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Qualitative Trajectory Calculus (QTC) offers a powerful set of tools towards selectable-granularity abstraction of relative trajectories of moving entities, while preserving essential aspects of their interaction. In this paper, we present a case study of an  application of QTC towards analysing human motion and interaction patterns in a japanese shopping mall. The ultimate purpose of this study is to use the derived results towards tuning human-aware social path planning algorithms for robots co-habitating and interacting with humans in the mall, and in other similar spaces. This is increasingly important given the rapid rise of service robots and the need for human-aware navigation maximising the safety and comfort of humans while preserving social norms such as proxemics and personal spaces.