Final Project: Menard's Site Selection

Menard's: Store Site Selection

Presented to

Menard's

Prepared by

Andrew Jeffers

May 22, 2017

Executive Summary

Purpose and method of this report

Menard's is a company whose goals, among many, include making a profit. They are interested in what is going on in the greater Denver, Colorado area, and they believe adding another store is needed and wish to expand their business in this area in an advantageous location. The purposes of this report are to:

• Analyze the potential customer base in the Denver area
• Determine and recommend three potential site locations for a new store and rank them from most to least favorable

Using ESRI Business Analyst, a number of analyses were executed as a way of determining the best possible locations for a new store. The analyses were conducted around the Denver area and include:

• Hot Spots: creates a custom-sized grid over an area and calculates demographics
• Customer Prospecting: find geographies within a set demographic range
• Rank Markets: markets are ranked based on selected attributes

Findings and conclusions

The results of the analyses provided mixed patterns concerning ideal potential customers in the surrounding area. It was up to the user to analyze the results to the best of their ability and choose three locations in which they think would be ideal to open a new store based off of these results. 

Recommendations on where to locate a new Menard's store

Recommendations for which sites would be ideal for adding a new store include (from most to least favorable):

1. 9042 Colorado Blvd Thornton, CO 80229
2. 832 Airport Blvd Aurora, CO 80011
3. 7984 W Almeda Ave Lakewood, CO 80226

Introduction

Menard's is a family-owned company started in 1958 that specializes in home improvement and is known throughout the industry as a low price leader. They have over 300 stores throughout the midwest and they are looking to expand their trade area. Currently, there are no Menard's locations within Colorado, however with Colorado's quickly expanding population, this may potentially be an ideal place to open a new store. Colorado's population has increased each year since 2010 when it stood at 5,048,644, and since then, population has increased by 491,901 residents to 5,540,545 in 2016, according to U.S. Census estimates (The Denver Post). Menard's ideal customers include home owners and professional customers such as builders, painters, plumbers and so on. Generationally speaking, baby boomers are the most important customer who tend to be do-it-yourselfers. However, a fast-growing segment in home ownership is younger people (millenials) who are more interested in do-it-for-me services and are value-conscious. Menard's largest competitors are Home Depot and Lowe's, who are the leaders of the home-improvement sector.

Purpose of this analysis

Business Analyst (BA) will run a number of analyses that will assist the user in determining where the best location will be to build a new Menard's store based off of demographic and business data provided by BA.

Scope of this analysis

The extent of this analysis includes Denver, Colorado and its surrounding area. More specifically, a 15 mile ring was placed, with Denver in the center, that served as the study area. 

Sources and methods

First, a map layer containing Menard's largest competitors was created. This was done by locating and entering the addresses of chosen competitors (Home Depot, Lowe's, and Ace) into a table and then geocoding the addresses and displaying them as a map layer. Google Maps was used as a way to determine which specific sites would be an ideal location to build a new store on. Demographic data was provided within BA and it is with BA that the analyses were conducted. The analyses that were conducted are as follows:

1. Hot Spots: A market analysis was run using 0.5 mile grid cell sizes and 2016 Total Population for the symbolization field. Also, 2016 Median Household Income was used as an added variable. After the analysis was ran, two hot spot maps with graduated color symbols were produced: one showing population and the other showing income.
2. Customer Prospecting: A market analysis was run using zip codes as the input level of geography where values were entered manually since there was no customer data available for this project. 2016 Total Households was one of the variables used where the average = 11,459, the floor was set to 12,000, and the ceiling was set to 26,000, just above the max value. This was done as a way to target higher household areas. The other variable used was 2016 Labor Force by Industry: Construction as a way to target professional customers where the average = 1198, the floor was set to 1200, and the ceiling was set to 4900 just above the max value. Once again, this was done as a way to target a higher number of professional customers. 

