9. Evaluating Retail Opportunities

This section provides a method for quantifying market opportunities in specific retail categories. It includes techniques for estimating market demand and supply in terms of retail space. Other more qualitative and equally important market considerations are also discussed. Finally, more advanced analysis techniques using GIS are provided.

To begin the evaluation of retail opportunities, the market analysis study committee should develop a "short list" of store types deserving detailed market examination. The short list can be based on focus group and consumer and business owner survey findings, professional knowledge of members of the study committee, results of downtown visioning efforts, and preliminary conclusions drawn from local demographic and lifestyle data.

A detailed study of market demand and supply is necessary for each store category to determine market potential. Demand refers to the amount of retail space (in square feet) that could be supported by consumers residing in the trade area, based on estimates of their spending potential. Supply refers to the actual square feet of retail space, sometimes called Gross Leasable Area (GLA), that currently exists in the trade area.

A comparison of demand and supply by store type can help identify gaps (demand exceeds supply). After considering other more qualitative market factors including how and where local residents shop, conclusions can be drawn regarding potential business categories worthy of business expansion or recruitment efforts. A flowchart describing this method is presented in Exhibit 9.1.

Appendices A and B provide detailed data used in the demand calculations for each of 39 store categories. Appendix C provides a blank template that can be reproduced and used in the examination of each store category.

Exhibit 9.1 - Evaluating Retail Opporunities By Store Type

Retail Demand Analysis

Estimates of your trade area’s consumer spending potential in selected retail store categories can be calculated using the Retail Demand Calculator, a downloadable MS Excel workbook. Estimates of demand are calculated in sales dollars as well as square feet of retail space for 39 retail categories that are frequently found in downtown districts.

DOWNLOAD THE RETAIL DEMAND CALCULATOR
(Requires MS Excel)

The calculator estimates demand by type of store (instead of type of product). The calculator goes an additional step by distributing general merchandise store demand (i.e. discount stores, “supercenters,” warehouse stores) among the specific store types. For example, shoe store demand includes sales in dedicated shoe stores (NAICS 44821) as well as sales in the shoe departments of general merchandise stores (including Wal-Mart). This is done to recognize the significance of general merchandise store sales in today’s retail sector.

The steps in the calculations are based on available secondary data from the U.S. Economic Census and the Urban Land Institute (already loaded in the MS Excel Workbook). Local trade area population and per capita income are also required, and need to be entered in the “Trade Area Assumptions” worksheet of the workbook. Purchasing potential index data available from some private data firms can also be entered (as an override) in the workbook to increase the accuracy of the resulting retail demand estimates.

Once your assumptions are entered, you can click on the “Trade Area Report” worksheet to review and print your report. This report will list market demand in sales and square feet for the 39 retail categories. See Exhibit 9.2.

Exhibit 9.2 - Retail Demand Calculator – Trade Area Assumptions and Trade Area Report Worksheets

Exhibit 9.3 explains how the Retail Demand Calculator works. The calculations can also be performed manually as demonstrated in the exhibit’s example.

Retail Supply Analysis

To analyze supply, a database of existing businesses needs to be constructed for each of the store categories under investigation. The database for each store category should include all of the retail businesses within the trade area used to calculate demand. You may want to also note other major competitors outside of the trade area even though they will not be included in the demand and supply square foot comparison. In addition, applicable departments within general merchandise stores that compete for business in this store category should also be included in the database.

The database should include a list of the names and addresses of all the current retailers in the primary trade area. For downtown retailers, a complete list could be obtained from your Building and Business Inventory (see section 2). For trade area businesses that are located outside of your downtown area, a list can be generated from yellow-page listings, private data firms that sell business lists, and your own business inventory.

For each retail store, include a reasonable estimate of store size in square feet. For general merchandise stores, include the approximate number of square feet devoted to that product line. While calculations of retail space in a market area are often based on observation and rough estimates, they do provide a reasonable and important "ballpark" figure for this analysis.

Square feet of store space is often called gross leasable area (GLA). It can be estimated by actual measurement of a building's street-front width and estimate of its depth. In some communities, building square feet may be available in tax assessment records. In many cases, square feet can be estimated by simple observation and comparison with other stores. The Urban Land Institute's Dollars & Cents of Shopping Centers: 2002 provides information on store GLA statistics that can be used as a comparative benchmark. See Appendix B for selected data from this source.

Other Market Considerations

Examining quantitative aspects of demand and supply is only part of the analysis. There are also a number of qualitative considerations that require local knowledge and insight about the market.

