Understanding user’ behavior in food delivery applications is crucial for enhancing user experiences and driving business growth. However, existing user segmentation models from web and e-commerce domains may not fully capture the unique patterns in mobile food delivery applications. This paper proposes the EBAI (Explorers, Bargain Hunters, Abandonists, Impulse Buyers) conceptual model as a novel approach to segment users based on their clickstream behavior. We apply the model to a large-scale, real-world dataset from Jahez™, a leading food delivery application in the Middle East. User actions are transformed into behavioral features tailored to each hypothesized segment. K-means clustering is then used to uncover distinct user groups within each segment. The resulting segments provide valuable insights, validating some of the hypothesized behaviors while also revealing unexpected patterns. Our findings highlight the importance of developing domain-specific segmentation conceptual models. The EBAI conceptual model offers a foundation for understanding food delivery application users, with implications for personalization, user interface design, and marketing strategies.