In the context of mobile health applications usability is a crucial factor to achieve user acceptance. The successful user interface (UI) design requires a deep understanding of the needs and requirements of the targeted audience. This paper explores the application of the K-Means algorithm on smartphone usage data in order to offer Human Computer Interaction (HCI) specialists a better insight into their user group. Two different feature space representations are introduced and used to identify persona like stereotypes in a real world data set, which was obtained from a public available smartphone application.