After these analyses were ran, each one was manually compared and contrasted with the other to determine which three areas may be ideal locations to set up a new store. After the three areas were selected, Google Maps was used to find specific sites for a store where considerations included how big the lots was, what the proximity was to other retail and commercial outlets, and how well traffic flowed through that particular area. Using the addresses provided by Google Maps of each site, an Excel table was used to normalize the address data so that it could be geocoded in BA. Two final steps were then completed which included:

1. Appending Data: In order to rank the sites, certain demographic and BA data needed to be added to the Potential Menard's layer. A market analysis was ran using the Potential Menard's layer as the layer that inherited the data. The analysis was run and the variables used were added as fields in the layer's attribute table. The variables that were added included:
• 2016 Total Population
• 2016 Median Household Income
• Ind: HH spent on home improvements in last 12 mo: $500+
• Ind: Home improvement done by HH member in last 12 mo
• Ind: HH Did home improvement by outside contractor/12 mo
• Ind: Hardware/electronics store/12 mo: Ace Hardware
• Ind: Hardware/electronics store/12 mo: Home Depot
• Ind: Hardware/electronics store/12 mo: Lowe's
2. Rank Markets: A market analysis was ran using Menards_append as the layer used to rank the selected sites. The primary field for ranking was 2016 Total Population and the additional selected fields included the other seven variables. The analysis was ran and the three potential store locations were then ranked 1 to 3 from most to least favorable.

Findings and Discussion

Figure 1: Menard's competitors

Competitors

Competitors in the Denver area are fairly well spaced out with no distinct clusters and are represented by large red X's. There are, however, areas with no large competitors in both the northeast and northwest sections of the ring (figure 1).








Hot Spots - Population

Figure 2: Hot spots based off of total population

The result of the hot spot analysis based off of total population (figure 2) is displayed as a 5-class choropleth map with bright yellow representing areas with the lowest populations to bright red representing areas with the highest populations. Areas with high populations are clustered near the middle including Denver, Lakewood, Aurora and the area north of Denver. Areas with lower populations can be seen on the west and northeast sides of the ring.





Hot Spots - Income

Figure 3: Hot spots based off of median income

The result of the hot spot analysis based off of median household income (figure 3) is displayed as a 5-class choropleth map with bright yellow representing areas with the lowest income to bright red representing areas with the highest income. Areas towards the upper, left, and lower sides of the ring tend to have the highest incomes while the far left area and northeast parts of the ring have the lowest incomes. Much of the area in the middle of the ring fall between the two extremes.





Customer Prospecting - Total Households

Figure 4: Ideal customer areas based off of total households

The result of the customer prospecting analysis based off of total households (figure 4) is displayed as a 5-class choropleth map where the best ranking is represented as bright red and the worst ranking is represented as bright yellow. The results here are quite mixed. The best areas include those east of Lakewood, north of Columbine, and south of Aurora.








Customer Prospecting - Construction Labor Force

Figure 5: Ideal customer areas based off of construction labor

The results of the customer prospecting analysis based off of construction labor force (figure 5) is displayed as a 5-class choropleth map where the best ranking is represented as bright red and the worst ranking  is represented as bright yellow. The results here appear to be more clear cut. The best areas include those east of Lakewood, about 8 miles east of Denver, and sections in the north and northeast areas. The worst areas include those towards the west side of the ring and some sections in the southeast area.




The Three Potential Sites

Figure 6: Potential Menard's store locations

Looking at all of the previous results together, three locations were chosen as potential sites for a new store, represented on the map in figure 6 as neon green circles with black dots in the middle. Site 1 is located in Lakewood (figure 7). Site 2 is located in Aurora (figure 8). Site 3 is located in Thornton (figure 9).

Figure 7: Lakewood location

Figure 8: Aurora location

Once the cities were decided upon, choosing a specific site location was based on where an empty lot could be found in an area where other retail is located and is within close proximity to high traffic flow, such as a major highway. Also, the lot had to be fairly large since Menard's requires a high amount of square footage for its stores.

Figure 9: Thornton location

Rank Markets

Figure 10: Ranking table

After the ranking analysis was ran, the results for site locations 1, 2, and 3 were ranked 3, 2, 1, respectively (figure 10). Site 3 (Thornton) had the highest population but featured the lowest median income. Site 2 (Aurora) had the second highest population but just edged out Lakewood for the highest median income. Site 1 (Lakewood) had the lowest population by far and the second highest income. 

Assignment 4: Site Selection

Trader Joe's Site Selection

Presented to

Trader Joe's

Prepared by

Andrew Jeffers

April 26, 2017

Executive Summary 

Purpose and method of this report

Trader Joe's is a company whose goals, among many, include making a profit. They are interested in what is going on in the Minneapolis and St. Paul, Minnesota area, and they believe another store is needed and wish to expand their business and add another store in an advantageous location. The purposes of this report are to:

• Analyze the relationships between the six Trader Joe's location in the MSP area with the surrounding area using customer information provided by Trader Joe's and their store locations
• Determine and recommend three potential site locations for a new store and rank them from most to least favorable 

