Abstract: The disclosed embodiments illustrate methods and systems for processing customer data to predict behavioral characteristics of a customer in a physical store. The method includes receiving customer data, pertaining to a shopping episode, of the customer from one or more sensing devices. The method further includes segmenting the shopping episode into one or more segments of time durations. The method further includes categorizing each of the one or more segments of time durations into one of an in-aisle category and a non-aisle category. The method further includes identifying hand-related actions of the customer based on the received customer data. The method further includes determining a likelihood of occurrence of an action-related category based on at least the identified one or more hand-related actions. The method further includes predicting the behavioral characteristics of the customer based on at least the determined likelihood of occurrence of the action-related category.