在服務業中,化妝品業將實質的產品與無形的服務銷售給顧客,因此,顧客便成為化妝品業的重心,然而透過顧客關係管理可以將產品與服務在最適合的時間(Time)、以最適合的管道(Deliver Channel)、把最適合的商品(Products)與服務(Service)、提供給最適合的顧客(Customers);本研究以類神經中的自組織映射圖網路與統計的集群分析方法,將顧客的基本資料及消費記錄做為顧客分群的輸入因子,透過兩種分群方法,比較其優異,以提供化妝品業在不同顧客分群中,針對不同需求的顧客區隔進行不同的行銷活動,以利化妝品業降低成本、提高利潤的目的。
Customer satisfaction is always the most important factor in cosmetics business. To keep and develop a long-term relationship with customers, a cosmetics vendor should not only provide a valuable product but also thoughtful service. Through customer relationship management (CRM), we can provide the right products and services at the right time with the right deliver channel to the right customers. In this research, we propose a method that utilizes an artificial neural network and a statistic cluster method to distinguish customers based on their purchasing behavior. With the method, different segment results can be generated for cosmetics vendors to target potential customers with the right promotional activities. Our experiment shows that cosmetics vendors are expected to increase profit significantly.