If you are not using at least one of these five free data sources right now, every day, in your work, you probably should be. If you are not giving praise and thanks to all of our talented and dedicated research colleagues in the federal government every day, you definitely should be.

Why? Because you have access to some of the richest and most useful data, produced by the most rigorously designed research methods, anywhere on the planet. All for free, and all easy to access. I guarantee this data is relevant and valuable for the work you do.

Our government has something called the U.S. Federal Statistical System, which encompasses 125 agencies that are engaged, to some degree, in collecting data and producing statistics. The Census Bureau is the big one, but there are others covering topics on every facet of American life. The data is used by federal, state, and local governments to make fact-based decisions about our communities. What is more, the data is made available to all citizens and private businesses to use as well.

Not sure how you should be using this data or where to begin? Consider these five data sets, from among many you can choose, which we at Versta Research find most useful in our work.

The Economic Census

Every five years, the U.S. Census Bureau collects extensive statistics about businesses. It is an official count known as the Economic Census. Nearly 4 million businesses, large, medium and small, covering most industries and all geographic areas of the United States, receive surveys tailored to their primary business activity.

Key statistics produced from the Economic Census are:

• Total number of establishments
• Value of sales, shipments, receipts, and revenue
• Primary business activity
• Total number of employees
• Total annual payroll
• Total first quarter payroll
• Industry-specific statistics

Data is sliced and diced by over 950 detailed industries classified using the North American Industry Classification System (NAICS), and by nearly 21,000 geographic areas.

What we use it for: Many of Versta Research’s studies focus on the business customers of our clients, including the benefits plans, insurance products, technology tools, and the machinery they buy. To get our sampling right, we need to know how many businesses there are in specific industries and locations. We also need to know the size of those businesses, both in terms of revenue and number of employees.

We always weight our B2B survey data to match benchmarks provided by the Census Bureau’s Economic Census (sometimes weighting by number of companies, sometimes by number of employees, sometimes by revenue). This helps us accurately project our survey findings to the target population our clients care about.

The American Community Survey

The American Community Survey (ACS) is the foundational, ongoing survey that most of us generically and routinely refer to as “Census Data.” Data are updated and released annually, and it provides a much deeper look into the demographics of the U.S. population than the decennial census.

It collects data at the household level (who lives together as families, their relationships to each other, household income, etc.) and at the person level (age, sex, occupation, educational attainment, and so on) and the two levels of data can be easily matched and merged.

Here are just some of the amazing data available through the ACS:

• Age
• Ancestry
• Commuting/journey to work
• Computer and internet use
• Educational attainment
• Employment status
• Grandparents as caregivers
• Health insurance coverage
• Hispanic origin
• Income
• Industry, occupation, and class of worker
• Language spoken at home
• Marital status/marital history
• Ownership, home value, rent
• Place of birth, citizenship, year of entry
• Race
• School enrollment
• Sex
• Housing characteristics

And there is more!

What we use it for: Many of our studies use techniques of public polling, or we survey consumers about the products the buy. This always has us asking about how many people there are in certain age groups, in specific income brackets, in specific employment sectors, who have children under 18, etc. Once we know the details of the population, we can develop effective sampling strategies to ensure our survey represents the targets we want to understand.

We nearly always weight our consumer and general public surveys to match benchmarks we develop from our analysis of the American Community Survey. This data is truly foundational, and at Versta Research we keep active working files at the ready, and we update our files annually.

The Survey of Consumer Finances

The Survey of Consumer Finances (SCF) is a survey of U.S. families conducted every three years by the Federal Reserve board. It goes much deeper into all aspects of household finances than the Census Bureau’s American Community Survey. If, for example, you want to know about Americans’ investable assets or 401(k) savings, this is the data you need.

The survey includes a sample of roughly 6,500 families, which is decent, but it means that data cuts by subgroups can be difficult. In fact, in order to protect the anonymity of the respondents, no geographic data is provided.

The data are extremely detailed, and somewhat complicated to work with. But there are excellent resources to help, including fully extracted SAS, STATA, and Excel datasets with constructed summary variables. The University of California at Berkeley provides a helpful analysis tool that has all the summary data loaded and ready to analyze. If you’re working with the raw data, this is a perfect way to cross check that your basic marginals and tabulations are correct.

