Assignment 5: Site Location

Bass Pro Shops Retail Site Selection

Presented to:

Bass Pro Shops Marketing Team

Prepared by:

Zach Miller

Geospatial Analyst - University of Wisconsin Eau Claire

Project Overview

Bass Pro Shops is an outdoor gear and apparel retailer with more than one hundred locations around the nation. Catering to anglers and sportsman alike, Bass Pro Shops emphasizes maximizing the customer experience at their stores or online, proving the best quality tools and equipment for the outdoors, and conserving the land and game that make it all possible. Eau Claire, Menominie, Chippewa Falls, Lake Hallie, Altoona, and many other nearby cities/towns are major fishing hubs and outdoor communities that could really use a one-stop bait and gear shop. With Gander Mountain closing and SCHEELS Sporting Goods being the only competitive outdoor gear provider in the Chippewa valley, Bass Pro Shops and the greater Eau Claire area would be missing out on a huge opportunity by not implementing a store in Eau Claire, WI. 

For this assignment, I will preform analyses on potential site locations for a new Bass Pro Shops store. These analyses will look at how income, population, drive time access, other retailers, and recreation habits all factor in to where a good site location for a new Bass Pro Shops would work well.

Methods

The first step in site selection is market analysis. It was important to understand the threshold of Bass Pro Shops (BPS) store implementation. In figure 1, the current BPS in the US located in cities of ~67,684 people, give or take 10,000, are shown. 

Figure 1

Knowing that there are ten successful BPS in "smaller" cities much like Eau Claire, reinforces the feasibility of implementing a BPS in the Eau Claire area. The next step was to look at other retailers for bait, tackle, and outdoor gear.

Figure 2: Market Structure Map.

In figure 2, all bait, tackle, and outdoor gear stores, big and small, within the study area are shown. Gander Mountain, which is located due southeast of the furthest southeastern store shown on the map, was not included due to its expected demise. However, eight stores over multiple cities is relatively low considering how prevalent fishing and outdoor recreation are in the study area - there is most certainly room for development in this market.

From there, three sites were selected based on the pre-existing stores located in figure 2 as well as easy access from major highways. The "rank sites" tool from business analyst was used in figure 3 to rank the three chosen sites based on specified attributes within a ten mile radius. The attributes chosen consisted of:

- Number of potential customers that went fishing in the last 12 months.
- Number of potential customers that spent over $250 on sports and/or recreation equipment in the last 12 months.
- 2016 total population.
- 2016 average household income between $50,000 and $200,000.

Figure 3: Potential Sites

These characteristics were helpful in determining which site was best suited for the ideal customers that would be shopping at a BPS. In figure 3, potential store one was deemed the most suitable store for the criteria specified above.

Next, trade areas were calculated in figure 4 to see drive times to each of the stores. Each of the rings represents a different threshold for drive times. The yellow rings represent drive times of ten minutes or less to each individual store, the red rings represent drive times of fifteen minutes or less, and the blue rings represent drive times of twenty minutes or less. In figure 4, some of the trade area for the Eau Claire site was covered up by the Lake Hallie store trade area, and because they are relatively close they mostly share the same trade area anyway. However, the red thin line near the southern portion of the map is pertaining to a drive time threshold for the Eau Claire site.

Figure 4: Drive times and trade areas.

Lastly, a gravity model (or point of indifference) was calculated to determine the locations of where customers will choose which store to go to.

Figure 5: Gravity model / Point of indifference.

In this formula:
d = distance along major highway between two cities.
Pa = population of city a
Pb = population of city b

Since the three sites chosen were in Menomonie, Eau Claire, and Lake Hallie, I chose Eau Claire to Menomonie for one distance, Chippewa Falls to Lake Hallie for another, and Chippewa Falls to Eau Claire for a third. The breaking point for the first distance (Eau Claire [a] to Menomonie [b]) was 19.5 miles. The breaking point for the second distance (Chippewa Falls [a] to Lake Hallie [b]) was 2 miles. The breaking point for the third distance (Chippewa Falls [a] to Eau Claire [b]) was 3.6 miles.

