year 2000 for non-fraud firms) was collected from Compustat financial statement data on Form 10-Ks, and supplemented by hand-collected data from original company 10-Ks, proxy statements, or other financial reports accessed via Electronic Data Gathering, Analysis, and Retrieval (EDGAR), SEC's data-gathering search tool. For CEOs, data on personal background characteristics were collected from Execucomp and BoardEx databases, supplemented by hand-collection from proxy-statement biographies.

In a 2024 survey of small business leaders and IT professionals in the United States, 58 percent of respondents stated that employee data was their most compromised company data in cyberattacks. Additionally, 53 percent of respondents reported customer or consumer data as the second most impacted company data.

Envestnet®| Yodlee®'s Retail Transaction Data (Aggregate/Row) Panels consist of de-identified, near-real time (T+1) USA credit/debit/ACH transaction level data – offering a wide view of the consumer activity ecosystem. The underlying data is sourced from end users leveraging the aggregation portion of the Envestnet®| Yodlee®'s financial technology platform.

Envestnet | Yodlee Consumer Panels (Aggregate/Row) include data relating to millions of transactions, including ticket size and merchant location. The dataset includes de-identified credit/debit card and bank transactions (such as a payroll deposit, account transfer, or mortgage payment). Our coverage offers insights into areas such as consumer, TMT, energy, REITs, internet, utilities, ecommerce, MBS, CMBS, equities, credit, commodities, FX, and corporate activity. We apply rigorous data science practices to deliver key KPIs daily that are focused, relevant, and ready to put into production.

We offer free trials. Our team is available to provide support for loading, validation, sample scripts, or other services you may need to generate insights from our data.

Investors, corporate researchers, and corporates can use our data to answer some key business questions such as: - How much are consumers spending with specific merchants/brands and how is that changing over time? - Is the share of consumer spend at a specific merchant increasing or decreasing? - How are consumers reacting to new products or services launched by merchants? - For loyal customers, how is the share of spend changing over time? - What is the company’s market share in a region for similar customers? - Is the company’s loyal user base increasing or decreasing? - Is the lifetime customer value increasing or decreasing?

Additional Use Cases: - Use spending data to analyze sales/revenue broadly (sector-wide) or granular (company-specific). Historically, our tracked consumer spend has correlated above 85% with company-reported data from thousands of firms. Users can sort and filter by many metrics and KPIs, such as sales and transaction growth rates and online or offline transactions, as well as view customer behavior within a geographic market at a state or city level. - Reveal cohort consumer behavior to decipher long-term behavioral consumer spending shifts. Measure market share, wallet share, loyalty, consumer lifetime value, retention, demographics, and more.) - Study the effects of inflation rates via such metrics as increased total spend, ticket size, and number of transactions. - Seek out alpha-generating signals or manage your business strategically with essential, aggregated transaction and spending data analytics.

Use Cases Categories (Our data provides an innumerable amount of use cases, and we look forward to working with new ones): 1. Market Research: Company Analysis, Company Valuation, Competitive Intelligence, Competitor Analysis, Competitor Analytics, Competitor Insights, Customer Data Enrichment, Customer Data Insights, Customer Data Intelligence, Demand Forecasting, Ecommerce Intelligence, Employee Pay Strategy, Employment Analytics, Job Income Analysis, Job Market Pricing, Marketing, Marketing Data Enrichment, Marketing Intelligence, Marketing Strategy, Payment History Analytics, Price Analysis, Pricing Analytics, Retail, Retail Analytics, Retail Intelligence, Retail POS Data Analysis, and Salary Benchmarking

1. Investment Research: Financial Services, Hedge Funds, Investing, Mergers & Acquisitions (M&A), Stock Picking, Venture Capital (VC)

2. Consumer Analysis: Consumer Data Enrichment, Consumer Intelligence

3. Market Data: AnalyticsB2C Data Enrichment, Bank Data Enrichment, Behavioral Analytics, Benchmarking, Customer Insights, Customer Intelligence, Data Enhancement, Data Enrichment, Data Intelligence, Data Modeling, Ecommerce Analysis, Ecommerce Data Enrichment, Economic Analysis, Financial Data Enrichment, Financial Intelligence, Local Economic Forecasting, Location-based Analytics, Market Analysis, Market Analytics, Market Intelligence, Market Potential Analysis, Market Research, Market Share Analysis, Sales, Sales Data Enrichment, Sales Enablement, Sales Insights, Sales Intelligence, Spending Analytics, Stock Market Predictions, and Trend Analysis

