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.