Conclusion

Implementing a Bass Pro Shops store near the River Prairie exit on US-53 highway would be a great location for this store to do well. Based on many factors analyzed in this assignment, this location would serve the needs of outdoorsmen and anglers from all around the greater Eau Claire area. Since the store's location would be technically in Altoona, a neighboring city of Eau Claire, the tax payers of Altoona would also benefit from this deal and stimulate their economy all while benefiting a great company that upholds standards of quality products and services, customer satisfaction, and sustainable practices.

Assignment 4: Retail Site Selection for Trader Joe's

Project Overview

Trader Joe's is a nationally recognized grocery store with six locations in the Minneapolis/St. Paul, Minnesota area and is looking to expand. Through the use of ArcMap, Business Analyst, and customer data, the best location for a new Trader Joe's store will be determined. 

Site Selection

The first steps in the site selection process is establishing the geographic extent of the area being studied, (this is known as the "study area"). For this assignment, the study area was set to Ramsey and Hennepin counties. Also determining the locations of current customers and store locations are an important aspect of site selection. Figure 1 shows a map of the study area in red, locations of Trader Joe's stores in the greater Minneapolis/Saint Paul area as gold stars, and locations of customers as white dots.

Figure 1: Study area and, locations of Trader Joe's stores, and customers.

Now that the study area, locations of stores, and locations of customers have been established, the next step is to determine market penetration of Trader Joe's stores within the study area. To determine how well Trader Joe's stores are doing compared to their competitors, market penetration looks at the number of Trader Joe's customers compared to the number of people within a geographic area. In figure 2, darker green areas show where Trader Joe's penetrates the grocery store market at higher levels than in lighter green areas. The red point on the map with the black dot in the middle shows the geographic center of all Trader Joe's customers in the study area. Again, Trader Joe's store locations are shown as stars on the map and green dots represent the locations of customers.

Figure 2: Trader Joe's market penetration.

 In addition to market penetration, it is helpful to know where ideal customers are located to determine site selection. Ideal customers can mean many things, but for the purpose of this assignment, ideal customers are ones who have families to feed and money to spend. These criteria can be analyzed through using the median household income and total families datasets. Ideal customer areas, shown as green areas in figure 3, are ones with a median household income of greater than $80,000 and have families.

Figure 3: Ideal potential customer areas.

Lastly, three locations were determined (shown in figure 4) as being the best potential sites to put a new Trader Joe's location. These locations were selected based on their proximity to ideal potential customers, market penetrations, and customer access. The three best locations are represented as red stars in figure 4 and the circles behind them indicate a ranking based on total population, median annual income, over $150 spent at a grocery store on average per week, and shopped at a Trader Joe's within the last six months. Red is the best choice of the three, orange is the second best, and yellow is the third best.

Figure 4: Potential locations for a new Trader Joe's 

Conclusions

What can be taken away from this analysis is that the best location to put a new Trader Joe's store would be in north west Eden Prairie (see figure 4). With close proximity to an ideal potential customer market in Chaska and minimal market penetration for room to grow in Chanhassen, Excelsior, and Shakopee, 16545 Luther Way, Eden Prairie, MN is a prime location for a new Trader Joe's location.

It is clear that business analyst is an extremely powerful tool in determining markets, site selection, and many other analyses pertaining to the growth of a business. Through examining where Trader Joe's customers and store locations were in a study area, many tools in the business analyst extension of ArcMap were used to research markets, potential customers, and best store locations. Ultimately, much more analysis would need to be done in order to truly determine if the potential sites chosen were for sale, affordable, and return on investment would put Trader Joe's in the green with the new location. Nevertheless, this exercise provided some good insight as to what it would be like to select a new site for a company such as Trader Joe's.   

Assignment 3: Real Estate Analysis

Background: The United States has a wide range of home values depending on numerous statistics and characteristics, and Eau Claire is no exception. 415 Congress street is a two-bedroom home within Eau Claire's 3rd ward district, and studying this home will yield insights into the Eau Claire housing market and it's geographic tendencies. The information that will follow will be in the interest of selling this home, so as to also discuss demographic tendencies of home buyers.

