Visual Comparison of Customer Stickiness in Retail Stores

Abstract

Understanding market trends and forming competitive promotion strategies has always been a major task of retail store managers. One big challenge is the lack of effiective tools for in-depth customer behavior analysis. In this paper, we apply visual analytics techniques to address the challenge, which is built up on the emerging and mobile location big data. We present a system that focuses on the analysis of customer stickiness which represents customers' affinity to retail stores. The system integrates mobile data pre-processing, customer stickiness analysis, multi-view visualization, and a set of interactions. The visual analytics techniques are mainly designed for two types of user tasks: 1) understanding the spatio-temporal distribution of customer traces related to retail stores; 2) evaluating the performance and trend of multiple retail stores through visual comparison. We have demonstrated the effiectiveness of the system through two case studies including advertisement placement and business branch reconfiguration.