1 Introduction
1.1 Purpose
of this study
In San Francisco County, CA, two friends are owners of two
separate coffee shops. Both of them want to maximize their trade areas in a way
that benefits both businesses. Under the circumstance that they do not want to compete
against one another. In order to maximize the trade areas, the competitive
market needs to be addressed. This entails looking at where the customers are
coming from, understanding the competition, and the accessibility to the coffee
shops.
1.2 Scope
of this study, sources, and methods
Both stores have provided the addresses of their respective
customers as well as the addresses to the coffee shops. One map will show where
the customers are coming from in relation to the two coffee shops based on the
geocoded addresses that were provided. The customers will be divided into those
that choose to be loyal to coffee shop 1 and coffee shop 2. Coffee shop 1 will
be addressed as the shop to the north of San Francisco County and Coffee shop 2
will be referenced as the shop to the south of the county, shown in Figure 1.
Mean centers will also be calculated for each business so see the mean area
where customers are located.
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| Figure 1. Reference map of the Coffee shops in San Francisco County. |
Another map will analyze the competition in San Francisco
County for the two coffee shops. ESRI Business Analyst provides the data for
the locations of other coffee and doughnut businesses in the area. The next map
looks at the customer derived trade areas for the two coffee shops. These areas
will assess whether the two owners will have competition against each other.
After looking at the trade areas, a final map will demonstrate the walk/drive
times to the businesses. Most of the customers walk to the coffee shops, so the
distance radius is altered to fit purpose of the map.
2 Findings and Discussion
2.1 Customers
After the addresses of each respective customer was geocoded
in Business Analyst, the distribution of customers was based on relative
location to the coffee shop. Figure 2 has a divide in the county in relation to
its customers. The Store 1 customers are closely clustered around the coffee
shop compared to Store 2 customers. Store 2 has a big more spread and more
customers that travel farther to attend Store 2. This is proven also by looking
at the mean center. The mean center of Store 1 is so tightly clustered that the
mean center symbol is touching the coffee shop symbol for Store 1. As for Store
2, the mean center is lightly farther off of Store 2. After reviewing the
locations of the locations of the respective customers, not as many live as
close to Store 2 (compared to Store 1), but the customers are coming from
longer distances. One thing to point out is that there is a few outlying
customers. Some of Store 1’s customers are mixed in the Store 2 region and vice
versa.
 |
| Figure 2. Location of Respective Customers for each Coffee Shop with the Mean Center of the customers. |
2.2 Competitors
The majority of competitors are clumped in the northeast
corner of the county, surrounding San Francisco, CA. This near the Union
Square, Financial District and South market of San Francisco. Store 1 is
approximately two miles from the center of the competitors, which can be seen
in Figure 3. However, Store 1 more susceptible to competition compared to Store
2. Store 2 only has a few other competitors around it, but none so close that
they are practically next to each other.
 |
| Figure 3. Location of the other Coffee and Doughnut Shop Competitors. |
2.3 Customer Derived Trade Areas
The trade areas were based on the customers. Figure 4
includes a multiple ring buffer around the coffee shops indicating where 40%,
60%, 80% of the customers are located for each store. The population within the
80% radii is 128,925. The largest age cohort (25-34) takes up 27.5% of that
population. Followed by 15-24 and 35-44 being the next largest cohorts. The
population that surrounds both of the businesses is mainly young adults.
 |
| Figure 4. Customer Derived Trade Areas with buffers at 40%, 60% and 80%. |
The first assumption
that can be made is that Store 2 has a larger trade area than Store 1. The customer
derived trade area is more stretched out due to the spread of customers. The
40% of Store 1 extends over 2 miles roughly. 80% of the customers need to be
reached a farther distance. Comparing this to Store 1, much of that market is
between a mile and 1.5 miles. Therefore, Store 1 does not have to go as far to
advertise its business. One thing to note is the consumer spending. In 2016,
within the 40% radius of both businesses, the average spent on food away from
home was $4,164.45 and the total amount was $62,749,905. This numbers are for
any food, but bakeries and coffee shops are included in that spending amount.