Procedure:

1. Analysis of the home itself, as in bedrooms, amenities, land, and other aspects specific to 415 Congress Street.

2. Analysis of the 3rd ward area and its similarities as well as differences compared to other neighborhoods around Eau Claire.

3. Demographic analysis of people that live in the 3rd ward area as well as prospective buyers of the home.

4. A comprehensive monetary analysis of the particulars discussed in sections 1,2 and 3 in reference to a final listing price for the home.   

Analysis:

Location: 415 Jefferson Street

The house at 415 Jefferson street is a single family home with two bedroom and two bathrooms.The house is roughly 2,000 square feet and includes a two car detached garage. Most homes in this area do not have garages, which is one reason why 415 Jefferson is unique. This house was built in 1871 but has since been updated most recently with new appliances. As well as well as a new roof in 2012. Throughout the home you will find hardwood floors and oak woodwork. Other houses in the area are about the same size with two or three bedrooms. However, not all of those homes have been recently updated. Given this home's size and location we would most likely be selling to a single family possibly with one child and a parent that would work at the university. Because this home is for sale and not for rent we would not market this to college students but rather full time residence.

The Bureau of Labor has numerous markers available that have been synthesized with market research to better understand the value of a home and it's surroundings. For example, the average price of a home will increase roughly 17-19% if there is a park within 100 feet. Having a school nearby affords a heavier police presence, and overall makes a community safer, which therefore can potentially raise values of a home by 10-15%, depending on the quality of the school. 

Figure 1: Amenities near 415 Jefferson St.

On top of the local park and school, 415 Jefferson is located less than a block away from a community garden. Unique features such as this produce heightened interest in housing markets depending on the target buyer, which includes families, as per a 2005 Texas A&M study, where other items such as landmarks and tourist attractions raised home value. 

Neighborhood Analysis

415 Jefferson Street sits within Eau Claire's 3rd ward neighborhood, which is a few blocks away from downtown and the UW-Eau Claire campus. Compared to other neighborhoods nearby, the average home price in the 3rd ward is high, and well above the city average, which is $157,000 (Zillow).

Figure 2: Average listing prices

Figure 2 displays the prominent uptick in Home value and final sale price the Third ward holds over nearby neighborhoods. A decent portion of the value rests on individual characteristics as mentioned previously, however a great portion rests on location of a home in Eau Claire. It's central location within the greater city, its locality to major shopping centers south of Eau Claire, and it's proximity to UW-Eau Claire, which supports roughly 3,000 jobs at any one time, are key factors.

Demographic Analysis

Home buyers are often concerned with the people they will call neighbors when searching for a home, and usually prefer to belong to a neighborhood that they themselves can identify with. Age, education, children, socioeconomic status, buy or own  are all key factors. The U.S. Census is usually the best place to consult initially for this kind of data, which is often a key point in real estate.

College Town Distribution

With 415 Jefferson in the 7th census tract of Eau Claire, the age distribution is slightly skewed, and predominately reminiscent of an Old and Newcomer population pyramid, shown below.

The nearby 17th census tract, with a greater majority of the third ward, comprises demographic characteristics of a college town age distribution, shown above. The characteristics of this segment are similar to an old and Newcomer distribution with regards to the mix of renters, homeowners, and single families, but it has a lower proportion of homeowners. The Old and Newcomer segment is characterized by people in transition of college to full-time employment and recent retirees. Further data collected supported this conclusion, including income data, which expands on the renter to ownership ratio based on median household income. Census block 7, as of 2016, had 526 homes with a household income greater than $50,000, compared to just 137 for census block 17. Even more telling, block 7 had 1175 declared family households, compared to 366 in block 17, mostly due to many of the houses in block 17 being rented by students, which then also drives down real estate prices.



Final Pricing Assessment


With all these geographies playing into consideration, including the visuals above, a final listing price of $180,000, or around said price, would be satisfactory of 415 Jefferson Street. With the home being modern, as well as being close to many commodities, this price would accurately reflect the homes value considering current market trends. The last time the house was sold, in 2007, it sold for $156,500, and Zillow currently lists the house at $174,900, however, given the characteristics of the house, the local area, and local demographics, $180,000 would be a fair assessment. 