Using ESRI Business Analyst, a number of analyses were executed as a way of determining the best possible locations for a new store. The analyses were conducted within Hennepin and Ramsey counties. These analyses include:

• Market Penetration: calculates market penetration by dividing customer data by demographics
• Hot Spots: creates a custom-sized grid over an area and calculates demographics
• Optimal Stores: finds an optimal store based on cluster distribution
• Customer Prospecting: finds geographies within a set demographic range
• Optimal Store Locations (Mean Center): determines the optimal location for a site based on the concentration of surrounding customers
• Rank Markets: markets are ranked based on selected attributes

Findings and Conclusions: 

The results of the analyses provided mixed patterns concerning the relationship Trader Joe's has with the surrounding area. It was up to the user to analyze the results to the best of their ability and choose three locations in which they think would be ideal to open a new store based off of these results. 

Recommendations of sites in which a new store could potentially be built

Recommendations for which sites would be ideal for adding a new store include (from most to least favorable):

1. 13625 Technology Dr, Eden Prairie, MN 55344
2. 800 Xenia Ave S, Golden Valley, MN 55416
3. 2365 Wayzata Blvd W, Long Lake, MN 55356

Introduction

Purpose of this analysis

Business Analyst will run a number of analyses that will assist the user in determining where the best location will be to build a new Trader Joe's store based off of customer data, current Trader Joe's store locations in the study area, and demographic and business data provided by BA.

Scope of this analysis

The extent of this study includes the Minneapolis and St. Paul, Minnesota region. More specifically, it is restricted to Hennepin and Ramsey counties. 

Sources and methods

Trader Joe's six store locations and customer data within the extent area were provided by Trader Joe's. Google Maps was used as a way to determine which specific sites would be an ideal location to build a new store on. Demographic data was provided within Business Analyst and it is with Business Analyst that the analyses were conducted. The analyses that were conducted are as follows:

1. Market Penetration: A market analysis was run using the customer data as the input layer and Zip Codes as the base layer used for calculations. The selected data collection was the 2016 Total Population. After running the initial analysis, some of the zip codes were then consolidated to produce a result that was easier to understand and interpret. 
2. Hot Spots: A market analysis was run using 1 mile grid cell sizes and 2016 Total Population for the symbolization field. Also, 2016 Median Household Income was used as an added variable. After the analysis was ran, two hot spot maps with graduated color symbols were produced: one showing population and the other showing income. 
3. Optimal Location (Mean Center): A site analysis was run using the customer data as the input layer where one mean store center was calculated using customer locations. 
4. Customer Prospecting: A market analysis was run using zip codes as the input level of geography and the customer data layer as the input as well. 2016 Total Households and 2016 Population Age 18+ were then used as variables. 2016 Population Age 18+ was used in particular as a way of targeting people who are more likely to go shopping since most people younger than 18 do not have the finances to support extensive shopping habits. 

After these analyses were run, each one was manually compared and contrasted with the other to determine which three areas may be ideal locations to set up a new store. After the three areas were selected, Google Maps was used to find specific sites for a store where considerations included how big the lot was, what the proximity was to other retail and commercial outlets, and well traffic flowed through that particular area. Using the addresses provided by Google Maps of each site, an Excel table was used to normalize the address data so that it could be geocoded in Business Analyst. Two final steps were then completed which included:

1. Appending Data: In order to rank the sites, certain demographic and BA data needed to be added to the Potential Trader Joe's Stores layer. A market analysis was run using the Potential Trader Joe's Stores layer as the layer that inherits the data. The variables that were added included 2016 Total Population, 2016 Median Household Income, Avg spent per week by HH (Household) at food stores: $150+, and Shopped at grocery store/6 mos: Trader Joe's. The analysis was run and these variables were added as fields in the layer's attribute table.
2. Rank Markets: A market analysis was run using Potential Trader Joe's Stores as the layer used to rank the boundaries in the market area. The primary field for ranking was 2016 Total Population and the additional selected fields included the other three variables. The analysis was ran and the three potential store locations were then ranked 1 to 3 from most to least favorable.  

Findings and discussion

Figure 1: Trader Joe's market penetration

Market Penetration

The result of the market penetration (figure 1) is displayed as a 5-class choropleth map with very light brown representing the lowest values to dark brown representing the highest values. The values indicate the percentage of customers within the zip code area compared to the total population within that area. Trader Joe's is penetrating the market well in all of Ramsey County and east Hennepin County. However, sales are somewhat lacking in west Hennepin County where the lowest percentage area are the westernmost sections and the section directly north of Lake Minnetonka. Trader Joe's stores are represented in this and subsequent maps as neon green stars. It's clear to see from this map that Trader Joe's may want to consider adding a location in the mid to western area of Hennepin County which may then allow for better market penetration in that area of the county.

