About Data Axle Historical US Business
Formerly named Infogroup Business USA, this dataset provides establishment-level information on businesses in the United States, at national, state, county, and ZIP code levels. Data on businesses in US territories are also included. Data are collected from multiple sources, including direct calls to businesses. The resource is a comprehensive source of information on small- and medium-sized businesses.
About Data Axle
Established in 1972 as Infogroup, Data Axle is a big data, analytics, and marketing services provider. Data Axle provides both digital and traditional marketing channel expertise drawing on proprietary data collected on millions of U.S. businesses.
Click on the links below to view DataSheets comprising statistical abstracts complete with infographics of indicators describing US business and industry created in Sage Data. Log in to explore the data at even more granularity - as well as relationships between these statistics and other indicators in the vast Sage Data repository.
The integration of the Data Axle Historical US Business dataset into Sage Data allows users to drill deep into the dataset and create customized charts, trends, rankings, and maps comparing companies, company subsidiaries, and industries across states, counties, and ZIP codes. Analyze competing companies; explore industries for untapped opportunity; target communities for product launch; and much more. In reviewing the samples below, identify the question(s) the data answers for marketing and entrepreneurial initiatives.
Residential Building Construction industries - ranking of Arizona counties
Golf Courses and Country Clubs - ranking of South Carolina ZIP codes by count of employees of golf courses and country clubs
Agriculture, Forestry, Fishing and Hunting revenue/sales - ranking of revenue/sales earnings of agriculture industries in California counties
Oil and Gas Extraction industries - ranking of the top 15 Texas counties by count of companies involved in oil and gas extraction
Fruit and Tree Nut Farming - compares the trend in revenue and sales earnings of fruit and tree nut farming in Georgia and Florida.
Urban Transit Systems - compares counts of employees in Illinois and New York
Burger King locations - ranks US states by number of Burger King locations in 2015
Burger King revenue/sales - compares revenue/sales at two Burger King locations in Maryland
The many indicators included in Data Axle Historical US Business can be viewed as stand-alone trends, charts, or maps in Sage Data. View the listing of indicators opening the Data Axle Reference Solutions: Historical US Business entries in the Browse by Source or Browse by Subject - Industry, Business, and Commerce. For example, the chart below ranks California counties by the number of retail bakeries located in each, using data at the 6-digit NAICS level found in the Industry Detail - Company Count indicator.
Note that you can learn more about the indicator, dataset, and source by viewing the statistical abstract that appears below the chart, as below. These summaries can be exported with the graph by clicking on the Export link in the menu bar above the chart. The Create DOI link allows you to create a DOI that ensures that each time you reference the data in a paper or elsewhere that the reader can view the exact view of the DataSheet at the time you created it. For more information on DOIs, click here.
The unique implementation of Data Axle Historical US Business in Sage Data allows you to compare indicators across industries, states, counties, and zip codes, and to create trends, rankings, and more - so be sure to explore the many options available to do so. To select multiple indicators, use the Compare Datasets option at the top of the Dataset list:
See the examples below and try it yourself with other indicators and geographies. Keep in mind that the graphs you create do not necessarily imply causality: the results may suggest a potential relationship between the variables you select, which may be an interesting line of inquiry for your own research.
Use Sage Data to compare and contrast Data Axle Historical US Business data across geographies. For example, the chart below compares revenue/sales earnings of appliance repair and maintenance industries in two Pennsylvania counties:
The trend below compares revenue/sales earnings of aquaculture vs fishing industries in Maine, 1997-2020.
You can also create charts comparing Historical US Business indicators with other indicators in the Sage Data repository. For example, the chart below ranks Colorado counties with respect to numbers of households with earnings, using data from the American Community Survey, and the numbers of securities firms in the county. Does the data suggest any business opportunities that might be worth further exploration?
About Data Axle Historical US Residential
Formerly named Infogroup Residential USA, this dataset provides household-level information on residences in the United States, at national, state, county, census tract, and ZIP code levels. Estimates of household income, wealth, purchasing power, and home value by residences are segmented by household and dwelling characteristics, allowing users to analyze community growth and declines in population and economic levels over time across geographies.
About Data Axle
Established in 1972 as Infogroup, Data Axle is a big data, analytics, and marketing services provider. Data Axle provides both digital and traditional marketing channel expertise drawing on proprietary data collected on millions of U.S. businesses.
Click on the links below to view DataSheets comprising statistical abstracts complete with infographics of indicators describing US business and industry created in Sage Data. Log in to explore the data at even more granularity - as well as relationships between these statistics and other indicators in the vast Sage Data repository.
The integration of the Data Axle Historical US Residential dataset into Sage Data allows users to drill deep into the dataset and create customized charts, trends, rankings, and maps comparing areas by household and dwelling characteristics. The data provides rich opportunity to understand an area's social and economic profile informing business and policy development initiatives.