The previously calculated differences in retail space demand and supply need to be analyzed in context of other market factors. The following provide additional considerations that add to the analysis of each category

Survey and Focus Group Findings:
What have we learned from local research about consumer behavior and perceptions of the downtown? Use findings from “Assessing Consumer Attitudes” (section 8) of the toolbox

Trade Area Demographic and Lifestyle Findings:
Does lifestyle segmentation data indicate that local residents are more likely to purchase goods within this store category? Use findings from “Analyzing Customer Demographics and Lifestyles” (section 7) of the toolbox

Analysis of Non-Local Market Segments:
Is there significant market potential from nonresident customer segments such as tourists and commuters? Use findings from “Analyzing Local Economics” (section 6) of the toolbox

Retail Mix Analysis:
How many businesses in the category are located in the downtown areas of comparison communities? Use findings from “Analyzing Business Mix” (section 4) of the toolbox.

Competitiveness of Existing Stores in Trade Area:
Are existing stores in this category providing the merchandise and service local shoppers demand? Base this on the knowledge of your market analysis study committee.

Competitiveness of Existing Stores Outside of the Trade Area:
Do surrounding communities with regional shopping centers and big box stores siphon business in this category out of the trade area? Use findings from “Analyzing Local Economics” (section 6) of the toolbox.

Consumer Behavior and Trends in Store Category:
Are purchases driven by convenience or comparison shopping? Do stores of this types locate in downtown districts anymore? Click on “Industry Links” to access trade associations for store specific research. Also, the monthly UWEX e-newsletter “Let’s Talk Business” provides articles on consumer behavior and trends related to retail development downtown.

Drawing Conclusions:

The quantitative comparison or retail space demand and supply by store type provide an initial measure of market opportunities (i.e. demand greater than supply). However, demand and supply must be analyzed in combination with many other market considerations. If there appears to be a significant amount of unmet demand, there may be opportunity for an existing business to expand or a new business to be recruited. Business development opportunities may also exist in areas where supply is greater than demand, especially in those communities that are successful in drawing customers from outside their trade area because of a special product niche they have created.

Advanced Topic:
Analyzing Retail Demand and Supply with GIS

The traditional role of GIS in retail demand and supply analysis is to find a suitable location for a new retail outlet. In other words, GIS is used to analyze market characteristics (such as competitor locations, consumer demand, demographics, traffic counts, etc.) and search for an optimal new retail location.

However, conducting downtown market analysis means the potential new business location is already known. Even so, GIS can still be used to analyze the feasibility of a downtown location in the context of the larger trade area. These types of GIS applications will contribute additional insight that may determine whether or not a retailer could be successful in a downtown location.

If you are interested in the following techniques and do not have GIS expertise, consider contacting a consultant, planner or market data provider for technical assistance.

Using GIS to Visualize Demand and Supply Distribution

Knowing the geographic distributions of retail demand and supply is vital to understanding the market. Mapping these distributions will show concentrations of high and low demand and the location of potential competition. More importantly, mapping these distributions will show the relationships between demand and supply. For instance, do areas of high demand have a large number of nearby stores or do gaps exist in the market? As GIS can overlay, or superimpose, different data sets onto one another, it is an ideal tool for exploring this relationship.

To map supply, a GIS can use business addresses and plot existing retail locations in a given NAICS or SIC retail category. Furthermore, the amount of consumer demand can be mapped using the demand calculations previously discussed in this section. Once mapped, the supply of retail locations can be shown along with the retail demand distribution. The combination of this information on the same map creates a powerful visual tool that can be used to analyze the downtown market. If the locations of retailers do not match the concentrations of consumer demand, a market gap may exist. If these gaps occur around a downtown or business district, the maps could show an opportunity for a new downtown retailer.

An example is shown in Exhibit 9.5. The GIS map shows the demand and supply conditions for hobby, toy and game stores around Franklin, Tennessee. Notice that there is a large amount of consumer demand for hobby, toy and game stores surrounding downtown Franklin. However, the map shows that the locations of existing hobby, toy and game stores are located outside of downtown and near the interstate highway to the north. These stores are located in areas of smaller demand and must depend on customers traveling to their stores. This market gap suggests that a new hobby, toy and game store located in downtown Franklin might capture the large amount of nearby consumer demand.

Exhibit 9.5- Franklin, Tennessee Hobby, Toy and Game Store Demand and supply

Using GIS to Analyze the Market Share for a New Retail Location

Mapping demand and supply is useful for examining retail conditions in a qualitative sense. The maps allow the viewer to determine how these two market conditions are related geographically. However, the viewer does not obtain any numerical market information from the map. In addressing this deficiency, GIS can be used in a more analytical role and calculate quantitative demand and supply figures.

The previous discussion in this section showed how to calculate demand and supply for retail establishments. These calculations allowed the amount of existing supply to be compared with consumer demand. If this comparison shows a market gap, it might signify a new market opportunity. However, these calculations examine conditions for the trade area without any regard to the store’s location within a trade area.

