Demographics Databases, and 2010 Demographic Updates from Scan/US on mapdata2go.com
 

This is a short guide to demographic data items, as used in mapping. Two sections shown after the map illustration on this page explain "Universe" data items, show the categories of demographic data items, and a guide to 'array variables'.

This page contains information any trained demographics data salesperson would tell you in a pre-sales conversation, and some information they might not mention.

Demographics

The term 'demographics' is a shorthand term for 'population characteristics'.

Demographic info is used to decide where to locate new stores, or other commercial activity. Demographics of a vicinity can be used to evaluate an existing store.

There is really just one geographic data item: 'vicinity', or 'nearness.' How many people are near a location, and what are their characteristics?

Vicinity 101A — simple headcount

One type of vicinity info that a business needs can be expressed as a question. "How close are people to my store?" If the business has customer records, they can calculate the distance to their store, and treat this distance as a demographic variable.

If the business does NOT have customer records, they can calculate the distance from their store to nearby geographic data containers such as Scan/US MicroGrids or Census blocks, and use this distance information to build a "gravity" or "attraction" model.

Vicinity 101B — who's near?

The other type of "vicinity" information uses fine-grained geography for one of two purposes: 1) to find niches of wealth, poverty, youth or age, male or female, and "cater to" these specific "demographics" or 2) to use the "birds of a feather flock together" principle to find, from customers whose locations are known, specific characteristics of the neighborhood in which they reside. The assumption, then, is that they will share the neighborhood characteristics, and that similar neighborhoods can be target-marketed. The assumption is the foundation of locale-based segmentation systems. (Experian's MOSAIC, carried in this product catalog, is one such segmentation system).

Income

Demographic datasets carry all different kinds of income: median income, average income , per capita income , disposable income , aggregate income , household income by age of head of householder. Having so many types of income is a consequence of an effort to represent income in one single most-useful number.

Expenditure

There are two kinds of expenditure data sources: survey data from a large panel that is extrapolated to cover all households, and data from actual sales.

Data from actual sales is often closely held by each sales organization and, when available, is not matched to the households in a vicinity. A much-sought ratio of "leakage", the amount of store sales in area compared to the amount of consumer purchases, is difficult to obtain, and, when obtained, is not easily verified unless YOU are the store selling both locally and remotely, and can compare the same-items-sold.

Survey data from a large panel — 64,000 in the case of Simmons uses for Simmons Profiles, and around 100,000 in the case of the BLS diary survey that Scan/US uses for its Scan/US Consumer Spending Potential — form the two most-widely used sets of consumer spending demographic data items. The Simmons data, at $200 per variable, is more expensive because it is more product-specific, and because the survey is conducted by a private company rather than a government agency.

Either way, it can be useful to know what people say they have typically spent in the past, on particular items or categories of items. A full range of data items is available in the Scan/US Consumer Spending Potential database.

In this database, there are two data items for each merchandise line: one covers the per-household expenditure, per year, for the data item. The other data item is the aggregate expenditure of all the households in the area, for that data item.

Shown above – 2010 ZIP codes superimposed over Scan/US 2010 MicroGrids

 

"Universe" Data items

Most demographic items can be expressed as a percentage of a larger number, for example, at the US level, rented housing units are about 28.97 percent of all housing units. For convenient reference – and calculation – these fundamental 'universe variables' are carried in most demographic databases, even though it duplicates some information. Population, household count, and sub-ranges of population by age, are "the universe" for their sub-domains.

Population

The total population is broken down by age, by sex, and by race, and whether in households or in group quarters

Households

The 115 million households in the US are are either family households ( 76 1/2 million) or nonfamily households (38.78 million).

The characteristics of each type differ as to size, and other characteristics.

Housing units

Housings units are vacant (12.05 percent), owned (58.98 percent) or rented 28.97 (percent)

Pop over 15

The population 16 and over is the universe of the labor force status: whether in the Armed Forces, civilian employed, civilian unemployed, or not in the labor force.

Pop over 24

The population 25 and over is the universe variable for the level of education reached by the population.

Terms used in Census Demographics

Inevitably, questions may arise about the exact meaning of terms such as 'income,' 'race', 'linguistic isolation,' or even 'household.' Here is a dictionary guide to demographic terms, as used in Census demographics databases.

 

Guide to array variables

Age

The age array has counts of both men and women, every five years up to age 25, and every ten years thereafter. There are several age arrays. In the Demographic Update, there are 12 cuts of age, with several other useful arrays pre-collapsed, such as over 55 or over 65, in "other age ranges".

RaceWhite
Black
American Indian/Alaskan Native
Asian
Hawaiian/Pacific Islander
"Other" or "multiple" races.

The Census Bureau's extensive categorization of multiple types is simplified to White, Black, American Indian/Alaskan Native, Asian, Hawaiian/Pacific Islander, and "other" or "multiple" races. Hispanic is carried as a separate category, since you can be Hispanic and any of the above.

The Detailed demographic update has a 12-age-range array showing percent Hispanic population. The Detailed Update database shows 18 age ranges for the population, males, and females, AND a 21-"range" array for the 1st 21 years.

Income

Income arrays are the number of households falling into each income range.

The Detailed Demographic Update carries 16- and 26-income range arrays for household income, disposable income, family income, and nonfamily income, while the Demographic Update carries only the 16-range arrays

Male/Female

In addition to Population by Age(12), both male and female pop are divided into age ranges with 12 ranges (demographic update) and 18 ranges (detailed demographic update)

Housing

Housing units by tenure (owned or rented)

Vehicles

The Detailed Update shows both owner and renter households with 1,2,3,4,5+ vehicles available, as well as none, while the Demographic Update carries four ranges of vehicles per household: none, 1, 2, and 3+.

Education

Level of education is shown for the population of 25 years and older.

The Demographic Update database has an array of 5 levels, while the Detailed Demographic Update has two arrays, one showing 5 levels, and one showing 7, with the 7-range array also showing counts for the population with less than a ninth-grade education, and those with the Associate degree.

Labor Force Status

In the Demographic Updates, employed are shown where they live. Labor force status is shown for the population of 16 years and older, with categories of civilian employed, civilian unemployed, in the Armed Forces, or not in the labor force at all.

In the business databases, employees are shown where they work, by business type, by occupation, and by whether site-based or field-based.

Other useful arrays

Other useful arrays are: Household size (4 or 7 ranges), families by type(6) and nonfamilies by type(6).