Resources:
Bureau of Labor Statistics.
“Eau Claire Comprehensive Plan 2015: Neighborhoods and Districts Assessment”. City of Eau Claire Wisconsin. http://www.ci.eau-claire.wi.us/home/showdocument?id=9331.
Esri Business Analyst
“Tapestry Segmentation.” Esri.
http://doc.arcgis.com/en/esri-demographics/data/tapestry-segmentation.htm#ESRI_SECTION1_87F5D845F8E04723AE1F4F502FF3B636.
“College Towns.” Esri. http://downloads.esri.com/esri_content_doc/dbl/us/tapestry/segment66.pdf.
“Old and Newcomers.” Esri. http://downloads.esri.com/esri_content_doc/dbl/us/tapestry/segment38.pdf.
Google Earth
Google Maps

Zillow.com

Assignment 2: Study Areas, Geocoding, Customers, and Trade Areas

Abstract

For this assignment, two friends own coffee and doughnut shops in two separate locations in San Francisco, CA. They want to determine how each of their stores are doing in relation to one another, other coffee and doughnut shops, and ensure that they reach the most customers possible without competing against each other. Through a series of four maps and some analysis of them, these business inquiries can be answered.

Methods

For the context of this assignment, five maps were created. The first, showing where each store's customers live. The second, showing where other coffee and doughnut shops exist. The third, showing each store's customer trade area. The fourth, showing drive time areas. The fifth, showing average incomes by census clock group. All of the maps for this assignment were created in ArcMAP.

For the first map, and all of the maps thereafter,  a study area was created. Since the stores are located in San Francisco, the logical study area created was in San Francisco county. Setting up a study area not only allows for more accurate and defined analysis, it greatly speeds up data processing and drawing since the only area of interest has been defined with the study area. Once the study area was defined, locations of each store and their respective customer's locations were geocoded into the study area. This means that the individual addresses of these places were put into the coordinate system defined in the study area as geographic coordinates. The mean center and standard distances of each of the store's customers were also calculated. The mean center shows a spatial rendering of the geographic center of each store's customers, and inherently in relation with the store's location. The standard distance is represented by an ellipse. This shows where around 68% of each store's total customers reside and also helps with the spatial analysis of this project.

Map 1

For the second map, a similar geocoding process took place but this time with other coffee and doughnut shops within the study area. This map along with Map 1, can provide some very useful information as to which customers are choosing this coffee and doughnut shop over others that may be closer in proximity.

Map 2

For the third map, customer trade areas for each store were calculated. This was done by inputting each store's customers into the customer derived area tool. The three layers provide a bit more accurate representation of where customers reside for each store than the standard distance calculation done in the first map. The green layer represents where 30% of the store's customers live, the yellow layer 50%, and the red layer 70%.

Map 3

    For the fourth map, a drive time area for each store was calculated. This was done by inputting San Francisco's road network into the drive-time areas tool. The three layers represent different distances a customer would have to drive to get to the business. This calculation provides a very useful idea as to how far customers are willing to drive to each store based on real road networks in San Francisco.

Map 4

For the fifth and final map, the median household income for each block group in San Francisco was added to the map. This was a preset of business analyst that was set up before the study area was but can be added to any map by adding median household income as a value in a graduated colors symbology.

Map 5

Analysis

Looking at the results, there is only a slight overlap between where about 68% of each store's customers are located and it appears to be right in the middle of the two stores. Considering store 2 has around 425 customers on record and store 1 has around 352, store 2 is doing a bit better than its counterpart. This is most likely due to the high number of coffee and doughnut shops on the north east side of town, creating more competition surrounding store 1 than surrounding store 2. It looks like each store is taking some of the other store's customers, as well. With a few blue dots within a couple miles of store 1, there are some customers that are choosing to go to store 2 instead, and vice versa. Where customers spend their time during the day could determine which store they go to when they're at work, school, etc.

