Trader Joe's Site Selection
Introduction
Site selection is one of the most important tools for a business to use when it comes to reaching their target market and surviving similar competitors. When it comes to field of geography, the technology available today to research site selection is extremely advanced and can be very advantageous to those skilled with using these tools. This lab I was given data for six Trader Joe's stores in Minnesota and the data for customers associated with those stores. The study area was specifically Hennepin and Ramsey counties. The goal of this lab was to familiarize ourselves with the tools tied to site selection in business analyst, as well as locate an ideal location for a new Trader Joe's store. The main tools used in the following lab were market penetration, mean center of consumers, locating ideal customers, and using rank sites to rank our three proposed sites.
Methods
(This exercise used Business Analyst 2015 for site location, Microsoft Excel for geocoding purposes, and Google Maps to locate proposed sites)
Market Penetration (Figure 1)
The first analysis I completed was the market penetration report. Market penetration divides the total number of customers by the total number of people in each geographically defined area, in this case it was zip-codes. This gives a percentage to see how well the market is being penetrated in each zip code. This is done by going to the Analyst Wizard menu and choosing market analysis and then market penetration. The geography level was set to zip codes and the customer data we were given was divided by the business analyst base data to give us an output showing market penetration for Trader Joe's in Hennepin and Ramsey counties.
Mean Center / Optimal Location (Figure 2)
Calculating the optimal location analysis is a relatively simple analysis and shows the exact middle of all the given consumers. I did this by going to Analysis Wizard, selecting Find Optimal Store Locations (Mean Center). I then specified my customer and store data and ran the analysis. A single point representing the optimal store location was given in the output, representing the most convenient location for a new Trader Joe's based on the customers' locations.
Locating Ideal Customers (Figure 3)
This analysis involves choosing variables for customer prospecting to find areas that match a user-defined criteria. This was also done through the analysis Wizard, except this analysis was slightly more open-ended and up to me to choose the best variables to identify ideal locations. The variables I chose were an income of at least forty thousand dollars and a population of people aged 24-29 greater than 4,000. To pick this criteria I needed to manually filter variables, find the two desired variables, and set a "floor" or "ceiling" value. I did not need ceiling values and set the floor value of income to $40,000 and the floor for population of 24-29 aged people to 4,000. Again, this geography level was set at zip-codes. I then clicked finish and completed the analysis to receive an output.
Proposing sites (Figure 4)
The next step in the process of site selection for Trader Joe's was to analyze the previous outputs (customer prospecting, mean center, and market penetration) to propose three potential sites for a new Trader Joe's store. After viewing my maps, I arrived at the three locations below(in blue). Satellite imagery was also used through Google Maps/Google Earth to make sure the proposed sites were not already occupied. These three locations were then put into an excel file, saved as an excel workbook, and added that data to ArcMap for geocoding. After geocoding the three addresses, they were ready to be analyzed by "Rank Similar Sites".
2909 Hazelwood St, Maplewood MN 55109
900 Sibley St. NE, Minneapolis MN 55413
4747 Lakeland Ave N, Minneapolis MN 55429
Ranking Similar Sites (Figure 5)
After geocoding the three proposed sites, it was time to run the analysis tool to rank similar sites and find which proposed site is the most ideal location for an new Trader Joe's store. To do this, I went to the analysis wizard and chose my proposed sites for the data with a buffer distance of 1.5 miles. The four variables used in this analysis were 2015 Total Population, 2015 Median Household Income, Ind:Avg Spent per Week by HH at Food Stores $150, and Shopped at grocery store/6 mo: Trader Joe's. After completing the analysis, the top ranked site was 4747 Lakeland Ave N, followed by 2909 Hazelwood St, and finally 900 Sibley St. NE.
Results
(Figure 1)
Figure one shows the market penetration for Hennepin and Ramsey counties. The darker green represents where Trader Joe's is reaching the most customers based on the total population of that zip-code. For example, Minneapolis's population has a higher proportion of customers than Maple Grove. This map shows a pattern of higher market penetration near urban sectors, especially the zip codes in and around the Twin Cities. The outer zip codes in the west have significantly less market penetration than the Twin Cities.
(Figure 2)
Figure 2 Shows a map of the mean center (spatially equivalent of mean) for all of the customers for Trader Joe's. The Mean center is also supposed to serve as the optimal location for a Trader Joe's based on the customer data. Again, the mean center pictured above is located in West Minneapolis. This analysis shows that the ideal location of a new Trader Joe's would be close to the Twin Cities area.
(Figure 3)
Figure 3 shows the ideal customers analysis. This analysis involved prospecting customers on variables chosen by me and the above output was created. Just to refresh, my variables were Households of income greater than $40,000 and population of 24-29 greater than 4,000. The geography level was set at zip codes. The above zip codes highlighted in green are the ideal zip-codes for a Trader Joe's based on my criteria. The same pattern as above is being exhibited. The ideal zip-codes are located near Minneapolis and St. Paul.
(Figure 4)
Figure 4 shows my three proposed locations. 2909 Hazelwood was chosen because it was near several shopping centers, a major highway, and several residential establishments. It was also chosen because it was in a zip-code that represented my ideal criteria for ideal customer analysis. 900 Sibley St NE was chosen because it is in the heart of Minneapolis and there is significant market penetration in that area. The mean center/optimal location was also located very close to 900 Sibley St NE. The last address I chose was 4747 Lakeland Ave N. I chose this location because it is in an area that has good market penetration, and surrounding zip codes to the NW that have potential for expansion and further market penetration of the current population in that zip code.
(Figure 5)
Figure 5 shows the analysis of Rank of Proposed Sites. The 1st ranked site was the site located at 4747 Lakeland Ave N, followed by 2909 Hazelwood St, and finally 900 Sibley St. NE. 4747 Lakeland Ave N seems like an excellent location because of its proximity to other shopping centers, residential establishments, and the market penetration in that area. The market penetration is high and there is room to expand in the zip code with less market penetration to the Northwest. Conclusion
This lab aimed to understand site selection and to familiarize me with the geographical tools associated with site selection. The tools used were a series of analyst tools through the analysis wizard in business analyst. These tools included market penetration, customer prospecting, mean center/optimal store location, as well as site ranking. After analyzing the customer and store data for Trader Joe's, I've come to the conclusion that the best location for a new Trader Joe's would be 4747 Lakeland Ave N. This is because of the potential for further market penetration in other zip codes, as well as the lack of nearby Trader Joe's in the area and proximity to the twin cities. Overall, I thought this lab was extremely educative and provided me with the fundamental knowledge of site selection. I really enjoyed this entire exercise and hope that I will be able to apply my newly acquired skills in the real world.
Sources
All data was provided by Ryan Weichelt, University of Wisconsin-Eau Claire
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