Hot Spots - Income

Figure 2: Trader Joe's hot spots based off median household
income

The result of the hot spot analysis based off of median household income (figure 2) is displayed as a 5-class choropleth map with bright yellow representing areas with the lowest income to bright red representing areas with the highest income. Most of Ramsey and eastern Hennepin counties feature areas with lower incomes while northern Ramsey County and mid to western Hennepin County feature areas with much higher incomes. Trader Joe's may want to consider locating in the higher income areas of Hennepin County, seeing as how there is a location within close proximity to the high income location in northern Ramsey County.

Hot Spots - Population

Figure 3: Trader Joe's hot spots based off total population

The result of the hot spot analysis based off of total population (figure 3) is displayed in the same manner as the previous hot spot map. For this map, however, population is represented where the lowest populations are represented by bright yellow and the highest populations are represented by bright red. Most of western Hennepin County has the lowest populations out the entire study area. The most populated areas are in eastern Hennepin County around Minneapolis and in the lower part of Ramsey County around St. Paul. Based on this map alone, Trader Joe's may want to consider adding a location within the heart of the highly populated region perhaps somewhere between Minneapolis and St. Paul. 

Optimal Location (Mean Center)

Figure 4: Trader Joe's optimal store location 

The result of the optimal location analysis based off of customer data (figure 4) is displayed as a neon pink circle and is located just west of Minneapolis in Hennepin County. Since this is the geographic mean center of all of Trader Joe's customers in this region, Trader Joe's may want to consider adding a store in this location or very close to it.  

Customer Prospecting

Figure 5: Trader Joe's ideal customer areas

The result of the customer prospecting analysis (figure 5) is displayed as a 5-class choropleth map where the best ranking is represented as bright red and the worst ranking is represented as bright yellow. The two best areas fall within the Golden Valley, Edina, Minnetonka, and Eden Prairie circle, the third best area includes St. Paul and west of St. Paul, and the least best area is in northern Ramsey County. There are already two locations within the third and fifth best areas, and the other three locations are located in close proximity to the first and second best areas. Based of this map, Trader Joe's may want to consider looking at an area slightly southwest of the first best area, perhaps in or near Eden Prairie.

The Three Potential Sites

Figure 6: Potential Trader Joe's store locations

Looking at all of the previous results together, three locations were chosen as potential sites for a new store, represent on the map in figure 6 as yellow stars. Site 1 is located in Eden Prairie (figure 7). Site 2 is located in Golden Valley (figure 8). Site 3 is located in Long Lake (figure 9).

Figure 7: Eden Prairie location

   Figure 8: Golden Valley location

Figure 9: Long Lake location

Once the cities were decided upon, choosing a specific site location was based on where an empty lot could be found in an area where other retail is located and is within close proximity to high traffic flow, such as a major highway.





Rank Markets

Figure 10: Ranking table

After the ranking analysis was ran, the results for site locations 1, 2, and 3 were ranked in that same order, respectively (figure 10). Site 1 (Eden Prairie) had the highest numbers in all categories except for median household income where it was ranked second among all sites. Site 2 (Golden Valley) had the second highest numbers in all categories except for median household income where it ranked last among all sites, just behind site 1. Site 3 (Long Lake) by far had the lowest numbers in all categories except for median household income where it ranked first among all sites by a large margin.

Assignment 3: Real Estate Analysis

Presented by

Andrew Jeffers

Jack Mielke

Michael Lewis

Address: 330 Roosevelt Avenue

Image 1: 330 Roosevelt Ave as seen from Wilson St

This house is located at 330 Roosevelt Avenue in Eau Claire, WI (Image 1). According to Zillow.com, the house is currently priced at $209,900. This ranch-style home has 4 bedrooms, 2.5 bathrooms, is 3,718 square feet, a large basement, and an attached two car garage. It is conveniently located on a corner lot one block off of State St and is within close proximity to Putnam Park, Clairemont Avenue, Water Street, and downtown Eau Claire. The lot size is a large 12,800 square feet, and as of 2016, net property taxes totaled $4,666.74.

Comparable Homes

Other Houses for Sale in the Area

Table 1: Comparing other houses for sale

Table 1 shows this house compared to other houses in the area that are for sale. With the exception of the two outliers on Oakwood and Marston, 330 Roosevelt has the most square feet (3718)  of any house and also the cheapest prices per square foot ($56) which is well below the average amount of $94.90. It also has among the most bedrooms with four. 

