Final Project: Culver's Site Selection

Introduction:

Site selection is the process of determining where to locate a business. As location is often the key to a store's success, this process is of utmost importance. Culver's is a restaurant founded in Wisconsin that prides itself on serving fantastically delicious frozen custard to people all across the state and country. 

In order to determine a new location for Culver's, I am going perform a series of analyses. First, I will identify the most attractive markets in which to operate. Next, attractive sites within that market are identified and assessed by the density of supply and demand within the market. After the sites have been assessed, the best site is chosen as the new retail location.

Methods:

First, I created drive time polygons around the existing Culver's restaurants in Wisconsin. I then appended demographic data to the polygons in order to determine key characteristics from the data. 

Next, I located the ideal customers by analyzing demographic data throughout the study area. Culver's is a fairly average fast-food restaurant, and as a result doesn't require an affluent or large customer base in order to thrive. To account for this, I specified my "ideal customer" search filter to show zip codes with median household incomes greater than $40,000 per year (Figure 2). I also added another filter to only show areas with populations larger than 10,000 in order to ensure a modestly strong customer base for the new store location (Figure 3).

Figure 2: Zip Codes with Median Household Incomes >$40,000

Figure 3: Zip Codes with total populations > 10,000

Next, I compared the "Ideal Customers" zip codes to current Culver's locations, to ensure there is enough distance between the two to prevent cannibalization of the customer base. I located possible sites in Ashland, Hayward, and Medford. I created 15 minute drive time trade areas around each of the points. I then used the spatial join tool to count the number of restaurants within 15 minutes of the site. Next, I divided the population of the trade area by the number of restaurants to determine the market saturation (Figure 4). The Medford site has a higher population and less restaurants than either of the others, causing it to have a lower degree of market saturation.

Figure 4: Market saturation of the proposed sites.

I performed the same analysis on the existing store locations in order to compare the market saturation values. The lowest of the proposed saturation values is still higher than many of the existing market saturation values, eliminating some of the concern related to market saturation (Figures 4,5).  

Figure 5: The market saturation of the existing restaurants.

After the sites were selected, the Ashland, Hayward, and Medford sites were ranked by their total populations, median household incomes, how likely persons were to eat unhealthy food, and how many people at at fast food restaurants 9+ times a month. The Medford site was ranked highest, followed by the Hayward site, with the Ashland site ranked third (Figures 6,7).

Figure 6: The ranked sites.

Figure 7: The selected site.

Medford has a large range of influence over the surrounding area. According to gravity model equations, Medford has a tremendously large influence over the surrounding areas. Persons within 5.146 miles to the south, 18.59 miles to the north, and 26.24 miles to the west will all be very likely to travel to Medford when they require goods they are unable to acquire in their towns. This draw will be essential for the restaurant to truly thrive in this location.  



Here are the resulting values from the gravity model calculations: Medford: 4324
Stensonville (South): 583 --> Distance: 6.28 --> breaking point: 1.134mi
Rib Lake (North-by-Northeast): 886 --> Distance: 19.79 --> breaking point: 1.20mi
Lublin (West-by-Southwest): 111 --> Distance: 27.26 --> breaking point: 1.02mi

Site Selection

Introduction:

Site selection is the process of determining where to locate a retail shop. As location is often the key to a store's success, this process is of utmost importance. This is done by first identifying the most attractive markets in which to operate. Next, attractive sites within that market are identified and assessed by the density of supply and demand within the market. After the sites have been assessed, the best site is chosen as the new retail location.

I am going to use this process in order to find the best location for a future Trader Joe's grocery store in Hennepin and Ramsey counties in Minnesota.

Methods:

First, I conducted a market penetration report in order to see how much of an impact Trader Joe's had on the markets of the Minneapolis-St. Paul metro area. The resulting values ranged from <2% of the population to 28%. This result shows how well specific stores are reaching their markets. Areas with higher market penetration don't necessarily need additional stores, as they would only be cannibalizing from their own customer base (Figure 1).

Figure 1: The market penetration of Trader Joe's in Hennepin and Ramsey Counties.

Next, I located the ideal customers by analyzing demographic data throughout the study area. Trader Joe's is a more upscale grocery store, and as a result requires a more affluent customer base in order to thrive. To account for this, I limited the "ideal customer" search filter to only show zip codes with median household incomes greater than $60,000 per year (Figure 2). I also added another filter to only show areas with population growth between 2010-2025 in order to ensure a strong future for the new store location (Figure 3).