There isn't too much concern as far as competition between the two stores goes, however. Both stores have a good amount of customers within walking distance (map 4), but what about customers that do not live within walking distance? Most driving customers are coming from the west side of town, and there isn't too much competition along the way to either store, which is great. However, if each store is looking to maximize their customer trade area, this business should look at marketing to west side neighborhoods where they already have some clientele coming from. Perhaps store 1 could market to potential customers living on the north side of Golden Gate Park and store 2 could market to potential customers that live south of Golden Gate Park. Another option would be to set up another store just south of Golden Gate Park (map 5). With minimal competition on that side of town (map 2), this area could provide ample opportunity to expand their business. This expansion would be a closer commute for customers currently going to either store as well as potentially bring in new customers from that area. Looking at map 5, median household incomes look promising on the west side of San Francisco as well, meaning that business could go well if there are potential customers who have money to spend in these areas.

Conclusions

After reviewing and analyzing the results, I feel as though marketing to San Francisco's western neighborhoods will be in the best interest of the business for now. Opening up a new store takes a lot of capital and could be risky to what looks like steady business at the moment. It looks to me like the customers that are going to the store that is actually farther away from their residence might either work near that particular store's location or pass by that particular store on their way to work, school, etc. This also falls into the context of customers living in the west-side neighborhoods, which in turn makes me a little weary about setting up a store on the west side. If customers want to wait til they're closer to work or school before they get their coffee or go on a coffee run / lunch break once already at work or school, then erecting a store near west-side customer's residences might not actually bring in any more business. The best thing to do would be to advertise store locations to the west side of San Francisco and offer incentives to customers to fill out a survey as to why they come to the location they do. If the business starts to see more interest in having a store closer to customers on the west side, only then should the business seriously consider setting up a third location closer to their long distance-commuting clients.

Assignment 1: Population Dynamics

Abstract

A company wants to invest in a business located in Jacksonville, FL. The team is unsure which type of business to invest in as they have different ideas of which demographics might be more marketable than others. Some think that Florida's growing children population could be a good market, some feel as though the company should look to high amounts of retired people as potential customers, and some feel as though Florida's large hispanic population is the most marketable. By looking at these different populations, the company can determine which demographic truly is the best to market to with their business investment.

*All calculations done in this assignment are based on estimates from the U.S. Census Bureau

Jacksonville's Population Pyramid

Figure 1. Population pyramid of Jacksonville, FL

The population pyramid shows a visual representation of Jacksonville's population dynamics in terms of age and sex. There are a fairly even amount of men and women with the exception of women 55 and older outnumbering men 55 and older. It's also evident that there are a large concentration of people aged 20 to 29, this could be due to Jacksonville's many universities and other postsecondary education options. There is also another bulge in the graph of people aged 45-59, this could represent the "baby-boomer" and "X" generations, where a lot of babies were born in the U.S. 45-59 years ago.

Calculating Dependency Ratios

The dependency ratio compares the non-working population (youth and the elderly) to the working population of a given place. The population data used to calculate these statistics is given in four year increments and represented as a percentage of the total population of Jacksonville (~846,951 people). The youth dependency ratio (YDR) is the sum of populations under 5 years, 5-9 years, and 10-14 years.

6.9% * 846,951 = 58,739 people under 5 years

6.6% * 846,951 = 55,379 people aged 5-9 years

6.1% * 846,951 = 52,019 people aged 10-14 years

Total YDR = 166,137 people

Next, the elderly dependency ratio (EDR) is calculated. This group is meant to represent citizens of Jacksonville that are no longer contributing to the work force (on average), aged 65 years and older.

4.3% * 846,951 = 36,502 people aged 65-69 years

2.8% * 846,951 = 23,770 people aged 70-74 years

1.9% * 846,951 = 16,585 people aged 75-79 years

1.5% * 846,951 = 12,377 people aged 80-84 years

1.6% * 846,951 = 13,252 people 85 years and older

Total EDR = 102,486 people

Figure 2. Formula for calculating dependency ratios

The dependency ratio (DR) for Jacksonville is calculated using the formula in Figure 2. This is done by adding the YDR and EDR together which returns the total number of dependents, then dividing by the population of people aged 15-64, this is the total working population. Lastly, multiplying the resulting quotient by 100 will return the DR.