Data includes:

• Economic expectations
• Use of financial institutions
• Credit cards
• Principal residence and real estate
• Lines of credit
• Loans to others
• Businesses owned
• Vehicles owned
• Educational loans
• Other loans
• Attitudes about saving, investing, and credit
• Financial assets
• Work and pensions
• Income and taxes
• Income expectations
• Inheritance and charity

What we use it for: Many of our studies are for financial companies who want to understand, target, or segment consumers based on assets, not income. And often we are interested in specific types of assets (or debits against their assets)—student loans, 401(k) savings, pension plans, and so on. This is our go-to resource for detailed financial profiles of the U.S. population.

The data helps us predict sampling incidence and research feasibility (and estimate research costs), and it provides solid benchmarks against which we can develop our sampling strategies and then weight our final data.

Occupational Employment Statistics

You’ve heard of the Consumer Price Index, right? That invaluable nugget of data is produced by the Bureau of Labor Statistics. It represents one piece of a treasure trove of data the bureau helps generate, tabulate, archive, and make available for everyone to use for free.

The BLS data we use most at Versta Research is from a major ongoing survey conducted by BLS as part of its Occupational Employment Statistics (OES) program. In ongoing, overlapping 6-month cycles, the OES program surveys 1.2 million businesses every three years. With their survey data they produce a rich repository of data with annual U.S. estimates for:

• Number of employees
• Average wages
• By 800+ occupations
• National data overall
• State-level data
• Metropolitan-area-level data
• By 415+ industry classifications (available at the sector, 3-, 4-, and selected 5- and 6-digit North American Industry Classification System—NAICS—industrial groups)

What we use it for: For B2B studies we usually target specific professions, types of employees, and types of decision makers. OES data is like the American Community Survey of job titles. We need to know how many workers there are, at what levels of professional expertise, in what industries, and in what areas of the country. It guides us in our sampling strategies and weighting for the survey work we do on behalf of clients who need to understand business-level decision makers.

As an example, we often conduct surveys of HR professionals. Recently we needed to understand those who work in employee benefits administration. We combined OES data about the number of HR professionals with additional data from SHRM (Society for Human Resource Management) detailing the ratio of employees to HR staff. We then used estimates to weight our own survey data to ensure accurate representation of our target market.

National Health Interview Survey

The National Health Interview Survey (NHIS) collects data on a broad range of health topics through personal household interviews. There is over 50 years worth of health data about the U.S. population tracking changes in health status and health care access. The NHIS is one of the major data collection programs within the Centers for Disease Control and Prevention (CDC).

One of the major strengths of this survey is that it provides details about health by many demographic and socioeconomic characteristics. The annual sample size for this survey is approximately 35,000 households containing about 87,500 persons (with all interviewing done in person!) and the response rate of NHIS is an amazing 70 percent of eligible households in the sample. The survey gathers health data about adults and children of every age.

Data available from NHIS include:

• Physical and mental health status
• Physical limitations and injuries
• Chronic conditions, including asthma and diabetes
• Access to and use of health care services
• Health insurance coverage and type of coverage
• Health-related behaviors, including smoking, alcohol use, and physical activity
• Measures of functioning and disability
• Immunizations
• Demographics, including age, gender, race, ethnicity, income and assets

What we use it for: Versta Research does a great deal of work in healthcare, so we are always trying to assess incidences of specific diseases, disabilities, and physical limitations in order to assess feasibility and costs for conducting custom research. By analyzing NHIS data we are able to derive incidences, demographic profiles, and sampling strategies for our target populations.

One interesting application for which we have used this data is the development of an apples-to-apples benchmark for health comparisons. We have been helping The United Methodist Church track the health of its active clergy for a decade. We developed a method of analyzing NHIS data to match exactly the demographics of their clergy population. We match on age, gender, marital status, race, ethnicity, region, and current employment, and provide more powerful benchmarks that allow us to assess the impact of vocational risks and health initiatives undertaken to mitigate those risks.