Corner Lots

Table 2: Comparing other houses on nearby corner lots

Table 2 shows this house compared to other nearby houses on corner lots within one block of State Street. It has the largest lot with 12,800 square feet and the lowest price per square foot ($3.42) which falls below the average of $3.67. It also has very low tax per square foot ($0.36) which is below the average of $0.47.

The Third Ward

Figure 1: Eau Claire neighborhoods

Figure 2: The Third Ward

 The house is located in the Third Ward Neighborhood in Eau Claire (Figure 1). The Third Ward is a unique neighborhood that offers a variety of benefits to its residents (Figure 2). The neighborhood is centrally located so that it is close to downtown Eau Claire, parks, and services. Many of the houses have a historic architecture that is not resembled by any other neighborhoods in the city. The neighborhood is within walking distance to the University of Wisconsin-Eau Claire, which provides the neighborhood with ample amounts of events and amenities such as close bus routes and a respectable educational institution nearby.  Putnam Park is a 230-acre park that is located along the east and south sides of the Third Ward. This park offers the ability to walk along trails and enjoy many different types of animals and plants. It is not common that a neighborhood in the middle of a city has the benefit of a park nearby where residents can enjoy the peace that is associated with the park. Along with having the park nearby, the neighborhood is also close to the Chippewa River.  The river has parks along its banks that are within walking distance of the neighborhood and there are also spots where you can walk right up to the river.  The Third Ward also has Demmler Community Garden.  This garden allows families and individuals to buy plots and plant what they want in the garden.  The garden helps to keep the neighborhood looking nice and adds to the green spaces that help give the neighborhood its uniqueness.

Third Ward Neighborhood Association

Most neighborhoods in the city have their own neighborhood assocation. The Third Ward is no exception and arguably has the best association in the city. The association meets every second Wednesday of the month and has strict regualations on what is and is not permitted in the Third Ward. This group not only protects the ideals of the Third Ward but also protects property values. The group maintains a level of expectation that keeps the Third Ward being known as an upscale neighborhood. The regulation topics that they discuss are as follows:

• Sanitation - All trash, recycling, and yard waste must be disposed of in a clean and visually appealing manner
• Parking - Limit on how long you can park in the street and requirements for parking on driveways (not on grass or dirt)
• Building Upkeep - Owners are required to keep their home in a visually appealing state, including repainting and updating homes

Schools

Figure 3: Drive time for Manz Elementary

 There are many schools in the area that service the Eau Claire area.  For this property, the three schools are Manz Elementary, Delong Middle, and Memorial High.  These schools get a rating from GreatSchools.org, a third party that evaluates schools based on test scores.  This evaluation is used to help judge the quality of education in the surrounding area.

       Figure 3 shows the drive times from Manz Elementary School.  Our house is on the border of the 4-minute and 6-minute range making the drive to this school about 5 minutes.  Manz Elementary has a rating of 6 out of 10 according to GreatSchools.org. 

Figure 4: Drive time for DeLong Middle

  Figure 4 shows the drive times for Delong Middle School. Our house is in the 12-minute range.  Out of the three schools, Delong has the longest drive time from 330 Roosevelt Ave. Delong Middle School has a rating of 4 out of 10 according to GreatSchools.org.  

Figure 5: Drive time for Memorial High

 Figure 5 shows the drive times from Memorial High School. The house is on the border of the 4-minute and 6-minute ranges making the drive about 5 minutes. Memorial High has a 7 out of 10 rating according to GreatSchools.org. Having a quality high school so close to the house is a great benefit.

Our Price - $220,000

Based on our house and all of the factors associated with it, we came to a final price of $220,000.

There are other houses in the area that have a lot less square footage and are priced higher than our house's Zillow price of $209,900. It is in a great neighborhood and close to downtown Eau Claire which is a nice feature.  It does not appear that much work has been done to the house over the years which is why we did not price it higher.  

Sources

"Schools in Eau Claire," http://www.greatschools.org/search/search.page?q=eau+claire

"Third Ward Neighborhood," http://thirdward.org/

"2015 Comprehensive Plan," last modified September 22, 2015, http://www.ci.eau-claire.wi.us/departments/community-development/planning/comprehensive-plan.

