Study Areas, Geocoding, Customers, and Trade Areas

Introduction

Two coffee shop owners in San Francisco are very interested in maximizing their trade areas while benefiting both businesses and not competing.  In order to solve this spatial task I used Business Analyst 2015, as well as ArcMap and several tools in the ArcToolbox.  The stores and respective customers were geocoded and put onto a map of San Francisco.  Competitors were also mapped as well as trade areas and drive times. Four maps were made to help solve this spatial problem. 

Defining a Study Area, Geocoding, and Mean Centers

The first step in the process of figuring out a solution is to define a study area.  Confining your data to a specific area can greatly reduce the processing time of Business Analyst and makes things more simple in general.  The county used for the study area was San Francisco county, California.  The next step was to use the ArcToolbox to find the mean center of customers for both stores.  Figure 1 was the first map created and it shows the two coffee shops, their respective customers, and the mean centers for each set of customers.  Both mean centers seem to be pulling inwards towards the center of the county. Figure 2 is the same map, it just also has other coffee and donut shops on it for the purpose of mapping competitors.  A lot of competitors are clustered in the Northeast part of the county. Store 1 (northernmost store) is the closest to the cluster of competition, meaning it could possibly have an effect on business for store 1 but not store 2.      

Figure 1

Figure 2

Customer Derived Trade Areas and Drive Times

After completing the first two maps, a second pair of maps was created were the drive time areas for each shop.  Figure 3 shows the drive times for the coffee shops.  On Figure 3, the first circle represents a half mile away, the second red circle represents a mile away, and the third blue circle represents one and half miles away.  If you look at figure 3 you will notice that store 1 in the north dips into the highly competitive area with several other coffee/doughnut shops.  Store 2 has no where near the same competition that store 1 is facing.  Figure 4 shows the customer derived trade areas for San Francisco.  The first circle contains up to 40% of the store's customers, the second red circle contains up to 60%, and the final blue circle contains up to 80% of the customers for the store.  Store 2 has a much wider reach compared to store 1. 

Figure 3

Figure 4

Results and Conclusion

When making connections from the results, we can see that store 2 in the south has much less competition to deal with than store 1.  It may be a good idea for store 1 to relocate to the southwest to remove itself from the intense competition in the northeast.  The mean center for store 1 is even pulling to the southwest.  It also may be a good idea for store 2 to move north slightly to accommodate for the mean center.  There are already far too many coffee and doughnut shops in the northeast.  In order to benefit both businesses, I believe it is in the best interest of store 1 to move southwest and for store 2 to move slightly north.  This will take some pressure off as store 1 is ridding itself of competition, and store 2 is simply adjusting for its respective customers.