6. Analyzing Customer Demographics and Lifestyles

To analyze market opportunities for your downtown, data about residents of your trade area(s) need to be examined. This data must include the absolute number of residents as well as their household characteristics. Demographics and lifestyle data from secondary sources can provide this information.

Does your trade area population consist more of homeowners or renters? Baby Boomers, or Gen-Xers? Which ethnic groups are represented in the population? If they are home owners, how likely are they to purchase home furnishings, renovate their homes, or spend leisure-time landscaping their yard? Current and projected demographic and lifestyle data about your trade area can provide you with a starting point for the in-depth analysis of specific business and real estate development opportunities.

The U.S. Census Bureau and private demographic firms can provide data to help existing businesses assess how well their product mix and location fit their target market. The data can also be used in business recruitment to demonstrate why a given business could succeed in your downtown.

While demographic and lifestyle data will be used in completing the remaining portions of your market analysis, it can also help the broader community understand how it is changing. Accordingly, the types of data described in this section can be shared with the public through community discussions and press releases (see Appendix A).

Demographic Data

Demographic data is almost always included in a market analysis. Unfortunately, far too much information often is included in these studies. An enormous amount of data is readily available from a variety of private and public sources leaving the reader with tables and tables of demographic information overload.

Interpretation of demographic data is often missing in market analysis. What does the data say about how the market is changing and how the consumers spend their time and money? Specifically, what does the data suggest about new business or real estate opportunities downtown? The following provides a starting point in your understanding and interpretation of demographic data in relation to retail spending.*

Population and Households - Population and household data allow you to quantify the current market size and examine future growth. Population is defined as all persons living in a geographic area. Households consist of one or more persons who live together in the same housing unit, regardless of their relationship to each other (includes all occupied housing units). Typically, demand is generated by individual or household purchases. Households can be categorized by size, composition, or their stage in the family life cycle. Members of the family influence a household purchase, such as a new computer. Individual purchases are personal to the consumer. Anticipated household or population growth may indicate future opportunities for a retailer.

Income - Household income is a good indicator of spending power of residents. Household income positively correlates with retail expenditures in many product categories. Retailers may consider the median or average household income in a trade area or seek a minimum number of households within a certain income range. Another common practice is to analyze the distribution of household incomes. Discount stores may avoid extremely high or low-income areas. Traditional department stores focus on markets with incomes over $35,000, while some specialty fashion stores target incomes above $75,000. A few store categories including auto parts are more commonly found in areas with lower household incomes. Using income as the sole measure of a market's taste preference, however, can be deceptive.

Age - Age is an important factor to consider because personal expenditures change as an individual ages. Drug stores and assisted care services flourish in areas with a large elderly population. Accordingly, drug stores often do well in communities with a larger number of people over the age of 65. Additionally, realizing and catering to the needs of an aging population can be beneficial to any retailer. Toy stores, day care centers, and stores with baby care items are successful in areas with many children and infants. Clothing stores and fast food establishments thrive in retail areas that contain a large concentration of adolescents. Theatres serve a broad section of the population; however, specialized entertainment and recreation options can target certain age segments.

Education - Education is another way to determine the socio-economic status of an area. Because income increases with advancing educational attainment, many retailers focus on income level rather than education. One exception is bookstores which are often sited by developers based on the number of college educated individuals in the trade area. Similarly, computer and software stores are often located in areas with high levels of education.

Occupation - Many retailers use the concentration of white or blue-collar workers as another gauge of a market's taste preferences. Specialty apparel stores thrive on middle to upper income areas and above average white-collar employment. Second hand clothing stores and used car dealerships are successful in areas with a higher concentration of blue-collar workers. Office supply stores and large music and video stores are especially sensitive to the occupational profile. These retailers target growth areas with a majority of white-collar workers.

Ethnicity - Recognizing the ethnicity of an area is important when choosing the merchandise to be carried. Retailers that use segmentation based on race and ethnic groups must make sure their efforts are authentic as well as accurate. Correct assortments, fashion orientation, advertising media, and product selection are all influenced by ethnicity.

Housing - The number of homeowners and the rate of housing turnover is an important factor for numerous retailers. Home ownership directly correlates with expenditures for home furnishings and home equipment. Home improvement, furniture, appliances, hardware, paint/wallpaper, floor covering, garden centers and other home products all prosper in active housing markets.

*Drawn in part from: Shopping Centers and Other Retail Properties: Investment, Development, Financing and Management by John R. White and Kevin D. Gray (eds)

Comparing the Primary Trade Area with Other Areas

Demographic statistics are especially useful if they are presented in comparison with other places. To see how your trade area differs from other places, it is useful to provide two comparison sets of data: comparable communities and the state as a whole.

