December 1998 No. 28

Retail Mix in Wisconsin's "Tiny Towns":
How Distance From a Major Discount Store
Impacts Local Retail Availability

What types of stores might make economic sense in a small community with a population of 1,000? How does distance from the nearest major discount-department store impact a community's retail mix? One way to begin to answer these questions is to analyze the types of businesses that are currently operating in other "tiny" Wisconsin towns.

This article summarizes a new UWEX report that analyzes the number and types of retail establishments in Wisconsin's cities and villages with populations ranging from 800 to 1,300 (referred to as "tiny towns"). Data is analyzed for communities located 5 - 15 miles, and greater than 15 miles from a major discount-department store (MDS). The data in this study may be used by chambers of commerce, economic development practitioners, and local entrepreneurs to search for potential retail opportunities.

Methodology
The first step in this analysis was to identify all Wisconsin cities and villages with populations between 800 and 1,300. Population estimates for 1997 from the Wisconsin Department of Administration were used to identify these communities.

These "tiny towns" were then segmented into two groups: 53 communities located between 5 and 15 miles ("as the crow flies") of a major discount-department store (MDS) and 28 communities located more than 15 miles from such a store. Major discount-department stores included in this analysis were Wal-Mart, K-Mart, Target and Shopko stores.

Next, a private business database was used to identify the number and types of retail establishments in the zip code area of each of these communities. Business data was purchased from American Business Information, Inc. (ABI) that reflects 1998 estimates of retail businesses currently in operation.

Retail Mix Analysis
Presented on the back page is a summary of the retail mix analysis. Here retail operations have been consolidated into 34 general categories. The average number and percent of total businesses are presented for communities 5-15 miles and >15 miles from a major discount-department store.

Conclusions from Data:
1. Most "tiny towns" have a retail base limited to only a few convenience-oriented businesses. Tiny town retailers typically include restaurants, taverns, building material sup pliers, convenience stores, specialty food shops and grocers. Many also have farm/garden stores, auto dealers, radio/TV/music and gift shops.

2. While most small communities are limited to only a few convenience-oriented businesses, this analysis also shows that even within these communities, there can be a wide range of retail stores, many that we would not expect to see there. Examples include sporting goods shops, appliance stores, boat dealers and art galleries. Each community has a unique mix of these specialty retailers, many of which serve a more regional market area.

3. The data also indicates that towns further away from a major discount-department store such as Wal-Mart have significantly more retail establishments. Communities 5 to 15 miles from a major discount department store had an average of only 21 stores while communities >15 miles had an average of 32 stores. This is consistent with research in Iowa that indicated that towns that do not have but are close to a Wal-Mart were most impacted by that retail giant.

4. Communities further away from a major discount department store have a slightly higher percentage of retailers in the gift and other categories. However, the overall percentages for each retail category are very similar.

When using this data in your town, it is important to remember that each community is unique and different. The data only indicates what other "tiny towns" look like, from a retail mix perspective, and not what is optimal. Further, it does not differentiate communities with more substantial non-resident (tourist) retail demand. These and other factors should be considered. By understanding these limitations, a community can use this data to develop a better understanding of its retail strengths and weaknesses as well as opportunities and threats. This learning forms the basis for identifying objectives for improving the retail mix and developing strategies for recruitment, retention and expansion initiatives.

Retail Stores Per "Tiny Town" Zip Code Area
Wisconsin Cities and Villages with Populations of 800-1,300

			5-15 miles from MDS	 	>15 miles from MDS 	
Store Type		Avg. # of Stores    % Mix	Avg. # of Stores    %Mix
Eating Places			3.3	    15.6%		5.1	    16.0%
Drinking places			3.1	    14.8%		4.8	    15.1%
Building Materials		1.2	    5.5%		1.8	     5.6%
Food-Convenience		1.2	    5.5%		1.5	     4.6%
Other				1.1	    5.0%		2.0	     6.4%
Specialty Foods			1.0	    4.9%		1.4	     4.5%
Food-Grocery			0.9	    4.5%		1.1	     3.6%
Farm/Garden			0.8	    3.7%		1.0	     3.2%
Auto/Truck			0.8	    3.9%		1.3	     4.1%
Radio/TV/Comp/Music		0.7	    3.4%		0.8	     2.6%
Gift				0.7	    3.5%		1.6	     4.9%
Hardware			0.6	    2.9%		1.0	     3.2%
Auto Supply			0.6	    2.7%		1.1	     3.6%
Gas Stations			0.6	    2.7%		0.5	     1.6%
Antiques/Used			0.6	    2.8%		0.8	     2.5%
Furniture			0.5	    2.4%		0.6	     2.0%
Sporting Goods			0.5	    2.1%		1.0	     3.0%
Boat/RV/SnowM			0.4	    1.7%		0.6	     1.8%
Apparel				0.4	    2.0%		0.4	     1.3%
Home Furnishing			0.4	    1.7%		0.4	     1.2%
Hobby/Toy			0.4	    1.7%		0.3	     0.9%
Appliance			0.3	    1.4%		0.3	     0.9%
Flower				0.3	    1.5%		0.5	     1.7%
Department			0.2	    0.7%		0.3	     1.0%
Drug				0.2	    1.1%		0.6	     1.9%
Liquor				0.2	    0.7%		0.4	     1.2%
Mobile Homes			0.1	    0.4%		0.0	     0.0%
Office Supply			0.1	    0.3%		0.1	     0.3%
Jewelry				0.1	    0.3%		0.1	     0.3%
Shoe				0.0	    0.1%		0.1	     0.3%
Book				0.0	    0.2%		0.0	     0.1%
Camera				0.0	    0.0%		0.0	     0.0%
Luggage				0.0	    0.0%		0.0	     0.1%
Sewing				0.0	    0.2%		0.2	     0.6%
       			Total	21.3	    100%		32.0	     100%

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