Technology has taken a giant leap forward the last few years by expanding the traditional tool of demographic research into an analysis of lifestyles and consumer spending behavior. The old school strategy was to look at population count and income and age to determine a good location for a business, but new school tools such as Leakage Factor, Retail Gap Analysis and Tapestry Lifestyle Analysis take decision making to a higher level and reduce the risk of failure.
This report examines how these new technologies help to make better real estate decisions. Recently, I was asked to market 10 acres of land in New Orleans which was zoned RM-4, the highest density available for multi-family use, but feedback from neighborhood associations and the city council representative showed opposition to new apartment development so I utilized the technology of the Site To Do Business Database on the CCIM.com website to generate sophisticated information on the best use of this 10 acre tract. I was able to examine the lifestyle of the residents in the area and how they spent their money to determine what businesses are needed.
When we analyze the target area population, we look at demographics within a radius: usually 3 miles, 5 miles and 10 miles; however, a better approach is to examine drive times. Drive time analysis provides more useful information when there are natural boundaries to an area; for example, north of New Orleans is Lake Ponchartrain and east of New Orleans is a wetlands area and Wildlife Preserve. The map below is an example of 5 minute (blue), 10 minute (brown) and 15 minute (green) drive times from the target 10 acre site, located in the eastern part of New Orleans.
Within these drive times, we can examine the population density, per capita and household income, home ownership and age brackets. This helps us determine if higher end businesses such as Brooks Brothers might thrive from a higher income population or if Dollar Generals are needed to serve a lower income population. For multi-family, we can examine how many people rent and are in their 20’s, the prime apartment renting age. For example, in the 5 minute drive time from the target 10 acre site, population from 2000 to 2009 declined from 67,717 to 32,391 but is expected to grow to 45,693 by 2014, with renter housing growing from 22% to 32%.
We can further break down the population into income brackets, since a high weighting in one bracket might skew the average annual household income of $40,743. The household growth rate from 2009 to 2014 is among the highest in the U.S. at 7.28%.
The forecasted annual population growth rate from 2009 to 2014 within a 5 minute drive time is 7 times the state and national average (see chart below, Trends 2009-2014).
The 2009 Household Income Pie Chart shows the percent of the population according to income brackets, and The 2009 Population By Race Shows five race categories as well as multiple categories.
We can compare the percent of population by age to the national average. In the target area, we have a lower than average percent of 35-54 year olds but a higher than average percent of under 24 year olds.
Drive times provide a snapshot but we also need to examine future growth of population and income. Within the 5 minute drive time, the population is estimated to grow from 35,217 in 2010 to 45,824 by 2015, and the median household income in 2010 was $43,486. Within a 10 minute drive time, the population is estimated to grow from 114,408 in 2010 to 146,207 by 2015.
The 2008 traffic study by the Louisiana Department of Transportation (www.dotd.la.gov) showed Interstate 10 traffic in New Orleans East at 34,000 cars per day, and 2010 estimate from Datametrix (www.CCIM.com) is 30,000 cars per day.
The Market Potential Index (MPI) is a new tool that measures the relative likelihood of the adults in households in the specified trade area to exhibit certain consumer behavior or purchasing patterns compared to the United States as a whole. An MPI of 100 represents the U.S. average, and a number higher than this means a higher propensity to spend in that category, compared to the national average.
Two conclusions can be drawn from consumer spending data. First, the MPI exceeds 100 on seafood, chicken or turkey in both the 5 and 10 minute drive time, meaning a higher than average propensity to spend on these items. Second, the population is high enough to support at least four supermarkets, using the assumption that a 50,000 square foot supermarket needs a population of approximately 8,000 residents.
We can zero in on how much money residents spend annually in specific categories and a future grocery store needs to know how much money is spent in the Food at Home category. Within a 5 minute drive time, total amount of money spent on food at home exceeds $39,000,000, and within a 10 minute drive time exceeds $111,000,000, but we also drill down in the data to determine what types of items a supermarket could sell to have a competitive advantage. For example, within a 10 minute drive time, there is $38,000,000 spent on snacks for food at home.
Using industries categorized by NAICS code, we can examine where demand exceeds supply which shows a need for a business to fill a void. We can determine supply by estimating sales to consumers by establishments, while excluding sales to businesses. We forecast demand, or retail potential, by estimating the expected amount spent by consumers at retail establishments. Supply and demand estimates are in current dollars. The gap between demand and supply is called the Leakage Factor, which presents a snapshot of retail opportunity. This is a measure of the relationship between supply and demand that ranges from +100 (total leakage) to -100 (total surplus). A positive value represents ‘leakage’ of retail opportunity outside the trade area. A negative value represents a surplus of retail sales, a market where customers are drawn in from outside the trade area.
