Nielsen Holdings N.V. (NYSE: NLSN) is a global information and measurement company with leading market positions in marketing and consumer information, television and other media measurement, online intelligence, mobile measurement, trade shows and related properties. Nielsen has a presence in approximately 100 countries, with headquarters in New York, USA and Diemen, the Netherlands.
Nielsen Pop-Facts: Current Year Estimates & Projections
The Nielsen Demographic Estimation Program traces its history to the industry’s earliest years, and is completing its third decade in the hands of the industry’s most experienced demographers. The demographers now with the Nielsen team did the industry’s groundbreaking work in small area estimation, and continue to make contributions to the profession of applied demography.
Pop-Facts is a shorthand term for the massive set of demographic estimates and projections produced each year by Nielsen. Estimates are data prepared for current year, and projections (sometimes called forecasts) are prepared for dates five years in the future.
Pop-Facts is produced each year for many geographic levels including national, state, county, place (city/town), MCD, census tract, and block group. Data are also available for commonly used areas such as metropolitan areas, ZIP Codes, and media areas such as DMAs. Because they are produced for small areas, Pop-Facts can be easily aggregated to custom geographic areas specified by the user.
- Discover hidden high-growth areas before your competitors
- Identify population-related problems in existing stores
- Reduce the time and money you spend on market research
Pop-Facts starts with the estimation and projection of “base counts,” such as total population, household population, group quarters population, households, family households, and housing units. Characteristics related to these base counts are then estimated. Population characteristics include age, sex, race, and Hispanic ethnicity; households are estimated by age of householder and income; family households are estimated by income; and owner-occupied housing units are estimated by value.
Pop-Facts are prepared first for large geographic areas, then for progressively smaller areas, with adjustments ensuring consistency from one level to the next. In order to take full advantage of methodological refinements and new data resources, each set of updates begins not with the previous year’s estimates, but with data from the most recent decennial census. For this reason, the difference between estimates for consecutive years is not an estimate of change from one year to the next. Change is estimated with reference to the previous census numbers. The target estimation and projection date is January 1 of the relevant year.
Nielsen Consumer Buying Power
Nielsen Consumer Buying Power provides the most current consumer expenditures available. Enhanced methodology, expansion of categories and more clearly organized data make the Nielsen Consumer Buying Power database an outstanding information source. It contains current-year estimates and 5-year projections of total household expenditures for over 350 specific product categories, including goods and services, and 73 summary categories.
Additionally, Nielsen developed a cross-reference that leverages the Nielsen Consumer Buying Power database to estimate potential consumer expenditures by store types for 41 distinct retail store types. Breakdowns of average household expenditures are also available for 53 Yellow Page headings. The estimates also include College Dorm (group quarters) population expenditures in areas where college dorms are present.
Nielsen Consumer Buying Power data is an invaluable tool for target marketing. The following provides examples of applications for this type of data:
- Mobile phone service expenditures to better track consumers’ transition to wireless technology.
- Elder care expenses, a growing concern as baby boomers hit retirement age.
- Vitamins and other health supplements, a booming market added to better reflect society’s growing health concerns.
- Household Repair and Services facilitates exploration of homeowners’ trend to do-it-yourself projects and home remodeling.
- Tuition costs, expanded to better reflect the increased use of private education.
- Automotive sales’ differentiation between lease and purchase, new and used.
How Nielsen Consumer Buying Power (CBP) is Built
The database is created using statistical models estimated from the Bureau of Labor Statistics’ Consumer Expenditure Surveys (CEX) and the most current CES data available. Current Nielsen CBP data employs the most recent annual surveys (1997-2001). Nielsen has an archive of the CEX over many years, but uses the latest five years to update the Nielsen CBP model coefficients each year.
The methodology now includes an independent set of national-level expenditure estimates and projections. Developed by Global Insight, formerly Wharton Econometric Forecasting Associates (WEFA), national expenditure models are created as controls to update the national spending levels for Consumer Buying Power line items.