Figure 2: Median incomes greater than $60,000

Figure 3: Areas with positive growth rates

After the attractive markets were located, three sites were selected. One of the sites is in Excelsior, in an empty lot in the town's downtown area (Figure 4). The next site is in Wayzata, just down the block from a new lifestyle center. The third location is in Eden Prairie, just outside of Eden Prairie center, a large mall.

Figure 4: The Excelsior site.

After the sites were selected, the Wayzata, Excelsior, and Eden Prairie sites were ranked by their total populations, median household incomes, how likely persons were to spend >$150 dollars per week at food stores, and how many people shop at Trader Joe's. The Excelsior site was ranked highest, followed by the Wayzata site, with the Eden Prairie site ranked third (Figure 5).

Figure 5: The sites, with their resulting ranks.

Excelsior was ranked the highest because of its extremely high median household income of >$107,000. As Trader Joe's market penetration is lower in Excelsior than in Wayzata, adding a store in Excelsior will increase the size of Trader Joe's market without cannibalizing customers from the existing stores.

480 Roosevelt

This house is located on the South side of the third ward. It is a beautiful Victorian home that has a lot of space inside and out. There are many reasons why this is a great house to buy. These range from the neighborhood it is in, to the proximity to other events in the downtown business districts or parks. It also tucked away from the student rentals and other activities associated with college students.

Location

The Third Ward is a well-known part of town. There is a strong sense of community and pride within this neighborhood. They are tucked away from the late night parties and problems associated with college students. The third ward has many well educated folks who take pride in their city and want to keep it looking nice and beautiful.

Proximity

Eau Claire is well known for its artful history of the downtown. There are various means of transportation offered to see the scenic downtown as well as not long to reach them. It is a short walk, bike, car, or bus ride to any of the parks, restaurants, or music shows. There are many plays in Zorn Arena as well as sporting events to attend year round.

Geographic Data

Based on the zoning the neighborhood should never be taken over with student rentals. The surrounding areas are zoned for single families to live there and need to be taken before the city to be changed. It is very unlikely the zoning would change based on the city’s comprehensive plan. The would not want to increase zoning in this direction because the neighbors who take pride in where they live would have an uproar about the things that go on associated with college students. This house is also valued right in the median value for homes in the third ward. It is on the higher end of the medium value, but this is skewed by the northern part of the third ward which is student housing. For the size of the house and the location this house is very reasonably priced around 260,000. There are not many houses for sale in the third ward because it is such a good neighborhood and people don’t leave there homes often.

Summary

This house is very reasonable priced and in a great location. It is a short distance from any of the destinations in downtown Eau Claire. This is a very well-known part of Eau Claire and the city likes to protect this. It is home to many well educated individuals who try to give back to the community often. This house would be a steal for anybody looking for a home to raise a family. These are well build houses with neighbors, who look out for each other, that want to grow together.

Study Areas, Geocoding, Customers, and Trade Areas

Two coffee shops in San Francisco, California wanted analysis performed on their customer bases to better understand their markets and their customers. 

Store 1's customers are primarily located around the Western Addition of San Francisco, with major populations also coming from Chinatown, the Marina District, and the Richmond District (Figure 1). Store 2's customers are primarily located between the Outer Mission and the Mission District, with a smaller westward concentration in between Monterey Boulevard and Portola Drive (Figure 1). The mean center for Store 1’s customers is located ¼ mile southwest of the store, suggesting that the population is concentrated fairly evenly around the store, with slightly more customers southwest of the store’s location (Figure 1). The Mean Center for Store 2’s customers is ½ mile north-by-northeast of the store’s location. This suggests that there are more distribution of customers for Store 2 is more widespread, and the map supports this by showing a large number of outlying customers as far as Chinatown and the Marina District (Figure 1).

Figure 1: Store Locations & Mean Centers

Their competition is concentrated in the Financial District between Chinatown and I-80, with some other locations throughout the Mission District (Figure 2). The stores in the financial district prevent either store from receiving barely any customers from that district, though the impact is more pronounced on Store 1 (Figure 1). The competing stores in the Mission District limit the concentration of customers in that area, though Store 2 is still able to maintain a fairly strong customer base regardless of the competition (Figures 1,2).

