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Prediction of Purchase Behaviors Based on Customer Demand Value Using Factorization Machines

Yuya Miyamoto and Michiko Tsubaki
The University of Electro-Communications, Department of Informatics, Chofu, Japan
Abstract—This study focuses on Integrated Marketing Communication which is an important factor of Customer Relationship Management. The purpose of this study is to compare the customer sales data of two different types of stores in the confectionery industry, using the framework which is “Sources of Communication Messages in a Relationship”. In addition, this study proposes the method to categorize the customer’s pursuit values for each store based on sales data. And also this paper proposes the new approach that can promote sales while increasing the value of usage in customers’ living, based on devising a method to improve the efficiency of customer direct mail delivery, using Factorization Machines. The result shows the value that customers desire in each two shops is different from not only on-site investigation but also customer sales data. Furthermore, a customer demand value is defined in this study, the customer direct mail delivery is established to combine customer demand value with the result of purchase behavior prediction using Factorization Machines, makes that the value of usage in customers’ living increase and sales promote.

Index Terms—factorization machines, customer demand value, purchase behavior, direct marketing, customer relationship management, prediction

Cite: Yuya Miyamoto and Michiko Tsubaki, "Prediction of Purchase Behaviors Based on Customer Demand Value Using Factorization Machines" Journal of Advanced Management Science, Vol. 6, No. 4, pp. 190-196, December 2018. doi: 10.18178/joams.6.4.190-196
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