A new DSS based on situation awareness for smart commerce environments

Real time adaptation of marketing strategies and actions in smart commerce environments, such as shops and malls, is an open challenge with a tremendous impact for the survival of traditional retailers. A main issue of traditional retailers, in comparison with e-commerce shops, is that they usually rely on analysis of point-of-sales data after purchase and/or focus groups and self-reports where customers are asked about what they like or want. This techniques, even if solid grounded to marketing and consumer research, do not allow analysis of data and decision making in real time, i.e., when consumers are inside a shop. In this paper we present our results on the definition and validation of a decision support system for real time decision making on discount and promotion actions. The system makes decision on the basis of recognition and assessment of situations of interest for the consumers, modelled with heuristics related to behavioural economics results. We validated our solution in a virtual shop simulated with V-REP, demonstrating its capabilities to adapt with regards to the changes in the environments, in terms of sensors, people, products, and different situations.