Introduction
Two coffee and doughnut shops in San Francisco are
interested in working together to maximize their trade area. Both coffee shops are located within close
proximity to one another; therefore have customers within the same general
area. In order to maximize their trade areas, each coffee shop needs a basic
understanding of their customers and competitors. Both coffee shops must recognize where their
customers are located as well as the overall walking distance of their
customers in order to establish a customer derived trade area. It is also
important to understand who their customers are in regards to various
demographics. Furthermore both coffee shops need to determine the location of
their competitors in the area. Through a spatial understanding of various
aspects in regards to their customers and surrounding competitors, both coffee
shops can generate a plan to maximize their trade area.
Methods
In order to begin establish a spatial understanding of the
customers and competitors of both coffee shops, a study area must be defined. Defining
a study area of around San Francisco allows for the necessary data to be
displayed within a central focus. After a study area is defined then then each
stores location and their customers can be geocoded. Geocoding allows for
specific point data to be located then displayed in a spatial representation,
in this case both store locations and their customers. Once each store is
plotted along with their combined customers, it is necessary to separate the
customers based on which specific coffee shop they go to. Assigning customers
to their respective store is necessary in order to establish the mean center
for each store’s customers. The mean center determines the central point for
each stores customer’s location displaying whether or not each store has more customers
in specific direction. The result from these processes produces a spatial
representation of the San Francisco area displaying each stores location, the
location where each set of their customers comes from, as well as the mean
centers of each set of customers (Figure 1. Coffee Shop Customers).
In addition to displaying the points of individual customers
for each store and determining both mean centers, it is also necessary to
establish a customer derived trade area for each store. The trade area for each
store is created through a business analyst tool which produces a trade area
represented by three rings. The first ring surrounding each store sets an area
enclosing 40 percent of each store’s customers; the second ring encloses 60
percent, while the third encloses 80 percent. The spatial representation
produced from this process illustrates the surrounding area where 80 percent of
each store’s customers are located. (Figure 1. Customer Trade Area)
Furthermore, while creating the customer trade area for each
store using business analyst, reports regarding community profile and retail
goods and service expenditures were generated. These reports provide data
concerning the population of the individuals located within each coffee shops
customer derived trade area. Using these reports in combination with the
spatial representation of the customer trade area not only determines where
current and prospective customers are located, but also provides useful
demographics regarding those customers.
Not only is it important to determine the general location
where majority of each store’s customers are located, but it is also important
to determine the general walking distance for each stores respective
customers. The walking distance
representation is created through the same business analyst tool used to
establish the customer trade area, and is also displayed by three rings. The
first ring surrounds 0.5 miles around each store, the second ring 1.0 mile, and
the third 1.5 miles. Considering most customers walk to their designated store,
it is important to produce a spatial representation that shows the distance
that majority of the customers have to travel to each store (Figure 1. Customer
Walking Distance).
The last spatial representation again displays the location
of each store as well as the location of various coffee shop competitors
(Figure 1. Coffee Shop Competitors). In
this map, the same San Francisco study area was used and the same points were
plotted for each coffee shop. The locations for the store’s competitors where
plotted through the business analyst tool, add business listing, and searching
for the other coffee and doughnut shops.
Conclusions
The spatial representation, Coffee Shop Customers, show the
mean centers for each store to be located at almost the same point of the
stores themselves, meaning there is a fairly even distribution of customers
surrounding both stores. Even though the mean centers appear to be fairly
central to each stores location, it is evident that each mean center has been
pulled towards the other store’s location. Thus, each store has a considerable
amount of customers that come from the location between the two stores.
The spatial representation, Customer Trade Area, also
indicates that a considerable amount of customers for each store are located in
the area between the two stores. The rings which enclose various percentages of
customers extend fairly evenly around each store, reflecting the same even
distribution of customers as the mean centers. The customer trade areas, like
the mean centers, indicated each store’s customers surround their respective
store fairly evenly from all directions; however also show there are
considerably more customers in the area between the two stores. The ring
enclosing 80 percent of the customers for each store appear to extend toward
the one another, meaning each store has a respectable amount of customers in
the direction of the opposite store.
The spatial representation, Customer Walking Distance, when
compared to the customer trade area spatial representation show that
approximately 40 percent of the customers for each store come from a distance
of one mile or less. Therefore, 40 percent of the customers for each shop are
is close proximity to their respective coffee shop. However, when comparing the
area containing 60 to 80 percent of each store’s customer is appears that these
customers over a mile to their respective coffee shop. Although 40 percent of
each coffee shop’s customer come from less than a mile away, the other 60 percent
travel more than a mile, likely coming from the direction of the opposite store
as the mean centers and customer trade areas indicated.
The spatial representation, Coffee Shop Competitors,
indicates that majority of the competitors of the two coffee shops are located
in the north east. The coffee shop located close to the north east area where
majority of the competitors is located has a smaller trade area than the other
coffee shop. Because there are more competitors located near this store
majority of its customers come from close by. The other store has a much larger
trade area, with customers coming from longer distances, because there are far
less competing coffee shops surrounding this store.
In addition to the spatial representations which provide
information regarding where each stores customers come from, the reports
generated in business analyst offer data establishing who each store’s
customers are. The community profile report states that within the area
encompassing 80 percent of the customers for both stores have a total
population of 138,511. Of the population of individuals in that area 26.7
percent of them are between the ages of 25 and 34, and there are 2,400 men than
women. The area has an average annual income of $96,083 and in regards to race
59.2 percent of this area is white, and 22.8 percent Asian being the next most
predominant race. The service expenditure report stated that within this area
the average annual amount spent on food away from home, with a likely portion
spent at coffee and doughnut shops, is $4,469.
Recommendations
Focusing on the
customers directly between both stores would be the most effective way to
maximize the trade area. A considerable amount of customers for each store is
located in between both stores, and even as far as next to the opposite store.
By addressing these customers both stores can work to maximize and possibly
even expand their trade areas in the direction toward one another. The populations
surrounding the stores, which consist of 80 percent of each store’s customers, are
primarily young adults ages 25 to 34. This area is also predominantly white;
however has a significant Asian population of over 20 percent. In addition to
focuses on the area between both stores, it may also be beneficial to focus on
these particular demographics.
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