An Information Stock Model of Customer Behavior in Multichannel Customer Support Services
基于美国健康保险公司的个体数据，构建模型预测客户在电话和网页渠道间的查询行为，发现电话信息增益是网页的两倍，客户可分为网页回避者和网页寻求者两类。
We develop a model to understand and predict customers’ observed multichannel behavior in a customer support setting. Using individual-level data from a U.S.-based health insurance firm, we model a customer’s query frequency and choice of using the telephone or web channel for resolving queries as a stochastic function of her latent “information stock.” The information stock is a function of the customer’s “information needs” (which arise when customers file health insurance claims) and “information gains” (which customers obtain when they resolve their queries through the telephone and web support channels), and other factors such as seasonal effects (for instance, queries that arise at the time of annual contract renewal). We find that average information gain from a telephone call is twice as much as that from visiting the web portal; customers prefer the telephone channel for health event-related information but prefer the web portal for structured seasonal information; and customers are polarized in their propensities of using the web channel and can be broadly classified into “web avoiders” and “web seekers.” Our model provides superior in-sample and out-of-sample fit than multiple benchmark models for aggregate and individual-level customer activity and has several managerial uses, such as capacity planning.