Predicting customer poachability from locomotion intelligence

ABSTRACTBusinesses constantly seek out customers who are open to testing competitor offerings. While prior research mostly studies consumer surveys and within-store transactions to identify such customers, the current paper analyzes Third-Party mobile phone data to illustrate the role of environmental factors in changes to their physical competitor visit patterns. In this paper, we analyze GPS data of user movement between stores belonging to Limited-Service Restaurants (NAICS code: 722513) to identify states where customers are more likely to visit competitor stores. Utilizing Association Rule Mining, we compare Texas and Michigan, and show that the expansion and contraction of repertoire of competitor visits relates to the weather. As weather gets colder from September to December, travel inertia sets in and people visit fewer competitor stores, but the extent of the decline varies across states and brands.