Comparing your trade area with other communities and the state allow demographic baselines to be established. These baselines will help determine whether your trade area has low, median, or high values in each demographic category. For instance, after examining demographics for your trade area, it may appear that there is a high proportion of white-collar workers. However, this observation cannot be verified until you know what constitutes an average number of white-collar workers. Comparing your demographics to those of other areas will allow you to make these statements.

Comparable communities can include five or six cities of similar size in the same region or state. The cities chosen should reflect similar distances from metropolitan statistical areas (MSA) of the region. Depending on the geographic size of your primary trade area, you will need to select similar sized trade areas. These trade areas can be estimated based on the zip codes (or combination of zip codes) surrounding each community. Appendix B provides a listing of Wisconsin cities, their municipal populations (even though they are different than trade area populations) and distance from the nearest MSA. This table can be used to select comparable communities in Wisconsin. Similar tables can be constructed for other states.

In addition to comparable communities, adding state statistics will provide a broader benchmark for comparing your community. State data will include a blend of urban and rural areas. Accordingly, it will not be limited to "similar places." However, differences between the trade area and the state (such as per capita income) will be used later in your analysis of business opportunities.

Demographic Data Sources

Detailed local census data is readily available free via the Internet through the U.S. Bureau of Census. Census data can be retrieved at several geographic levels (county, city/village, town, census tract, zip code, etc.).

The U.S Census web site has a link to their new, user-friendly data site called American FactFinder. Use American FactFinder to view, print, and download statistics about population, housing, industry, and business. Using FactFinder, you can also find U.S. Census Bureau products; create reference and thematic maps; and search for specific data. "Basic facts" provides fast answers to the most common questions. Using this feature, you can find statistical information for many geographic areas, and display the data in a table or on a map.

In addition to the Census Bureau, there are numerous, nationally recognized data firms that can provide demographic estimates for a particular trade area. While much of their data is based on the U.S. Census and other public sources, these companies add value by providing annual updates. They also package the data in easy to use comparative formats that makes it easy to compare one geographic area with another. Furthermore, you are able to tap into the knowledge of skilled demographers that have designed data products around particular industry needs. These firms provide a way to order reports by simply calling a toll free number or downloading the data directly using their software. Prices charged by these firms have become more and more affordable as competition has increased.

Exhibit 7.1 proves an example of a demographic comparison report assembled for a sample community from public and private data sources. The "subject trade area" column reflects demographics data on the trade area as defined earlier in the market analysis. The "Comparable communities" column reflects the demographic averages of five or six other communities. While a complete trade area analysis is not possible for each of these communities, each of the includes one or more zip code areas. The "State" column provides a third level of comparison.

Lifestyle Data

Adding consumer lifestyle takes the market analysis a step further. It recognizes that the way people live (lifestyle) influences what they purchase as much as where they live (geography) or their age, income, or occupation (demography). Lifestyle data enables us to include people's interests, opinions, and activities and the effect these have on buying behavior in our analysis.

In the 1995 American Demographics article "Birds of a Feather", Susan Mitchell explains how marketing professionals are using lifestyle or "geo-demographic cluster systems" to learn more about their current customers, identify new potential customers, and make better marketing decisions. She relates how marketing data firms can provide detailed customer profiles that can help you better focus your product mix, the services you offer, and your marketing efforts to target specific high potential customer segments.

Cluster systems are based on the premise that "birds of a feather tend to flock together." Did you ever notice that the homes and cars in any particular neighborhood are usually similar in size and value? If you could look inside the homes, you'd find many of the same products. Neighbors also tend to participate in similar leisure, social, and cultural activities.

Cluster systems use these tendencies to redefine neighborhoods into smaller similar groups. The clusters are based on demographic similarities (income, education, and household type) and the groups' common lifestyle preferences and expenditure patterns (attitudes, product preferences, and buying behaviors).

The quality of a segmentation system is directly related to the data that goes into them. High quality and useful systems allow you to predict consumer behavior. In a retail business targeting tourists, for example, it should allow you to identify products and services that might appeal to this market segment. This usefulness depends on how well the data incorporates lifestyle choices, media use, and purchase behavior into the basic demographic mix. This supplemental data comes from various sources such as automobile registrations, magazine subscription lists, and consumer product-usage surveys.

Lifestyle Data Sources

Several private data firms offer cluster systems. The firms use data from the U.S. Census and other sources to separate neighborhoods throughout the U.S. into distinct clusters. They utilize state-of-the-art statistical models to combine several primary and secondary data sources to create their own unique cluster profiles. Most systems begin with data from U.S. Census block groups that contain 300-600 households. In more rural areas, the data is more typically clustered by zip code.

