Market Cannibalization and Demographics

This analysis was created for a retailer in the Columbia, MD market that was considering expanding into the Towson, MD market. To understand the feasibility of a new store, drive times and demographics were combined to understand whether the two markets were complementary or competing. In this case, it was determined that there was minimal cannibalization (overlap shown in green) of the two markets and the primary market area (red and yellow) was well suited to support another site.

Current and Future Residential Population

Many retailers need to know not only the current population (shown in purple) for a new market, but also what the future population will be. In this example, a national retailer was considering a new site in the Owings Mills area, and wanted to understand where active development activity was occurring. New development, shown in green, is described in the table by how many lots are planned and now many are actually being developed.

Psychographic data can be used to better characterize a retailer's current and potential customer base. Much more than simply age, gender, race, and income, this data incorporates expenditure data and consumer habits to better understand the lifestyle of consumers. On this map, the colors represent the dominant LifeMode for each neighborhood, and the numeric labels represent one of 65 unique categories describing specific lifestyle characteristics of that neighborhood. This information can then be summarized into reports that quantify the population according to each lifestyle category.

Consumer Expenditures on Retail Goods

Portraying consumer expenditure data on a map reveals patterns that help retailers understand their market. This map was created to understand the retail habits of the population in Carroll County, MD and shows higher per-household expenditures in darker shades of purple. Total consumer expenditures were also calculated for the entire 15 minute drive time trade area.

Consumer Expenditures on Gasoline

MacKenzie GIS maintains hundreds of types of consumer expenditure data which can be portrayed on a map to understand the retail landscape. This example highlights patterns in spending on gasoline and was used to help identify areas of greatest potential.

Median Household Income

This map illustrates median household income in order to better understand the retail market in the Upper Marlboro area. MacKenzie's GeoDatabase contains hundreds of demographic variables that can be mapped in this same way, and includes both current and five-year projections.

Market Demand for Sporting Goods

This map was part of an analysis to determine the viability of a large sporting goods store at a new site in Perryville, MD. For this project, market areas (20, 40, and 60 minute drive times) were overlaid with consumer expenditure data to understand the market demand for sporting goods and related products. In addition to seeing the pockets of higher per-household expenditures, the data was summarized into a table that showed the total expenditures for each trade area. It was then evaluated vis-à-vis market supply data to understand overall potential for the new site.

Retail Market Potential Based on Lifestyle

This analysis was created for a company that wished to expand services beyond its existing 7 sites (depicted as colored squares). To help understand where there was greatest market potential, each location was assigned a dominant lifestyle characteristic which described the types of consumers in that area. Using the results of this overlay, new areas with similar lifestyles were mapped to show moderate and high potential for services.

Market Supply for Sporting Goods

This map was part of an analysis to determine the viability of a large sporting goods store at a new site in Perryville, MD. For this project, market areas (20, 40, and 60 minute drive times) were overlaid with business volume data to understand existing market supply for sporting goods and related products. In addition to seeing the location and sales volume of competing businesses, the data was summarized into a table that showed the total existing revenue for each trade area. It was then evaluated vis-à-vis market demand data to understand overall potential for the new site.

Retail Marketplace Map

When evaluating the suitability of a new site, retailers consider many factors including traffic volume, co-tenancy, and nearby retailers. This map, which was created to highlight a shopping center in Baltimore, MD, combines this information into a map that characterizes the local retail marketplace.

New Market Potential

This map illustrates the way in which demographic data can be analyzed to understand the viability of a new store. In this example, the business already had stores in Perry Hall and Dundalk, and wanted to know if there was enough population in between to support a new location in Rosedale. By overlaying 4-mile rings and summarizing the demographic data, it was determined that there was adequate population to support the new site, without cannibalizing customers for the other two.

Pin Mapping Customers and Employees

This map provides a powerful example of using GIS as a new lens to view your business. Customer lists and employee rosters where converted from simple lists into a map, revealing patterns in the data. This business, which already had an existing store in Perry Hall, was able to understand where its current customers and employees come from, and better evaluate where to expand its services.

Targeting New Areas for Expansion

Businesses that understand their current customer base can leverage GIS to understand where to find new customers. In this example, an upscale retailer was seeking new locations that would reach the same type of customers which made its current site successful. The map identifies high potential areas and characterizes the dominant lifestyle of potential customers in each target area.

Threshold Trade Area Analysis

Unlike traditional fixed-distance ring and drive-time demographic reporting, threshold trade area analysis allows businesses to understand how large their trade area must be to be successful. In this example, a restaurant knew that 100,000 people was the minimum threshold for a successful site. For this location, that meant a 17.8 minute drive time (depicted in gold). This trade area is depicted on the map alongside the simpler ring (black) and drive-time (green) trade areas.

TradeWeb Analysis

One of the easiest ways to define a trade area is to understand where the "nearest" store is located for each potential customer. This is accomplished by creating boundary lines that are equidistant from each store. The resulting TradeWeb can then be overlaid with information such as retail expenditures to summarize and compare each trade area and evaluate the viability of new sites. In this example, the data suggests that there is adequate demand for retail goods for the new shopping center.