License the Nielsen Consumer Buying Power database and automatically receive the summary data found in the Consumer Buying Power Summary database -current-year aggregate household expenditures for 73 summary-level products/services in your local market. Summaries are created through the aggregation of individual variables into broad groupings. For example, the summary variable “Photographic Equipment” would provide total household expenditures for the specific variables “Film” + “Film Processing” + “Photographic Equipment”.
Nielsen CBP Expenditure Categories
Line items are summarized into product and service categories such as:
- Electronic Devices
- Food at Home
- Major Appliances
- Medical Expenses
- Personal Care
Nielsen CBP Retail Store Categories
Similar product/service categories are aggregated into broader groupings of 41 retail store types based on the type of store(s) in which specific products would likely be purchased. These groupings include:
- Eating places
- Sporting goods
Nielsen CBP by Yellow Page Headings
Line items are aggregated into 53 headings based on where products/services would most likely be found in the Yellow Pages section of your local phone directory. Groupings include headings such as:
- Lawn care services
- Major appliances
- Video rentals
Census & ZIP Code Boundary Maps
Businesses, Employee Counts and Sales
The Nation’s Most Comprehensive Database of U.S. Business and Employee Counts
Business-Facts® gives marketers access to U.S. business and employee count information for all types of companies, both large and small. This data can be used for a broad range of sales and marketing applications, including market analysis, site location, targeting, planning, and territory evaluation. Business-Facts is a national database covering business establishments and professionals in the U.S. and contains more than 12 million records.
How is the Business-Facts Database Built?
Beginning with Yellow Pages and White Pages phone directories, infoUSA collects data (number of employees, annual sales, SIC codes, and much more) on more than 12 million U.S. businesses. Beyond these two sources, infoUSA mines its base data from federal, state, and municipal government blue pages, annual reports for publicly-held companies, and industrial and regional business journals. Specific input data sources include:
- American Stock Exchange Facts Book
- Annual reports
- Big business directories
- Business and standard listings in the White Pages
- City directories
- County courthouse records for new business formations
- Industry directories
- IPO Reporter
- Major metropolitan newspapers
- NASDAQ Fact Book
- Standard & Poors Stock Guide
- State manufacturers directories
- The Wall Street Journal
- Yellow Pages
After compiling the base file, infoUSA runs the business information through several routines to ensure that the final product will be dependable for use by salespeople and marketers interested in using its contents for mailing campaigns. For instance, infoUSA processes the business file through Group 1 CASS Certified Software for address and ZIP Code verification. Furthermore, each month infoUSA runs the files against the National Change of Address (NCOA) and the Delivery Sequence files to ensure that business addresses are current and accurate.
infoUSA calls existing and new businesses at least once each year to verify information, collect additional data, and correct suspected errors. At least four attempts are made to contact each business. Large businesses (i.e., those with 100 or more employees) are phoned twice a year to verify their information. This activity results in 17 million out-bound telephone calls each year by infoUSA. Telephone verification concentrates on the following data elements:
- Name of owner or manager
- Number of employees
- Primary business activity
- Fax number
Details and Delivery Options
The Business-Facts/Basic Database consists of 11 major industrial groupings
- Agriculture, Forestry and Fishing
- Finance, Insurance, Real Estate
- Public Administration
- Retail Trade
- Transportation, Communication, Utilities
- Wholesale Trade
- Non-classifiable Establishments
Census & ZIP Code Boundary Maps
Business-Facts is a registered trademark of Nielsen.
Enhancement of the Base File by Nielsen
All data compilation, validation, and verification techniques outlined above result in a robust, thorough base file for use in creating the Business-Facts database. However, when the base file is delivered to Nielsen, additional enhancements are made to improve matching capabilities and provide greater integration into a range of applications, like mapping. For instance, employment data, sales figures, and point/geo codes (latitude, longitude, census tract, etc.) remain incomplete when Nielsen receives the data. The database development team at Nielsen adds value to the business data by populating fields that are left empty by infoUSA, providing the most precise point coding and creating an improved SIC roster.
