基于MaxDiff和潜在类别分析的移动支付客户细分研究

Research on Customer Segmentation of Mobile Payment Based on MaxDiff and Latent Class Analysis

在竞争激烈的移动支付市场中,对客户进行细分尤为重要。从客户的心理、态度等角度出发,首先采用MaxDiff调查方法测量受访者对移动支付产品的偏好,从而得到MaxDiff数据,再利用潜在类别分析对客户进行分类得到每个细分群体在各个对象上的偏好得分,最后从人口统计学和行为特征方面对细分群体进行验证分析。研究结果显示:客户被分成3个细分群体,分别是"安全和场景"类、"优惠和便捷"类以及"功能和速度"类,它们在移动支付的偏好上有显著差异。这样的细分结果可为移动支付服务商实施精准营销提供决策参考。

Customer segmentation is a particularly important thing in the fiercely competitive market of mobile payment. From the psychology and attitude of the customer, firstly MaxDiff data are obtained by MaxDiff survey method to measure the respondents＇ preferences for mobile payment products. Then Latent Class Analysis （LCA） is used to classify customers and the preference score of each segmentation group on all items can be obtained. Finally each segmentation group will be verified from the aspects of demographic and behavioral characteristics. The results showed that the customers are divided into three segmentation groups, which are ＇safety and scene＇, ＇discount and convenient＇ and ＇function and speed＇ respectively, and there are significant differences on mobile payment preference between them. In a result, segmentation group can provide decision-making consultation for the precision marketing of the mobile payment service providers.