Location Analytics – Store Location Analysis

Abstract

Retail chains compete against each other in terms of reaching the customer. While companies often try to attract customers by targeting them with the right set of offers and promotions, it is imperative that they are located in an area that would best cater to the needs of the customers. Market domination comes not just by how they reach the service provided but also by how reachable they geographically are to start with. Choosing the targeted location to open a new branch can play a huge role in the success/failure of the branch. The demographic characteristics of a location play a huge role in forecasting the revenue that can be generated from a store. This total revenue can be understood to be split between different competitors that share the market space. In addition to competition from other retailers, there will be competition from the retail chain’s own branches in case there are multiple branches within the same locality. Choosing among different locations to open a new branch is a matter of comparing the expected incremental revenues at different locations given a new unit comes in that location. In this paper, we talk about how models can be built to project the possible revenue of a store. In addition, we also quantify the cannibalization caused by other stores in the proximity. Combining the expected sales with the cannibalization, we show how expected incremental sales can be used to make judgment on where to open a new store.