Improve Sales Forecasting with Customer Behavior Analysis

Abstract

In this paper, we explore the utility of customer behavior analysis of un-structured video data for improving sales forecasting, which is an important task for supply chain management in retail store. Specifically, we develop video-based customer behavior analysis system for monitoring and analyzing customer's shopping behavior, then extract the information about how the customers interact with the stores and products, and finally design a framework to incorporate the video-based analysis result into sales forecasting. To the best of our knowledge, this is the first work that introduces the customer behavior analysis of monitoring video data to sales forecasting task. In order to validate our observation, we conducted a series of experiments in a physical retail store and demonstrated that integrating video-based customer behavior analysis into a conventional sale forecasting model results in a performance improvement.