This project uses ML and GIS data to identify optimal location for Migros Supermarkets in the Canton of Zurich (Switzerland)
Made by dr Matteo Jucker Riva, data scientist and location specialist, [email protected] #---------------
Disclaimer: I have no affiliation with Migros and this analysis was not requested by Migros AG. All the data used is publicly available
See the detailed description here: https://matteo-jriva.medium.com/location-intelligence-the-branch-network-optimization-problem-4aa4740088d8
See the results here: https://www.google.com/maps/d/u/0/edit?mid=1_uX0U2V-byD1GLv0KRuWC2Gxv2wRuNT7&usp=sharing
Download the input data from here: https://www.dropbox.com/s/ifvp73nkzupzycg/input_geo_data_rasterFormat.zip?dl=0
Location intelligence is the process of deriving meaningful insight from geospatial data relationships to solve a particular business problem.
This projects addresses a particular problem for retail stores, called "Branch Network optimisation". In this type of analysis, geospatial data are used to determine optimal location for retail branches in order to improve spatial coverage and fill gaps in the branch network.
Here we will try to identify geospatial features that drive the loication of Migros Supermarket locations within the canton of Zurich, and feed this information to a machine learning model in order to identify additional promising locations for addtional branches