Access B2B Contact Data for North American Small Business Owners with Success.ai—your go-to provider for verified, high-quality business datasets. This dataset is tailored for businesses, agencies, and professionals seeking direct access to decision-makers within the small business ecosystem across North America. With over 170 million professional profiles, it’s an unparalleled resource for powering your marketing, sales, and lead generation efforts.

Key Features of the Dataset:

Verified Contact Details

Includes accurate and up-to-date email addresses and phone numbers to ensure you reach your targets reliably.

AI-validated for 99% accuracy, eliminating errors and reducing wasted efforts.

Detailed Professional Insights

Comprehensive data points include job titles, skills, work experience, and education to enable precise segmentation and targeting.

Enriched with insights into decision-making roles, helping you connect directly with small business owners, CEOs, and other key stakeholders.

Business-Specific Information

Covers essential details such as industry, company size, location, and more, enabling you to tailor your campaigns effectively. Ideal for profiling and understanding the unique needs of small businesses.

Continuously Updated Data

Our dataset is maintained and updated regularly to ensure relevance and accuracy in fast-changing market conditions. New business contacts are added frequently, helping you stay ahead of the competition.

Why Choose Success.ai?

At Success.ai, we understand the critical importance of high-quality data for your business success. Here’s why our dataset stands out:

Tailored for Small Business Engagement Focused specifically on North American small business owners, this dataset is an invaluable resource for building relationships with SMEs (Small and Medium Enterprises). Whether you’re targeting startups, local businesses, or established small enterprises, our dataset has you covered.

Comprehensive Coverage Across North America Spanning the United States, Canada, and Mexico, our dataset ensures wide-reaching access to verified small business contacts in the region.

Categories Tailored to Your Needs Includes highly relevant categories such as Small Business Contact Data, CEO Contact Data, B2B Contact Data, and Email Address Data to match your marketing and sales strategies.

Customizable and Flexible Choose from a wide range of filtering options to create datasets that meet your exact specifications, including filtering by industry, company size, geographic location, and more.

Best Price Guaranteed We pride ourselves on offering the most competitive rates without compromising on quality. When you partner with Success.ai, you receive superior data at the best value.

Seamless Integration Delivered in formats that integrate effortlessly with your CRM, marketing automation, or sales platforms, so you can start acting on the data immediately.

Use Cases: This dataset empowers you to:

Drive Sales Growth: Build and refine your sales pipeline by connecting directly with decision-makers in small businesses. Optimize Marketing Campaigns: Launch highly targeted email and phone outreach campaigns with verified contact data. Expand Your Network: Leverage the dataset to build relationships with small business owners and other key figures within the B2B landscape. Improve Data Accuracy: Enhance your existing databases with verified, enriched contact information, reducing bounce rates and increasing ROI. Industries Served: Whether you're in B2B SaaS, digital marketing, consulting, or any field requiring accurate and targeted contact data, this dataset serves industries of all kinds. It is especially useful for professionals focused on:

Lead Generation Business Development Market Research Sales Outreach Customer Acquisition What’s Included in the Dataset: Each profile provides:

Full Name Verified Email Address Phone Number (where available) Job Title Company Name Industry Company Size Location Skills and Professional Experience Education Background With over 170 million profiles, you can tap into a wealth of opportunities to expand your reach and grow your business.

Why High-Quality Contact Data Matters: Accurate, verified contact data is the foundation of any successful B2B strategy. Reaching small business owners and decision-makers directly ensures your message lands where it matters most, reducing costs and improving the effectiveness of your campaigns. By choosing Success.ai, you ensure that every contact in your pipeline is a genuine opportunity.

Partner with Success.ai for Better Data, Better Results: Success.ai is committed to delivering premium-quality B2B data solutions at scale. With our small business owner dataset, you can unlock the potential of North America's dynamic small business market.

Get Started Today Request a sample or customize your dataset to fit your unique...