"330 Roosevelt Ave, Eau Claire, WI 54701," last modified March 21, 2017, https://www.zillow.com/homes/330-Roosevelt-Ave,-Eau-Claire,-WI-54701_rb/

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

Executive Summary

Purpose and methods of this report

     Two friends who own two different coffee and doughnut shops in San Francisco, CA want to maximize their trade areas in a way that will benefit both businesses, but they also do not want to compete against one another. The purposes of this report are to:

• Recommend ways that each store can maximize their trade areas while avoiding competition between one another
• Produce four maps that show the following in each:

1. Location of each store, their customers, and the mean center of customers for each store
2. Location of the store's competitors (other coffee and doughnut shops)
3. Customer derived trade areas for each store
4. Driving and walking distances for each store

    Using ESRI Business Analyst, a number of analyses will be conducted including:

• Geocoding each store's location who's data is in .txt format 
• Geocoding customer addresses which is available in tabular form, assigning which customers go to which store, and finding the mean center of customers for each store
• Identifying where the store's competitors are located 
• Creating customer derived trade areas and drive time areas of each store
• Generate reports on the customer derived trade areas that contain community profile data and retail goods and services expenditures data 

Introduction

Two friends who own two different coffee and doughnut shops in San Francisco, CA want to maximize their trade areas in a way that will benefit both businesses; they also do not want to compete against each other. Both stores will provide the addresses of their respective customers along the with addresses of their stores. Both store owners want four separate maps that illustrate where customers are located and the customer's mean location of each store, the locations of each store's competitors, customer derived trade areas for each store, and driving/walking distances for each store since most of their customers walk to their shops. Using the generated maps and the data generated from the trade area report containing community profile data and retail goods and services data, recommendations will be made to the two store owners on how to maximize their trade areas in a beneficial way while also not competing against one another. Several questions must be answered in order to assist with making the proper recommendations including:

1. What is the market like for both stores?
2. Are the stores competing for the same customers?
3. Is one store in a better position compared to the other?
4. What about similar competitors?
5. Who are their customers?  

The extent of this study and the analyses associated with it were kept within San Francisco County, CA and did not include any data outside of the county. Customer address data provided by the store owners may only represent a portion of their entire customer base depending on if customers are willing to provide their addresses.

Conclusions

Answers to questions from the introduction

What is the market like for both stores? Who are their customers?

•  Store 1: Store 1 has a lower population of about 128,000 people with a dense trade area. There are a large number of households within the area where the per capita income is at a higher $63,851. The trade area has a younger population where about 65% of those who are ages 25 and older has a Bachelor's Degree or a Graduate/Professional Degree. The employed population 16 and older (~88,000 people) have mostly White Collar jobs. The population is made up mostly of young, successful, hard-working singles who are open to new experiences and places. The average amount of money spent on food outside of the home is $4,849.73.

• Store 2: Store 2 has a higher population of about 160,000 people with a trade area that is not quite as dense as compared to store 1. There are a lower number of households within the area where the per capita income is at a lower $45,149. The trade area has a slightly older population where about 48% of those who are ages 25 and older has a Bachelor's Degree or a Graduate/Professional Degree. The employed population 16 and older (~94,000 people) have mostly White Collar jobs. The population is made up of many young, successful, hard-working singles who are open to new experiences and places and prosperous married couples who are ambitious, hard-working, and like to shop. The average amount of money spent on food outside of the home is $4,970.79.

Are the stores competing for the same customers? 

Based on figure 3 which shows the trade areas of each store, the stores do not appear to be competing for the same customers since the trade areas do not overlap. However, there are many customers who travel to the store that is farther away from their homes, which may mean that both stores are then competing for these customers.

Is one store in a better position than another?

Looking at the location of competing stores in figure 2, it would appear that store 2 is in a much better position compared to store 1. Store 1 is located in an area where there is a high density of coffee and doughnut shops while store 2 has a much lower density of coffee and doughnut shops within its trade area. 

While the per capita income is much lower in store 2's trade area, the population spends a slightly higher amount of money on food outside of the home. 

What about similar competitors?

There is a highly dense amount of competitors in the northeastern part of San Francisco County, where the density lowers towards the south and western part of the county. Since there seems to be an overabundance of coffee and doughnut shops in the northeastern area, one might benefit from opening a shop towards the southwestern part of the county.

Recommendations

• Attempt to expand the trade areas slightly to the south and west for store 1 and slightly to the north and west for store 2 by perhaps advertising towards those areas since competitors are much fewer in the western area of the county.
• Be sure to market appropriately based on the people that make up each existing trade area

Findings and Discussion

The findings of this report will include presenting the maps and explaining the geographic information they provide. It will also include discussing some of the data provided by the trade area reports.

