標題: Customer Purchase Behavior Prediction from Payment Datasets
作者: Wen, Yu-Ting
Yeh, Pei-Wen
Tsai, Tzu-Hao
Peng, Wen-Chih
Shuai, Hong-Han
交大名義發表
National Chiao Tung University
關鍵字: financial technology;real time advertising;customer behavior prediction
公開日期: 1-Jan-2018
摘要: With the advances in the development of mobile payments, a huge amount of payment data are collected by banks. User payment data offer a good dataset to depict customer behavior patterns. A comprehensive understanding of customers' purchase behavior is crucial to developing good marketing strategies, which may trigger much greater purchase amounts. For example, by exploring customer behavior patterns, given a target store, a set of potential customers is able to be identified. In other words, personalized campaigns at the right time and in the right place can be treated as the last stage of consumption. Here we propose a probability graphical model that exploits the payment data to discover customer purchase behavior in the spatial, temporal, payment amount and product category aspects, named STPC-PGM. As a result, the mobility behavior of an individual user could be predicted with a probabilistic graphical model that accounts for all aspects of each customer's relationship with the payment platform. To achieve real time advertising, we then develop an online framework that efficiently computes the prediction results. Our experiment results show that STPC-PGM is effective in discovering customers' profiling features, and outperforms the state-of-the-art methods in purchase behavior prediction. In addition, the prediction results are being deployed in the marketing of real-world credit card users, and have presented a significant growth in the advertising conversion rate.
URI: http://dx.doi.org/10.1145/3159652.3159707
http://hdl.handle.net/11536/150987
DOI: 10.1145/3159652.3159707
期刊: WSDM'18: PROCEEDINGS OF THE ELEVENTH ACM INTERNATIONAL CONFERENCE ON WEB SEARCH AND DATA MINING
起始頁: 628
結束頁: 636
Appears in Collections:Conferences Paper