🧭 Optimizing Retail Store Locations to Better Serve Customers
Where should we Open new retail stores to better serve customers? Location-Allocation is a spatial decision-making tool used to identify the most strategic places to position new facilities (like stores, hospitals, schools) so they can serve demand efficiently.
In this project, my objective as a route optimization data analyst was to select the best store locations among several candidates in order to maximize customer access to retail services.
To achieve this, I used the Location-Allocation solver in ArcGIS Pro. This tool analyzes the relationship between demand points (population) and candidate facilities (stores), using real travel times on the road network. I applied a common retail scenario: customers tend to shop at the nearest store, and typically won't travel more than 5 minutes to do so.
The analysis first identified 3 stores that can serve the highest number of customers among 208 demand zones. It also revealed areas where people remain beyond the 5-minute accessibility threshold — valuable insights for strategic future expansion.
The analysis was then extended to simulate store expansion and market competition:
A required facility (existing store) was added to optimally locate 2 additional stores to maximize coverage.
Competing stores were introduced, and a Huff gravity model was applied to estimate customer probabilities and maximize market share.
Finally, a target market share scenario determined that a total of 10 stores (including the required facility) would be needed to reach 70% market share, considering competition.
This project demonstrates how spatial data analysis can guide smarter business decisions: ➡️ Choosing optimal investment locations ➡️ Maximizing market reach and attendance ➡️ Improving fair access to services
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