2.4 Drive/Walk Times
Considering many of the customers walk to these coffee
shops, the walk/drive distances had a multiple ring buffer at .5 miles, 1 mile,
and 1.5 miles in Figure 5. Referring back to the customer derived trade areas
in Figure 4, 80 percent of the customers were within about two miles of the
business. Taking into considering the walking routes or accessible roads within
the 1.5 mile radius, the buffers are altered to fit the specifications. The
customers for both businesses are tightly clustered around the location of the
coffee shops. Looking specifically at store 1, many of the customers fill the
.5 mile area as well as the mile radius. Store 2 has a similar pattern, but
still a significant amount of customers in the 1.5 range. Store 2 has a
customer base that is willing to travel a little farther than the customers at
Store 1.
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| Figure 5. Walk/Drive Times for each coffee shops with buffers at 0.5 miles, 1 mile, and 1.5 miles. |
3 Conclusions
The customers are willing to travel farther distances to
Store 2 more because there is less competition on the southern half of the
county. Store 1 is located closer to the central business district of San
Francisco County. That leaves the customers location being significantly
closer. With more competition around, they do not have to travel as much to get
the coffee or doughnut product. Simply, Store 2 has a widespread of customers,
while Store 1 has a more closely compacted spread of customers. It seems a
though a line could be drawn through the county that will distinguish between
customers of Store 1 and Store 2. By not having a mix within their customers,
the competition with the two businesses will not have to be an issue. Store 1 will have to take into consideration
the high concentration of competition in the northeastern part of the county,
specifically to the east of the business. For Store 1, its trade area could be
extended. There is a higher chance of customers from farther distances willing
to come to the coffee shop, but not as far as interfering with Store 1’s
customers.
4 Recommendations
After considering the findings and conclusions of this study,
the following recommendations can be made to maximize the trade area for Store
1:
- Extend the trade area to the Richmond District. A handful of customers have identified their location in the surrounding areas of the district.
- Create a promotion around the Golden Gate Park. This could attract tourists or influence anyone doing recreational activities to stop at the shop for a break.
- Maximizing the trade area east of the business will create a more competition for the San Francisco area.
- Note that the Mission District is heavily influenced by Store 2 customers to the south, and Potrero district is in the “dividing” line of the two store customers.
Based on the findings for Store 2, the following
recommendations to maximize the trade area include:
- Trade areas should be extended farther distances to a 3 to 5 mile radius around the business, as long as it does not interfere with the alterations of Store 1. Look specifically to extending it to the northeast or south east of the store.
- To attract an area that has minimal competition and not as many customers, the southwest corner of the county would be an area to advertise to people who do not have great access to coffee and doughnuts.
- Diamond Heights would be a community that would be worth extending the trade area too.
- City College of San Francisco is within the 1.5 mile buffer. Promoting a coffee shop to college students would be a great investment in the business. Many students find that coffee shops are great places to study and run on caffeine.
- Since customers are willing to travel longer distances for Store 1, San Francisco State University could be a good area to maximize the trade area.
5 Appendix
Data can be found publically in the Q:Drive of the
University of Wisconsin-Eau Claire’s server.
Retail Goods and Service Expenditures:
Community Profile: file:///Q:/StudentCoursework/RWeichelt/GEOG.352.001.2175/COONENKA/Assignment%202/Community%20Profile%20-%20Customer%20Derived%20(Modern).pdf
Data Note: The
Spending Potential Index (SPI) is household-based, and represents the amount
spent for a product or service relative to a national average of 100. Detail may
not sum to totals due to rounding. This report is not a comprehensive list of
all consumer spending variables therefore the variables in each section may not
sum to totals.
Source: Esri
forecasts for 2016 and 2021; Consumer Spending data are derived from the 2013
and 2014 Consumer Expenditure Surveys, Bureau of Labor Statistics
6 References
ESRI. 2016. "Esri Business Analyst."