One particular cluster system, CACI's ACORN, includes a purchase potential index that measures potential demand for specific products or services. It compares the demand for each market segment with demand for all U.S. consumers. The index is tabulated to represent a value of 100 as the average demand. Values above 100 are more likely to purchase those products or participate in the respective activity. Conversely, values below 100 are less likely to purchase the given product. As an example, sample data for the "Small Town Working Families" sector is as follows:

Private marketing data firms that offer lifestyle segmentation systems can be found through the 'supplier listing sourcebook" available through the American Demographics web site.

GIS and Demographic/Lifestyle Analysis

As previously mentioned, demographic analysis is useful in understanding purchasing characteristics for different market segments. While demographics can be collected and analyzed without the use of geographic information systems, there are many instances where GIS can aid and even enhance the analysis. While most downtown professionals may not be experts in GIS, some consultants, planners and marketing data providers can offer technical mapping assistance. The following discussion describes two examples of using GIS to assist in demographic analysis.

Using GIS to Visualize Trade Area Demographics

When demographics are obtained for a trade area, they are often reported as single values for each demographic category. In other words, the trade area income is reported as one value, the trade area population is presented as a single number, and so on. However, demographic values can vary over the trade area. Each geographic unit used in defining the trade area (zip code, census block group, etc.) has its own associated demographic values. When these individual values are combined into a single trade area value, some of their usefulness is masked. In uncovering additional insight contained in trade area demographics, GIS can be used to map different demographic categories. Mapping these variations may reveal valuable, visual information that can be used to show the attractiveness of a downtown location and aid in business recruitment and expansion.

Effective demographic mapping requires an understanding of some basic cartographic concepts. Perhaps the most important concept is an understanding of the problems associated with demographic densities. By its nature, downtown is developed at a much higher density than the surrounding city. Accordingly, there is often a higher population in a small area than a similar-sized area on a community's fringe. Moreover, many business owners would view the large concentration of customers as a competitive advantage over a non-downtown location. However, a map showing the number of people in each geographic unit (e.g. census block group) does not always show this relationship.

As a real world example of this problem, consider the map in Exhibit 7.2. The map of the La Crosse, Wisconsin area depicts the population in each census block group. Why does this type of map fail to accurately represent the number of customers in downtown? The problem is due to the nature of census block groups. More specifically, census block groups have different sizes. While the U.S. Census Bureau tries to control the number of households in each block group, it is not always possible to make the units the same size. Problems associated with geographical barriers (rivers, mountains, etc.), the nature of the population distribution (sparse or concentrated), and the sizes of households can cause wide variation in population numbers. In accounting for these problems, the U.S. Census Bureau resorts to drawing census block groups with different sizes.

As a result, census block groups with a large area often will have a larger population than those with a smaller area. These larger areas with greater populations tend to dominate the viewer's eye on a map. When these large census block groups are located away from downtown, it appears that downtown has a small population compared to the outlying urban areas. Additionally, there may be many more block groups with smaller populations located in a smaller area. However, their small size and small population values can become obscured on a map. Consequently, the larger number and grouping of these smaller block groups needs to be addressed. GIS can tackle this problem by transforming the map into population density.

Exhibit 7.2 - Map of Block Group Populations for La Crosse, Wisconsin

Exhibit 7.3 shows a map of the same La Crosse, Wisconsin area with an equivalent color scheme. However, this new map has undergone a transformation and now depicts the population density in the area. The new density map shows the exact opposite of the previous map. Here, the viewer sees that there is a large population clustered around the downtown and a relatively small population toward the urban fringes. The story told by the population density map would not be seen in a single population value representing the entire trade area. As a result, the new map aids in showing the potential of downtown as a business location and can be used as a valuable business recruitment tool.

Exhibit 7.3 - Population Density Map for La Crosse, Wisconsin

Using GIS to Analyze Visitor Demographics

The previous section discussed how GIS could create a useful visual representation of demographics. However, GIS is not limited to producing maps and graphics. GIS can also be used as an analytical tool in demographic analysis. As an example, consider the problematic nature of assembling demographics for non-local visitors. Profiling visitors is essential in the study of tourists, commuters and other market segments. While collecting demographics for the surrounding resident market is a straightforward process, visitors can come from a wide area. Obtaining and analyzing demographics for every area that produced a visitor is unrealistic using traditional methods. In these instances, GIS can be used to profile demographics of the non-local market.

Many businesses dependent on visitors maintain customer address lists (such as hotels). These addresses become useful, as knowing where visitors live means knowing something about the demographics in their neighborhood. More specifically, by knowing a visitor's address, GIS can be used to quickly identify the census block group, or neighborhood, where a customer lives. With each census block group comes rich demographic information available through the U.S. Census Bureau or private data providers. Namely, each census block group or neighborhood has associated income, population, occupation, education, age and housing information. The demographics associated with these neighborhoods can be entered into a GIS and used as a surrogate for demographic information on each individual visitor.

