Interest degree of products analysis by RFID technology for offline shops marketing optimization

With the booming of e-commerce, salerooms of online shops have affected the offline shops marketing severely. It requires a smart system to help dealers to predict the products sale trend, so as to save cost for their entity business. In this paper, we propose an interactions data detection system based on RFID technology. The customers' behavior information reflected by Received Signal Strength Indicator (RSSI) and time duration when they compare and select products is recorded in the Cloud Platform Server (CPS) for analyzing product sale trend. Furthermore, we have defined the IDP value based on detected interactions data. By practical experiments, the IDP is shown to have same variations associated with practical sales. Therefore, for a product with a high IDP value, dealers can advertise or recommend relevant information of such a product via displays at the shops to increase its sales volume.