Number of Dependents = (Total YDR + Total EDR) = 268,623

Population (Ages 15-64) = (Total Population - Number of Dependents) = 578,328

DR = 46.448

For the state of Florida, the dependency ratio is :

Total YDR = 3,339,781

Total EDR = 3,634,468

Number of Dependents = (Total YDR + Total EDR) = 6,974,249

Population (Ages 15-64) = (Total Population - Number of Dependents) = 12,671,523

DR = 55.039

Looking at the data, there are 63,651 more youth dependents (those 14 and younger) in Jacksonville than elderly dependents (those older than 65). This difference accounts for about 7.5% of the Jacksonville population, which is quite a significant difference considering that youth dependents account for nearly a fifth (19.6%) of Jacksonville's population and elderly dependents only account for just over an eighth (12.1%).

Calculating Location Quotients

The location quotient shows where groups of certain demographics are concentrated as compared to the country's average.

Table 1. Used to calculate location quotients for various geographies of Florida

To calculate the Location Quotient of a given geography in either Jacksonville, Duval county, or the state of Florida, one must divide the percent population of that place by the percent population of the United States. 1 indicates that a given area has an average concentration of a particular group (ie. 10-14 population of Duval County), greater than 1 indicates a higher than average concentration, and lower than 1 indicates a lower than average concentration.

LQ = (percent population at city, county, or state level)/ (percent population at US level) 

LQ (Pop. 0-14): Jacksonville = 1.02 , Duval County = 1 , Florida = .88

LQ (Pop. 65+): Jacksonville = .86 , Duval County = .87 , Florida = 1.32

LQ (Hispanic): Jacksonville = .5 , Duval County = .49 , Florida = 1.39

LQ (White): Jacksonville = .86 , Duval County = .89 , Florida = .90

Notice the above average youth dependent concentration in Jacksonville. There is also a greatly above average concentration of elderly dependents and hispanic populations at the state level for Florida.

Selected Economic Characteristics

The location quotients for various economic sectors of Jacksonville is shown in Table 2. It lists financial, professional, educational, arts, other, and public administration sectors and their concentration compared to the average in the state of Florida. Percentages were calculated by dividing the sector by the total number of service industries. Location quotients were calculated by dividing the percentages of Jacksonville's service industries by the percentages of Florida's industries.

Table 2. Shows location quotient of various economic sectors for Jacksonville, FL

 Looking at Table 2, there is an above average concentration of both financial and public administration sectors. This might be indicative of the large number of college students and the working population. 

Analysis

After having looked at Jacksonville's age and sex population pyramid, dependency ratios, and location quotients of population, demographic, and economic sectors, there are a few good options for what type of business to invest in. Due to the high amount of young people in the work force as well as the soon-to-retire population, it might be smart to market to the elderly. Although there aren't too many elderly dependents currently in Jacksonville, there will be within the next decade once the late baby-boomer generation reaches that age and the large percentage of Jacksonville's population, the working population, will come steadily after them. This could be a good market assuming that the baby-boomers and current working population won't move after retirement. 

Another potentially good investment could be to market to youth populations. With youth dependents making up nearly an eighth of Jacksonville's population, having an above average concentration than the rest of the country, and increasing steadily, there is a good market up for grabs with this age group. With the large amount of jobs in financial and public administration sectors, this could be attractive to young people who want to settle down and start having children, thus feeding the already high concentration of this population.  

College-aged students could be a good group to focus marketing on as well. Having a few universities and multiple colleges, vocational schools, and the like will attract that age group for as long as they are up and running. Not to mention the upwelling of youth could likely result in that population staying in Jacksonville to receive a postsecondary education. There are above average financial and public administration sectors to offer jobs to recently graduated students as well. 

Overall, the best marketing option to invest in is the youth population. They make up nearly 20% or an eighth of the cities total population and birth rates have been rising for a few years. With the many job opportunities in financial and public administration sectors, adults seeking to become parents can easily find work and afford to have children.