Using this neighborhood demographic information as a surrogate is based on the premise that "birds of a feather flock together." As discussed in the section on lifestyle segmentation systems, people of similar demographics tend to live near one another. Therefore, the neighborhood demographics are likely to be similar to those of the individual visitor. Using addresses, GIS can determine every neighborhood that produced a visitor and extract the demographics of these neighborhoods. The demographics extracted from each visitor neighborhood can be combined to produce a useful demographic profile of the visitor market.

The demographic profile is even more useful when it is given some perspective. Similar to the comparable communities analysis discussed earlier in this section, the visitor demographic profile can be used to determine what makes visitors demographically different from the general population. Instead of comparing local community demographics to those of other communities, the visitor demographics can be compared to the demographics of a larger region. For instance, if visitors primarily originate from a three-state area, the visitor demographic profile can be compared to the demographics for the entire population of those three states. These demographic profiles of the community visitors and the larger region can be compared on a category by category basis.

The following example explains the steps used in the GIS analysis of visitor demographics.

Step 1. GIS is used to map the locations of visitor addresses. As an example, Exhibit 7.4 shows a map of visitor origins for a sample community.

Exhibit 7.4 - Sample map showing how GIS can be used to determine visitor origins

Step 2. Once the visitor origins have been mapped, GIS is used to determine the neighborhoods containing each visitor and extract the associated neighborhood demographics. These neighborhood demographics are used as a surrogate for the demographics of the individual visitor. Exhibit 7.5 shows an example of one sample neighborhood containing visitors as well as some of the demographics associated with the neighborhood.

Exhibit 7.5 - Map of a sample visitor neighborhood showing representative demographics

Step 3. GIS is used to combine all of the demographics extracted from every visitor neighborhood. Combining the neighborhoods creates a demographic profile of the visitors. To aid in the analysis, GIS also creates a demographic profile of the larger region. The regional demographic profile includes every neighborhood instead of just those neighborhoods that produced visitors. These two profiles are then used to examine differences in visitor demographics. For instance, the table shown in Exhibit 7.6 compares several demographic categories. The first column contains the demographic category, the second column shows the visitor demographic profile and the third column depicts the profile created for the larger region.

In this example, GIS was able to demonstrate that visitors originated in neighborhoods that had higher incomes, a greater proportion of college educated residents, more executive and professional employees, a higher rate of home ownership, and more vehicles per household than the overall three state area.

In summary, GIS provides a powerful tool for examining your market in ways tables and narratives cannot. Your analysis of demographics and lifestyles can be enhanced by the proper use of this technology.

Appendix A - Sample Press Release

For Immediate Release
(Enter Date)

Contact: (Enter name and phone number of primary contact)
(Enter name and phone number of secondary contact)

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DEMOGRAPHIC DATA REVEALS CHANGES IN DOWNTOWN MARKET

(Enter city)--(Enter main street organization) has analyzed data on the demographics and lifestyles of consumers served by the (Enter City) downtown area in order to determine what types of products and services to sell downtown. In researching the needs of the community members with respect to potential downtown businesses, the (Enter main street organization) looked at several different data sources. First the team looked at characteristics of the surrounding community including; population, household types, age, education, and occupation. This data helps paint a picture of the community that is useful for businesses when deciding whether to locate here.

Data on nearby communities of similar size, and at a comparable distance from larger cities was examined.

Identifying ______,______,______,_____ and ______ as comparison communities, the study group volunteers examined data about these communities to see how they are different than (Enter City).

(Enter main street organization) used U.S. census data along with lifestyle data from (Enter Data Firm) to look more closely at the types of consumers in (Enter City's) trade area. From that data the committee was able to compile a consumer profile that included local and national information on trends in consumer spending among various age, income, and ethnic groups.

The study group concluded that the (Enter City's) trade area has grown ______. Furthermore, local households differ from the comparison communities due to ______. Based on these differences, the study team will be examining the market potential in more detail for ______ products and services that could be sold downtown.

As a result of (Enter main street organization) research efforts they feel they've gained a better understanding of which types of businesses are most likely to succeed in downtown (Enter City). This means that in the future they will be able to present a strong case to business considering locating in downtown (Enter City). Additionally, with the information they've collected on the characteristics of local consumers, they hope to encourage a mix of businesses that will be a good fit for the local community.

Interested parties may volunteer for the downtown market analysis team by calling (Enter name of committee chair) (Enter phone number). For more information on the downtown market analysis or on (Enter Main Street Organization), contact (Enter Main Street Manager Name), at (Enter phone number).

Appendix B - Wisconsin Comparison Communities

*Community is located in multiple counties