Customer Repurchase Intention Prediction - A Case Study of a Shopping Mall

• Main Authors: CHIANG, YUNG-TAO, 姜詠韜
• Other Authors: JWO,JUNG-SING
• Format: Others
• Language: zh-TW
• Published: 2019
• Online Access: http://ndltd.ncl.edu.tw/handle/7eb4ne

碩士 === 東海大學 === 數位創新碩士學位學程 === 107 === The retail business is highly competitive. To promote sale revenues, the online and offline service integration has become a newly strategic trend. In recent years, consumers have been enjoyed with online e-commerce which provides the convenience of online shopping. Yet, consumers are still paying their attention to and enjoy those offline activities and shopping experiences. Therefore, to deliver the right promotion channel and to target the right customers are the key to success in offline business. In this paper, we use the big data and modeling techniques to analyze the operation of a shopping mall as a case study in Taiwan. On the basis of the annual sales and business activities, we can explore the repurchase intentions through customers’ behavior and their transactional activities. We also establish a predictive model by using data, including custom members’ behavior, purchase records, store environment information, etc. From the related data, a return custom member list can be generated for the marketing promotion target. The store managers of the Shopping mall who is targeting to maximize revenue or profit can make their decision by using this model to generate a list of its target customers. This could lead the shopping mall to achieve its pre-set goals for their business goal.