Maps

Map 1: Customers and Their Mean Centers

Figure 1: Map of each store's customers
and their mean centers

Figure 1 shows where each store's customers are located and the mean center of the locations of each store's customers. The location of the two stores are represented by the red square box with the coffee mug in the middle of the square, and each store is identified as either '1' (the northernmost store) or '2' (the southernmost store). The stores are represented as such in all the maps generated for this report. The customers of store 1 are represented by the small, circular green dots while the customers of store 2 are represent by the small, circular blue dots. While it appears most of the customers go to the store that is closest to their location, there are some outliers where some customers are going to the store that is farther away from their location. Each store's customers are clustered around each store location, and spread out the further away it becomes from the store. The mean center identifies the geographic center for a set of features (in this case, the customer locations). The mean center for store 1 is located just southwest of store 1 and is represented by the larger, green circle with the black dot in the middle; the mean center for store 2 is located just north of store 2 and is represented by the larger, light blue circle with the white dot in the middle. This suggests that, for each store, more customers are coming from areas in the center of the county (represented by the thick black line around the county in this and subsequent maps) as opposed to the outer regions.

Map 2: Competitors

Figure 2: Map of  the competitors of the stores

Figure 2 shows the locations of the competitors of stores 1 and 2. Competitors were defined as a type of business associated with 'Coffee Shop' and 'Doughnut'. Since any of these businesses could potentially be a competitor to either stores 1 or 2 regardless of location, they are lumped into one main category of competitors. The competitors are represented as yellow with black outlined X's. It is plain to see that there is an uneven distribution of competitors within the county where they are highly clustered in the northeast area of the county and are clustered much closer to store 1 than store 2. In fact, it is impossible to count by glancing at it just how many competing locations there are since their symbols overlap each other to a high extent. Around store 2, the density of competing locations is much less compared to store 1. There are very few competitors in the southernmost and westernmost areas of San Francisco County.



Map 3: Customer Derived Trade Areas

Figure 3: Map showing the customer derived
trade areas of each store

Figure 3 illustrates the customer derived trade areas of each store. These trade areas are areas around stores that represent the number of customers that are within each area. For this report, three rings were produced around each store where, starting from the location of the store, the yellow rings represents 40% of the customer base, the red ring represents 60% of the customer base, and the purple ring represents 80% of the customer base. The trade area for store 1 is much smaller compared to that of store 2, showing that the majority of the customer base of store 1 are located much closer to store one compared to the customer base of store 2. The trade areas do not overlap at any point. In fact, the closest they get to each other is about one mile. This indicates that there is room to expand each store's trade area while remaining free from competing against one another.



Map 4: Drive and Walk Distances

Figure 4: Map showing the driving and walking
distances of customers

Figure 4 illustrates the driving and walking distances of the customers for each store. They are represented in a similar fashion to the customer derived trade areas of Figure 3. There are three rings around each store location that increase in distance away from the store. Starting from the location of each store, the yellow rings represent a distance of 0.5 miles, the red rings represent a distance of 1 mile, and the purple rings represent a distance of 1.5 miles. The sizes of the drive/walk areas of each store are similar, but the shapes are different. Store 1's areas are more square shaped while store 2's areas take on more of what could be described as rough, circular shapes. This suggests that the streets and other paths surrounding each store's location are constructed and laid out differently. The drive/walk areas do not come close to crossing each other where the closest point of overlap is about 1.5 miles.





Analysis of the trade area reports

Community Profile: Store 1

Profiles were generated for the 40%, 60%, and 80% population areas. Answers given below will be for the 80% area since this represents the majority of the customer base for store 1. In each category, data was provided for the years 2010, 2016, and 2021. Answers below will be for the year 2016 since that is the most current data.

• Total Population: 128,927
• Households: 68,940
• Per Capita Income: $63,851
• Median Age: 37.3
• Population 25+ by Educational Attainment (111,627 people): 39.4% have a Bachelor's Degree while 26% have a Graduate/Professional Degree
• Civilian Population 16+ in Labor Force: 95.8% employed
• Employed Population 16+ by Occupation: White Collar jobs (professional, sales, etc.) make up 80.7% out of a total population of 87,921 people

The top 3 tapestry segments are:

1. Laptops and Lattes
2. Trendsetters
3. Metro Renters

This includes people that are:

• Young, successful singles in the city
• Intelligent and hard-working
• Urban denizens who are partial to city life
• Internet dependent
• Adventurous and open to new experiences and places

Community Profile: Store 2

Profiles were generated for the 40%, 60%, and 80% population areas. Answers given below will be for the 80% area since this represents the majority of the customer base for store 2. In each category, data was provided for the years 2010, 2016, and 2021. Answers below will be for the year 2016 since that is the most current data. 

