A Market Potential GIS Case Study - Market Potential Analysis for Check Cashing and Pawn Brokers

Spatial Insights undertook a market potential analysis of check cashing and pawn shop expansion potential in the Houston, TX metropolitan area. Using precision geocoded business locations from CAP Locations ReCAP Retail database, coupled with current year demographic estimates sourced from AGS, we employed a suite of GIS tools to analyze and map the geographic distribution of demographic demand and market potential.

Location of Check Cashing and Pawn Shops, Houston, TX. (Click for larger image)

The demographic analysis was performed using block group level demographics. Block groups are neighborhood-sized areas with similar demographic composition. They are the smallest units of geography for which most demographic data estimates are available.

In order to assess the potential demographic demand, we evaluated the current year (2008) demographic data by block group, as follows:

Total population
Median household income
Percentage of renter occupied dwelling units
Average household size
Population density

These variables are known to be strong indicators of demand for check cashing and pawn brokerage services. While examination of each of the demographic criteria alone is useful, it is the spatial concurrence of the data that is most indicative of demand. We calculated an index score that mathematically combines these five variables using a data indexing scheme.

Index Mathematics
In this example, each variable was equally weighted and classified into five ranges, each containing 20% of the data. A weight was assigned to each range of data, according to its relative importance. In the above schema, the best possible demand score is 25, the worst possible demand score is 5, and a score of 25 represents areas that have:

Population > 2,494
Income < $32,767
Over 303 renter occupied dwelling units
Average household size > 3.36
Population density > 6,333

Lower scores represent areas that have a lesser contribution from one or more of the five components. Scores over 18 are generally considered good for this analysis.

Demand Index Score Results
TrendMap, a trend surface mapping tool developed by Spatial Insights, was used to generate a "hotspot" map of demand, based on the calculated demand index scores. The maps depict areas that have the highest demand index scores as magenta, with decreasing scores in shades of red, orange, yellow and blue.

Demographic Demand Index Results, Houston, TX. (Click for larger image)

Close-Up: Demographic Demand Index Results, Downtown Houston, TX. (Click for larger image)

Supply Side Analysis
CAP Locations ReCAP Retail database of existing check cashing and pawn shops were analyzed using TrendMap. The resulting map shows the concentration of competitors based on floor space (gross leasable area, or GLA) of the stores within a 2.0 mile radius. The map depicts areas that have the highest concentrations of square footage (GLA) as magenta, with decreasing competitor density in successively "cooler" shades of red, yellow, green and blue.

Access to Check Cashing and Pawn Shop Retail Space, Houston, TX. (Click for larger image)

Close-Up: Access to Check Cashing and Pawn Shop Retail Space, Downtown Houston, TX. (Click for larger image)

Supply/Demand Model
In order to identify areas of strong market potential, a supply/demand model was developed that delineates areas based on the level of modeled demographic demand, relative to the existing "supply" of retail space. A simple bivariate indexing scheme was employed that compares the index scores from the demographic demand model with the supply-side hot-spot map.

The mathematics of the schema used are as follows:

A score of 10 (best case scenario) represents areas that have the strongest demographic demand, and the lowest existing retail space (GLA)
Lower scores represent areas that have either less demand or more existing retail space

Supply/Demand Index Results, Houston, TX. (Click for larger image)

Close-Up: Supply/Demand Index Results, Downtown Houston, TX. (Click for larger image)

Conclusions
Understanding the geographic correspondence between areas of strong demographic demand and low concentrations of competitive retail space provides a basis for identifying potential expansion opportunities. More detailed study of specific areas is warranted for those areas that exhibit strong combinations of demographic demand and weak competitive factors.