Retail Market Power
The Retail Market Power® (RMP) database provides an actionable portrait of sales opportunity for optimal site and market analysis, so you can maximize your growth strategies by accurately targeting the sales gaps that exist in the marketplace. By using sales potential to depict supply and geography-based estimates of potential annual consumer expenditures to depict demand within a specific market, RMP enables an opportunity gap analysis of the retail environment. The database was developed using the Consumer Expenditure (CEX) surveys conducted by the Bureau of Labor Statistics and the Census of Retail Trade conducted by the US Census. Current-year (CY) supply and demand estimates and five-year (5Y) demand projections are available for all standard census, postal, and marketing geographies.
Supply Side Estimates
The base for the supply side or potential sales estimates for Retail Market Power is the Census of Retail Trade (CRT), a component of the Economic Census fielded by the U.S. Census Bureau. The county level data from CRT is updated by accounting for changes in business sales activity each year using wage & employment data from the BLS (the ES-202 file) and local sales tax data. The county level values are allocated to block groups based on employment counts from Business Facts. This results in block group level potential retail sales estimates by NAICS (North American Industrial Classification System). The NAICS categories are further break out by Merchandise Lines and adjusted to reflect current year totals of retail sales.
Data Sources for Potential Sales:
- Census of Retail Trade (CRT)
- Annual Survey of Retail Trade
- Nielsen Business-Facts
- Census of Employment & Wages
- State Sales Tax reports
- Trade Associations
Demand Side Estimates
The base for the demand side or potential expenditures estimates is the Consumer Expenditures Survey (CEX) from the Bureau of Labor Statistics. Estimates are produced by developing regression models of household expenditures for a wide range of goods and services. These household level models are combined with Nielsen current year demographic estimates to create geographic estimates of potential household demand for products and services. Using CRT information, those estimates are assigned to NAICS categories and used to estimate potential demand by NAICS code.
In order to ensure that the potential demand estimates are aligned with expenditures at the macro level, control totals are introduced into the development process. These control totals are obtained thorough Global Insights, which is the premier source of information at the national level. Trade Associations data is also a part of the control process and it serves as a measure of expenditures in specific industries. Similar to the supply side, estimates are developed using the NAICS standard.
Data Sources for Potential Expenditures:
- Consumer Expenditure Survey (CEX)
- Global Insights
- Nielsen Current Year demographics
- Trade Associations
Retail Market Power allows you to compare supply and demand to determine potential sources of revenue growth at any standard or user defined geographic level. Such comparison can be achieved at the retail outlet level or the merchandise line level. An opportunity gap appears when household expenditures levels for a specific geography are higher than the corresponding retail sales estimates. This difference signifies that resident households are meeting the available supply and supplementing their additional demand potential by going outside of their own geography. The opposite is true in the event of an opportunity surplus. That is, when the levels of household expenditures are lower than the retail sales estimates. In this case, local retailers are attracting residents of other areas in to their stores.
Nielsen PRIZM – Lifestyle & Behavior Segmentation System
PRIZM® is a revolutionary new segmentation system that harnesses the power of both household and geographic level data. PRIZM captures the essence of the existing PRIZM and MicroVision systems, while using a patent-pending methodology that marries demographic and lifestyle data to help companies target their customers.
PRIZM has a final schema–and it breaks new industry ground. The final model contains 66 segments consistent at both the household and geodemographic levels. PRIZM marks the first time marketers will have a means of using geodemographic segmentation, where appropriate and household-level segmentation, where appropriate–all using the same system. The 66-segment model resulted from these demographic drivers:
- Presence of Children
- Marital Status
The final 66 segments are arranged to make up two standard sets of groups: Social Group and Lifestage Group.
The 14 Social Groups are classified by are classified by three levels of affluence (low, moderate, high) and by the following four levels of urbanization:
- “Urban”: Mega-cities with density score of 85-99 (on scale of 0 to 99); Urban areas comprise 19% of U.S.
