Reorientation, the process of regaining one’s bearings after becoming lost, requires identification of a spatial context (context recognition) and recovery of heading direction within that context (heading retrieval). We previously showed that these processes rely on the use of features and geometry, respectively. Here, we examine reorientation behavior in a task that creates contextual ambiguity over a long timescale to demonstrate that mice learn to combine both featural and geometric cues to recover heading with experience. At the neural level, most CA1 neurons persistently align to geometry, and this alignment predicts heading behavior. However, a small subset of cells shows feature-sensitive place field remapping, which serves to predict context. Efficient heading retrieval and context recognition require integration of featural and geometric information in the active network through rate changes. These data illustrate how context recognition and heading retrieval are coded in CA1 and how these processes change with experience.