Interaction Data Detection System to Upgrade Brick and Mortar Shops: Metrics Allow Offline Shops to Compete with Online Retailers

The dramatic growth in online business has had a strong impact on brick and mortar shops because of the convenience and efficiency of online transactions. Online retailers can easily predict product sales trends by analyzing the interaction data gathered when customers explore web advertisements, save product items in e-carts, and make purchases. However, in the case of brick and mortar shops, an efficient scheme to assist retailers in obtaining useful information to predict product sales trends is absent. This study introduces a system based on radio-frequency identification (RFID) to help offline retailers detect and analyze the interaction data between customers and products during the sales process. In particular, the interest degree of a product (IDP) can be quantified based on the detected interaction data. If retailers determined that an item is popular with a high IDP value, they can stock more of it and advertise or recommend relevant information via displays in their shops to enhance the sales volume; otherwise, they can organize clearance sales to decrease the probability of overstocking. We tested our prototype, the interaction data detection system (IDDS), in two brick and mortar shops for two months. The results of this prototype test are presented in this article, along with a brief comparison between the proposed IDDS and conventional interaction tracking systems.