• Total Population: 160,365
• Households: 57,087
• Per Capita Income: $45,149
• Median Age: 40.7
• Population 25+ by Educational Attainment (122,384 people): 28% have a Bachelor's Degree while 20.2% have a Graduate/Professional Degree
• Civilian Population 16+ in Labor Force: 94.5% employed
• Employed Population 16+ by Occupation: White Collar jobs make up 66.3% out of a total population of 93,665 people

The top 3 tapestry segments are:

1. Laptops and Lattes (these people are described in the previous section)
2. Pacific Heights
3. Urban Chic

Pacific Heights and Urban Chic include people that are:

• Prosperous married couples living in older suburban enclaves, many with older children
• Ambitious and hard-working
• A more diverse population
• Financially responsible, but still indulge in casino gambling and lotto tickets
• Serious shoppers that appreciate quality and bargains
• Active in fitness pursuits
• Top market for premium movie channels like HBO and Starz

Retail Goods and Services Expenditures: Store 1

Profiles were generated for the 40%, 60%, and 80% population areas. Answers given below will be for the 80% area since this represents the majority of the customer base for store 1. In each category, data was provided for the years 2016 and 2021. Answers below will be for the year 2016 since that is the most current data. 

When it comes to spending money on food away from home, the average amount spent is $4,849.73.

Retail Goods and Services Expenditures: Store 2

Profiles were generated for the 40%, 60%, and 80% population areas. Answers given below will be for the 80% area since this represents the majority of the customer base for store 2. In each category, data was provided for the years 2016 and 2021. Answers below will be for the year 2016 since that is the most current data.

When it comes to spending money on food away from home, the average amount spent is $4,970.79.


Sources

ESRI tapestry segments information: http://doc.arcgis.com/en/esri-demographics/data/tapestry-segmentation.htm

Assignment 1: Population Dynamics

Executive Summary

Purpose and method of this report

Recently, an opportunity has presented itself for a large amount of money to be invested in a new business in Jacksonville, Florida. The purposes of this report are to:

• Determine the age, population, and industry dynamics of Jacksonville compared to the state of Florida and the U.S.
• Make recommendations of what type of business to invest in based on these findings

Using U.S. Census data, this report will include:

1. A population pyramid - shows age and sex dynamics of a population
2. Dependency ratio - compares the youth and elderly populations to the working population
3. Location quotients - is a measure of geographical concentration of a variable in a region compared to another region

These findings will assist in making the appropriate recommendations for what type of business to invest in.

Findings and conclusions

Recommendations for what type of business to invest in

Introduction

An opportunity has arisen for investing a large amount of money into a new business in Jacksonville, Florida. However, it is not certain as to what type of business this money should be invested in. A number of population dynamics come into play here including:

• A growing population of young children
• A large population of retirees
• A surge in Hispanic populations

There are also some service sector dynamics that must be looked at. Using data from the U.S. Census website, these population and service sector dynamics will be analyzed comparing Jacksonville to the entire state of Florida and the United States as a whole. After analyzing these areas, this report will help in answering the question, "What type of business should be invested in in Jacksonville, Florida?"

Conclusions

Recommendations

Findings and Discussion

Figure 1: Jacksonville, FL population pyramid

Population Pyramid

Jacksonville, FL has a total population of 1,401,600 people. Looking at the population pyramid of this city (Figure 1) will allow for analyzing which age group and sex that would be ideal for the potential business. There is a fairly equal ratio of males to females across the board, so the business could be gender neutral. However, the age dynamics are more varied. Currently only about 12% of the total population of Jacksonville are elderly people ages 70 and above. Children 19 and under make up approximately 25% of the population. The largest group, as can be visually seen by the "bulge" on either side of the graph in the middle of the age cohorts, belongs to young adults from 20 years of age, to older adults up to age 54.

Dependency Ratio

Figure 2: Dependency ratio of Florida

With a dependency ratio of 55.04 (refer to figure 2), which is quite high, it can be concluded that Florida has large amount of people that are either under 15 or older than 64 compared to those that fall between these ages. Since Florida is a popular retirement location, this ratio may be influenced by the number of retirees residing in this state. However, there could also be a higher population of children under 15 years old. 

Location Quotients

to be continued...