- “2nd City”: Cities and big towns with density scores of 40-85; 2nd Cities comprise 18% of total U.S.
- “Suburban”: Suburbs of Urban and 2nd City areas, with density scores of 40-90; Suburbs comprise 23% of total U.S.
- “Town & Country”: Exurbs and towns with density less than 40; Town & Country comprises 40% of l U.S.
“Density” refers to the density of population in neighborhoods. At its simplest, this involves dividing the total population of a particular census tract or block group by its land area and creating a density ranking of 0 to 99 (0 least dense, 99 most dense). For the PRIZM model, Nielsen’s Data Research & Development team devoted extensive resources to creating a more accurate measure and classification of neighborhood density.
Lifestage Groups – based on age, kids
The 11 Lifestage Groups are classified by three levels of affluence (low, moderate, high) and by one of three primary categories of age-and-children combinations:
- “Younger Years”: Largely under age 35, these households have few–if any–children. Households tend to be singles, although there are also couples that fall into this Lifestage.
- “Family Life”: Households with kids meet the primary criteria for this Lifestage. While the householder age range is broad–25 to 54–and there are some couples that fall into this Lifestage, the vast majority of households have at least one child under 18.
- “Mature Years”: Largely over age 45, these are empty–nest households–mostly couples whose kids have flown the coop.
Combine PRIZM with thousands of consumer behavior surveys to predict usage, expenditure and market penetration for products, services or activities in any geographical area.
Click here for details.
Census & ZIP Code Boundary Maps
Know your Customers with Nielsen PRIZM Segmentation
Nielsen MyBestProfiles gives you access to the results of thousands of consumer behavior surveys compiled by Simmons and MRI (Mediamark Research Inc.)
PCensus lets you combine the results of these surveys with PRIZM®market segmentation data to predict consumer behavior for products, services or activities in any geographical area.
For example, you can create a PCensus profile report for any area showing market penetration estimates for a restaurant chain (such as Wendy’s) or a beverage (such as Coca-Cola). Additionally, use PCensus “targeting” to identify areas of high market potential.
Combine data from MyBestProfiles with a Nielsen PRIZM database by taking the following steps:
1. Obtain the profiles needed for your project
The profiles encompass a wide variety of categories such as these from MRI:
- Alcohol and tobacco
- Apparel & Jewelry
- Automotive Products & Services
- Cable & Network TV Media Usage
- Financial, banking & Insurance
- Food & Beverage
- Gas Credit Cards & Chains
- Grocery Chains & Coupons
- Hardware & Appliances
- Health & OTC Drug
- Home Furnishings & Improvements
- Magazines & Newspapers
- Print & Radio Media Usage
- Retailers & Shopping
- Sports & Leisure
- Television Viewership
2. Select a specific product, service or activity
Each category is broken down into specific goods, services or providers. “Restaurants” represent over 100 chains such as: Arby’s, Burger King, Dairy Queen, KFC, McDonald’s, etc.
For example, you might select a Nielsen profile for households that have a propensity to eat at Wendy’s.
3. Order the profiles you need from Tetrad
4. Use the profile in PCensus to predict usage, expenditure and market penetration for the profiled item in any geographical area
Why Append PRIZM segments to your customer data?
PRIZM can help you learn all about your customers – their demographics, lifestyles and consumer behaviors. We can append PRIZM segments to your customer file of names and addresses to give a richly detailed profile of what your customers are like and why they buy from you.
How do you use the PRIZM profile of your customer with PCensus?
Location Analysis –
Use PCensus to profile the market area around a new or existing location to determine if there are sufficient households of the PRIZM segments that describe your customers or sites.
Finding Target Markets –
Use PCensus to find market areas (ZIP codes, counties, places, census tracts or block groups) that have households that match the PRIZM profile of your customers.
Contact Tetrad for more information on PRIZM and a cost estimate to process your client addresses.
PCensus Analyst is a powerful analyst tool that combines mapping, demographics and your data to create powerful analyses and compelling reports and visualizations.
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