Figure 2: Competitor Locations

Both stores exist in completely different markets. Figure 3 shows Customer Derived Trade Areas with 40% of the customers within the yellow ring, 60% of the customers within the red ring, and 80% of the customers within the blue rings. The stores are both in very different neighborhoods with very different client compositions.  

Figure 3: Customer Derived Trade Areas

Analysis of Store 1’s trade areas indicated that the customers within the 60% ring spend the most on food away from home, with a spending index of 148 (100 is the national average). The 40 and 80% rings had spending indices of 129 and 136, respectively. Among the trade areas for Store 1, the 60% ring has the highest median household income, and the lowest racial/ethnic diversity. The household sizes in Store 1’s trade areas are all between 1.81 – 1.78, suggesting that there aren’t many families in the area.

Figure 4: Store 1's trade area information.

Customers within all of Store 2’s trade areas have higher average spending indices than Store 1’s 60% ring, with the 40, 60, and 80% rings having 151, 159, and 161 respectively. Store 2’s 80% ring has the highest household income, lowest white population percentage, and the highest Asian population percentage among all of the trade areas. Store 2’s trade areas have much lower black populations, much higher Hispanic populations, and substantially more of the population identifying as “Some other race alone”, than Store 1’s trade areas.

Figure 5: Store 2's trade area information

Almost all of Store 1’s customers live within 1.5 miles of Store 1. Store 1 is in a part of the city with a much more traditional street grid which makes it easy for customers to walk to the store directly. Store 2 is in a part of San Francisco with irregularly organized streets, which cause the drive time area rings to be slightly shorter, in Euclidean distance (Figure 6).

Figure 6: Drive Time Areas for both stores.

According to my analysis, Store 2 is in a demographically preferable position. The population’s higher average household size allows for higher disposable income, which allows for more spending on coffee.

Colorado Springs Demographic Breakdown

I have been tasked with performing demographic analysis of the city of Colorado Springs in order to determine the demographic breakdown of the city. I am to analyze how the breakdown of Colorado Springs compares to the rest of its county, the state of Colorado, and the U.S. as a whole. I am to use this information to develop a business model that fits the most marketable demographic of the city.

According to my population pyramids of the city, the city has an overabundance of 20 to 29 year-old males (Figure 1). This is most likely due to both the Air Force Academy, and Cheyenne Mountain. The city also has a high number of citizens between 40 to 54 years old and an almost equally high percentage between 5 to 19 years old.(Figure 1). 

Figure 1: Population Pyramids

According to the Dependency Ratios I calculated, Colorado Springs has a slightly higher dependency ratio than the rest of the state. The entire population of the area is supported by the 53.7% that is actually working. This indicates both a large population of both youth and elderly.

Figure 2: Colorado Springs

Figure 3: State of Colorado

My Location Quotient calculations indicated the population of Colorado Springs has a different make-up from the rest of the Country (Figure 4). Colorado Springs has more population between 0-14 years of age, and more population racially classified as "White" than the US average (Figure 5). There is no difference between the percentage of the population that identifies itself as "Hispanic" in Colorado Springs from the US as a whole (Figure 5). Colorado Springs has significantly fewer elderly than the national average (Figure 5).
Economically, Colorado Springs is below average according to the percent of persons in the Finance industry when compared to the rest of the state (Figure 6). Professionals make-up the exact same percentage of Colorado Springs' and the State's industries (Figure 6). There are slightly higher percentages of persons in Educational and Arts related fields in Colorado Springs than the state as a whole (Figure 6). Other service industries and Public Administration are substantially higher represented in Colorado Springs than in the rest of the state (Figure 6).

Figure 4: Population Percentages

Figure 5: Location Quotient

Figure 6: Industry Location Quotients

Based on my analysis of the population of Colorado Springs, I have determined that the 20-29 year-old males are going to be the demographic our business will try to cater toward. I propose we develop the "Man Cave", a restaurant and entertainment experience featuring: airsoft/paintball, huge t.v. screens, a fully stocked bar with craft brews galore, a wide variety wings, and an extensive arcade. We will establish ourselves as the place for all of the air force academy students to spend all of their time and money.