Developed in cooperation with Canada and Mexico, NAICS represents one of the most profound changes for statistical programs focusing on emerging economic activities. The system was developed using a production-oriented conceptual framework, grouping establishments into industries based on the activity in which they are primarily engaged. NAICS moves down in detail from Sector to Subsector to Group then to Industry. This is an improvement over the previous method, the 1987 Standard Industrial Classification (SIC) system.
The chart below shows the Leakage Factor by NAICS Subsector for the target area. The highest Leakage Factor shows new businesses needed are:
The Leakage Factor shows what businesses are needed by the percent that demand exceeds supply, but also shows the dollar amount of the unfulfilled demand. This can be used to forecast sales for a business coming into the area. The Retail Gap represents the difference between Retail Potential and Retail Sales. Retail establishments are classified into 27 industry groups in the Retail Trade sector, as well as four industry groups within the Food Services & Drinking Establishments subsector. These data are based upon national propensities to use various products and services, applied to local demographic composition. Usage data were collected in a nationally representative survey of U.S. households, and forecasts for 2010 and 2015 are prepared by ESRI. Table Six shows industry groups with the highest sales (Retail Gap) in the target area are:
Retail Marketplace Reports are available by theme, such as grocery store sales, and we can drill down to county, city, zip, census tract and block group (the smallest unit of measurement of census data). Themes can get very specific, even down to a map of the population that used aluminum foil the last six months. The map below shows grocery store sales by zip codes south and west of the target area are above $28 million and since there is only one Winn Dixie store in that area, we know the market will bear additional stores. We can use information on expected sales to right-size building square footage and land area.
Tapestry identifies neighborhood segments and describes the socioeconomic quality of the immediate neighborhood. The Index is a comparison of the percent of households or population in the area, by Tapestry segment, to the percent of households or population in the United States, by segment. An index of 100 is the U.S. average. The top two Tapestry Segments are:
Family is the cornerstone of life in Family Foundations communities. A family mix of married couples, single parents, grandparents, and young and adult children populate these small, urban neighborhoods located in large metropolitan areas, primarily in the South and Midwest. This market represents stability. Hardly any household growth has occurred since 2000; these neighborhoods experience little turnover. The median age is 39.0 years; the median household income is $46,308. Most households are single-family structures built before 1970, occupied by owners. Many residents are members of church boards or religious clubs and participate in fund-raising. Basketball is a favorite sport; residents play it, attend professional games, watch games on TV and listen to games on the radio. They watch courtroom TV shows, sports, and news programs on TV and listen to gospel, urban, and jazz radio formats.
Metro City Edge
Metro City Edge residents live in older, suburban neighborhoods of large, metropolitan cities, primarily in the Midwest and South. This market is home to married-couple, single-parent, and multigenerational families. The median age is 29.4 years, and the median household income is $32,291. Nearly half of employed residents work in the service industry. Most households live in single-family dwellings; 14 percent live in buildings with two to four units, many of them duplexes. Homeownership is at 54 percent, and the median home value is $78,213. Prudent shoppers, residents buy household and children's items at superstores and wholesalers. They enjoy watching TV (especially sitcoms and courtroom TV shows), going to the movies, visiting theme parks, roller skating, and playing basketball. They read music, gardening, and baby magazines and listen to urban and gospel radio.
The Top Tapestry Segments Pie Chart shows that the Family Foundations segment is the highest rank in the target area at 21.80% of the population, and we can compare that to the national average at .80% in the table and chart below. The top two segments include lifestyle traits such as playing basketball and watching courtroom TV, so we can tailor our advertising around that media rather than newsprint.
Our use of technology has delivered important information that will assist us in determining the best businesses for the target 10 acre site while reducing risk of business failure. We have progressed from simply knowing the population count, age and income to knowing detailed information about who lives in the target area, how they spend their money and what businesses are missing that could satisfy that demand. We have been able to conclude the target area has the highest unfulfilled demand for furniture, sporting goods, clothing and food stores, and we have been able to forecast the total sales of a future grocery store and can plan our capital expenses such as store size accordingly. We know what makes the nearby residents unique and where they spend more of their money compared to the average consumer, so we can also lower our inventory costs by stocking the goods with the highest demand. We can also reduce our advertising costs and reduce waste by targeting the media that our customers will use. These new school tools are available to anyone facing a real estate decision, not just the Walmarts of the world, and all you have to do is simply collect the data from a reliable online source and put some thought into the needs of the customers you will serve.