For instance, demand and supply calculations may show potential for a new store. Yet, it is still unknown whether the store will succeed in a downtown location. The distribution of demand and supply might signify that a downtown site might not be a viable location. Factors such as the proximity to competition, or an absence of nearby demand could suggest another location within the trade area might be more suitable. To explore this market uncertainty, GIS can use the distribution of retail demand and supply to quantitatively predict the market share of a new store.

For a new downtown store to succeed, it must capture a large enough market share of existing customers. The market share must come from either unmet demand, or be captured from existing stores. Knowing this market reality, how can the market share of a proposed store be determined?

Using GIS and a concept called predictive gravity modeling, a new store’s market share can be analyzed. These predictive models are commonly known as spatial interaction models (SIMs), gravity models, or consumer behavior models and are often calculated using GIS. Regardless of the specific model, these models consider the location of demand and supply and predict where consumers will likely shop. Simply stated, these consumer predictions can be used to determine if a new store will capture enough of a market share to succeed. A predictive model usually considers at least four factors in determining where consumers will shop. These factors include:

• The travel time for a customer to the new store. The models assume that a customer will more likely travel shorter distances to a store.
• The attractiveness of the new store. The attractiveness of a new store is important to consumer behavior, as customers desire more amenities. Often the attractiveness is determined by the size of the store, but can include other factors (i.e. level of service, prices, product brands, proximity to other stores, etc.).
• The travel time or distance of a customer to a competing store. Again, the models assume that a customer will travel shorter distances.
• The attractiveness of the competing stores. If a competing store is more attractive, a customer might choose the competitor or be attracted from longer distances.

Predictive models use these four factors to determine the probability, or likelihood, that a customer living in a certain neighborhood will visit a new store. By calculating the probabilities for each neighborhood in a trade area, the overall market share for the new store can be determined. To demonstrate how this can be done with GIS, consider the following step-by-step grocery store case study derived from Stevens Point, Wisconsin.

Step 1: Calculate Grocery Store Demand and Supply

The grocery store retail category was analyzed using the demand and supply analysis previously discussed in this section. The results of this analysis showed a gap of approximately 30,000 square feet of unmet grocery demand in the trade area.

Step 2: Determine the Market Share Captured from Each Neighborhood in the Trade Area

To determine whether or not a new grocery store of 30,000 sq. ft. could succeed downtown, we can use GIS, the demand and supply of grocery stores, and a simple predictive model to determine the market share derived from each neighborhood. (A common gravity model, known as the Huff model, is used in this example.) GIS is used to determine the travel distance between each store and neighborhood. Once these distances are known, the model factors in the size of each store and calculates the probability of customers originating from each neighborhood. These probabilities can be thought of as the market share captured from each neighborhood.

Exhibit 9.6- Predicted Market Share Calculations for Stevens Point Trade Area

Step 3: Calculate the Demand Capture from Each Neighborhood and the Overall Trade Area

Using the market share calculated for each neighborhood, a total market share for the trade area can be calculated. For instance, consider a neighborhood with a predicted market share of 58% (ρ = 0.58) and a population of 1,275 people. By multiplying 1,275 by 0.58, we can determine that approximately 740 people from the neighborhood are likely to shop at the new store. By repeating this calculation for each neighborhood in the trade area, we can determine the total number of customers who will likely shop at the grocery store. In doing so, the calculations show that a predicted 11,880 people will likely shop at the new store. Using per capita spending for grocery stores, this number can be converted into the market share of demand dollars (Exhibit 9.7)

Step 4: Reconcile Captured Demand with Existing Gap in Market Demand

The initial demand and supply calculations from Step 1 showed a gap of 30,000 sq ft. To compare this value with the estimated market share of the new grocery store, we can use a grocery store sales per square foot value to translate the market share into square feet (Exhibit 9.8).

As the new grocery store’s market share (61,600 S.F.) is greater than the existing and sizeable market gap (30,000 S.F.), the calculation shows that the proposed grocery store may capture enough demand to be successful. Note that the market share is greater than the demand gap because the new store’s location will likely capture more than its "fair share" of customers.

Conclusion

The preceding discussion has shown several ways that GIS is used in retail demand and supply analysis. However, it should be noted that these methods only enhance the analysis and must be combined with a more in-depth study. Furthermore, there are many more GIS applications and advanced demand and supply analysis techniques that may be useful in downtown market analysis. For more information on using GIS in retail demand and supply analysis, consult the additional resources section.

Appendix A - Calculation of Retail Sales Demand per Capita

U.S., 2002 Dollars
Based on the 2002 Economic Census, U.S. Census Bureau

Appendix B - Estimates of Retail Sales per Square Foot GLA

Average of US Neighborhood, Community and Regional Shopping Centers
Based on the 2002 Dollars and Cents of Shopping Centers, Urban Land Institute

Appendix C - Retail Opportunities Evaluation Form