Consumer behaviour holds special importance in the retail industry. Consumer location impacts consumer behaviour by dictating purchase trends. This paper investigates the problem of examining product sales across a chain of stores to extract the geographic regions that characterize a product. Characterizing region for a product is a coherent geographic region where the consumers actively consume the said product. We introduce DICE, a diffusion-based technique to uncover all such regions for a given product, when they exist. In contrast to current state of the art, DICE involves minimal usage of parameters and shows remarkable tolerance to noise. We present experiments conducted on real datasets from a general commercial supermarket in France. Empirical evaluation and user-studies establish that the presented method significantly outperforms its natural baseline and previous state of the art approaches.