We investigate incumbent customers' store switching behaviors following new store entry in a retail franchise setting. Using customer-level transaction and store characteristics data from a retail franchise in a major urban district, we model switching behavior using a zero-one inflated beta (ZOIB) regression with Bayesian estimation. This approach distinguishes customers who do not switch, partially switch, or completely switch to new stores. We find that new store entry generates more partial switchers than complete switchers. Among pre-entry behavioral variables, purchase frequency and purchase quantity are the strongest predictors of non-switching, suggesting the roles of travel costs and inventory optimization. Conversely, bulk purchasers are most vulnerable to complete switching, as their infrequent, large-quantity trips may imply high travel costs which a nearby new entrant may reduce. Multi-category shoppers are prone to partial switching, likely optimizing category-level purchases across stores. Among store characteristics, greater inter-store distance helps retain incumbent customers. Our findings reframe franchise encroachment as a share-of-visit or share-of-purchase problem rather than a customer-loss problem, offering franchisees a segmentation framework for targeting efforts after new store entry.