Customer Behavior Modelling Using Radio Frequency Identification Data and the Hidden Markov Model

Abstract

Developments in radio frequency identification (RFID) technology have made data on customer movement paths in supermarkets available. In this paper, we propose a method for customer behavior modeling by using RFID data and the hidden Markov model (HMM). In this method, "Stop" and "Pass by" behavior are estimated and the proposed method is evaluated by predicting the sales areas where customers actually purchased items. Using this method, we also demonstrate the shopping momentum. This effect, however, is experienced by only some customers, not all.