Number of Credit Cards of Household by Home Value - ranking of % of households with 1 vs 4 credit cards by value of home in Maricopa County, Arizona.
Home Value by Year Built - ranking of Fairfield County, Connecticut, homes with an estimated value of $600,000-$699,999 by year built
Households with Annual Income over $500,000 - maps Virginia households with estimated annual household income over $500,000
Household Income by Number of Children - ranks households with estimated annual income of $75,000-$99,999 by number of children in Austin County, Texas.
Household Purchasing Power by Location Type - maps Texas counties by percentage of households with estimated purchasing power of $1-$24,999 that reside in single-family dwellings.
Household Purchasing Power by Age of Head of Household - ranks percentage of households with estimated purchasing power of over $500,000 by age of head of householder in Boulder, Colorado.
Household Wealth by Square Footage of Dwelling - ranks Wyoming households with estimated wealth of $1,000,000-$2,499,999 by square footage of the household dwelling.
Household Wealth by Length of Residence - ranks Florida households that have resided at their residence 20 or more years by estimated household wealth.
The many indicators included in Data Axle Historical US Residential can be viewed as stand-alone trends, charts, or maps in Sage Data. View the listing of indicators opening the Data Axle Reference Solutions: Historical US Residential entries in the Browse by Source or Browse by Subject - Population and Income. For example, the chart below ranks Cook County (Illinois) households by percentage renting or owning their residence.
Note that you can learn more about the indicator, dataset, and source by viewing the statistical abstract that appears below the chart, as below. These summaries can be exported with the graph by clicking on the Export link in the menu bar above the chart. The Create DOI link allows you to create a DOI that ensures that each time you reference the data in a paper or elsewhere that the reader can view the exact view of the DataSheet at the time you created it. For more information on DOIs, click here.
The unique implementation of Data Axle Historical US Residential allows you to compare indicators across industries, states, counties, and zip codes, and to create trends, rankings, and more - so be sure to explore the many options available to do so. To select multiple indicators, use the Compare Datasets option at the top of the Dataset list:
See the examples below and try it yourself with other indicators and geographies. Keep in mind that the graphs you create do not necessarily imply causality: the results may suggest a potential relationship between the variables you select, which may be an interesting line of inquiry for your own research.
Use Sage Data to compare and contrast Data Axle Historical US Residential data across geographies. For example, the chart below compares counts of residences with home values in the $900,000 - $999,999 range in four Southern states:
The trend below compares households by length of residence in two Pennsylvania counties:
You can also create maps showing locations of households by household and dwelling characteristics. For example, the infographic below maps New York ZIP codes by counts of households with estimated wealth between $1 million and $2,499,999, and two children:
About Data Axle Historical Canadian Business
The Data Axle (formerly Infogroup) Historical Canadian Business dataset provides establishment-level information on businesses in Canada at the national, provincial, territorial, and forward sortation area levels. Data are collected from multiple sources, including direct calls to businesses. The resource is a comprehensive source of information on small- and medium-sized businesses.
About Data Axle
Established in 1972 as Infogroup, Data Axle is a big data, analytics, and marketing services provider. Data Axle provides both digital and traditional marketing channel expertise drawing on proprietary data collected on millions of U.S. businesses.
Click on the links below to view DataSheets comprising statistical abstracts complete with infographics of indicators describing US business and industry created in Sage Data. Log in to explore the data at even more granularity - as well as relationships between these statistics and other indicators in the vast Sage Data repository.
The integration of the Data Axle Historical Canadian Business dataset into Data Planet allows users to drill deep into the dataset and create customized charts, trends, rankings, and maps comparing companies and industries across Canadian geographies. Analyze competing companies; explore industries for untapped opportunity; target communities for product launch; and much more. In reviewing the samples below, identify the question(s) the data answers for business and economic development initiatives.
Residential Building Construction industries - ranking of provinces and territories by counts of residential building construction companies
Audio and Video Manufacturing - ranks provinces and territories by number of persons employed in audio and video manufacturing businesses
Silverware, jewelry and plated ware manufacturing - compares trend in number of persons employed in silverware, jewelry and plateware manufacturing in the western provinces
Liquor Stores revenue and sales - compares trends in four Canadian provinces
Arts, recreation and amusement - maps Canadian provinces by revenue and sales in these industries
Compares 2023 revenue/sales for animal rescue societies in Ontario and British Columbia
The many indicators included in Data Axle Historical Canadian Business can be viewed as stand-alone trends, charts, or maps in Sage Data. View the listing of indicators opening the Data Axle Reference Solutions: Historical Canadian Business entries in the Browse by Source or Browse by Subject - Industry, Business, and Commerce listings. For example, the chart below ranks Canadian provinces and territories by the number of retail bakeries located in each, using data at the 6-digit NAICS level found in the Industry Detail by NAICS - Company Count indicator.
Note that you can learn more about the indicator, dataset, and source by viewing the statistical abstract that appears below the chart, as below. These summaries can be exported with the graph by clicking on the Export link in the menu bar above the chart. The Create DOI link allows you to create a DOI that ensures that each time you reference the data in a paper or elsewhere that the reader can view the exact view of the DataSheet at the time you created it. For more information on DOIs, click here.
The unique implementation of Data Axle Historical Canadian Business in Sage Data allows you to compare indicators across industries, provinces and territories, and postal areas - so be sure to explore the many options available to do so. To select multiple indicators, use the Compare Datasets option at the top of the Dataset list:
See the examples below and try it yourself with other indicators and geographies. Keep in mind that the graphs you create do not necessarily imply causality: the results may suggest a potential relationship between the variables you select, which may be an interesting line of inquiry for your own research.
Use Data Planet to compare and contrast Data Axle Historical Canadian Business data across geographies. For example, the chart below compares revenue/sales earnings of household appliance stores in the western provinces.
The chart below ranks provinces and territories by revenue/sales earnings of aquaculture vs fishing industries.
You can also create charts comparing Historical Canada Business indicators with other indicators in the Data Planet repository. For example, the chart below ranks Canadian provinces and territories by count of population from the Canadian Census of Population and Housing and counts of employees working in health services.
As reported by Data Axle's Database Content Group Reference Solutions, location employment represents the number of employees at that location of the business. Volunteers are only included when there are no paid employees. The database carries two separate employment number fields: Location and Corporate. Location employment is available on 98% of the businesses and is largely obtained through telephone verification.
Reported versus Modeled Values
When an employment number cannot be verified through the telephone interview process, a model is applied to estimate the employment size. Approximately 47% of businesses carry a modeled employment number rather than a verified number. The model uses a multi-step approach, with over 8 million telephone verified employment figures as the cornerstone, to create the most accurate estimated employment information possible.
The model considers records that are part of a chain or corporate family and compares that to actual data for similar locations in similar geographies. For records that are not part of chain or corporate family, the model profiles actual data for records with the same 6-digit, then 4-digit SIC assignments within similar geographies. The model also takes into account the number of SIC’s assigned per business, as businesses serving multiple industries tend to have more employees than businesses with just one line of business or SIC. Professional records, such as doctors, dentists, and lawyers, have their own modeling rules because of their unique structure. Yet, the same modeling principles and similar techniques are applied.
Accuracy
To ensure accuracy, employment information is verified through the telephone interview process and compared to modeled information each month. Data Axle’s employment model is 95% accurate within 2 employee size ranges and 100% accurate within 3 employee size ranges.
Monthly audits are performed to validate location employment numbers focusing on locations with 500+ employees. Businesses with 10,000+ employees and certain industries, such as churches, restaurants, and associations, are re-validated.
Employee Size Distribution
Data Axle maintains a true employee count, even when the value is applied through a model. Additionally, an employee size code is assigned:
Certain industries are not eligible to possess a location employee size count. These include Automated Teller Machines, Coin Counting/Sorting Kiosks, Propane Tank Kiosks, Video Rental Kiosks, and Unclassified Businesses (SIC 999977).
Corporate Employee Size
Corporate employee size is only available on records in the Data Axle database that are coded as corporate parents or subsidiary headquarters (approximately 25,000 businesses). The corporate employment number represents the company wide number of employees for that parent or subsidiary headquarters. Such locations are also eligible to have a location employee size assigned reflecting the number of employees specific to that location.
All of these corporate employment figures are actual numbers from telephone interviews, annual reports, newspapers and periodicals. Infogroup does not model or sum corporate employment.
According to Data Axle, an estimate of annual location sales volume is available on the majority of the records that have a location employment figure. Because verifiable sales volume figures are virtually impossible to obtain from private businesses, Data Axle has developed, and continually improves, a model that estimates the sales volume for the company. The model’s primary source is the U.S. Department of Commerce data on sales per employee for each 6-digit NAICS code. Data Axle then leverages data from the Data Axle database including the number of employees at the location, industry codes (4-digit SIC and 6-digit NAICS), and the state the business resides in to calculate the estimated sales volume. The model is refreshed every five years following release of the U.S. Economic Census results.
Corporate sales volume is only available on records in the Data Axle Historical US Business database that are coded as parents or subsidiary headquarters. About 20,000 records carry this data. The corporate sales volume figures are actual numbers compiled from annual reports, newspapers, and periodicals. Data Axle does not model or sum the corporate sales volume figures.
