Counting your customers: who are they and what will they do next?
Management Science
Rational shopping behavior and the option value of variable pricing
Management Science
Customer Referral Management: Optimal Reward Programs
Marketing Science
Consumer Addressability and Customized Pricing
Marketing Science
Consumer Learning, Brand Loyalty, and Competition
Marketing Science
A Dynamic Changepoint Model for New Product Sales Forecasting
Marketing Science
Modeling Browsing Behavior at Multiple Websites
Marketing Science
The Effects of Free Sample Promotions on Incremental Brand Sales
Marketing Science
Brand Loyalty Programs: Are They Shams?
Marketing Science
Optimizing the Marketing Interventions Mix in Intermediate-Term CRM
Marketing Science
Measuring and Mitigating the Costs of Stockouts
Management Science
Measuring and Mitigating the Costs of Stockouts
Management Science
Online customer identification based on Bayesian model of interpurchase times and recency
International Journal of Systems Science
Measuring and prioritising value of mobile phone usage
International Journal of Mobile Communications
Exploring customer perceived value in mobile phone services
International Journal of Mobile Communications
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We extend the Schmittlein et al. model (1987) of customer lifetime value to include satisfaction. Customer purchases are modeled as Poisson events, and their rates of occurrence depend on the satisfaction of the most recent purchase encounter. Customers purchase at a higher rate when they are satisfied than when they are dissatisfied. A closed-form formula is derived for predicting total expected dollar spending from a customer base over a time period (0, T]. This formula reveals that approximating the mixture arrival processes by a single aggregate Poisson process can systematically underestimate the total number of purchases and revenue. Interestingly, the total revenue is increasing and convex in satisfaction. If the cost is sufficiently convex, our model reveals that the aggregate model leads to an overinvestment in customer satisfaction. The model is further extended to include three other benefits of customer satisfaction: (1) satisfied customers are likely to spend more per trip on average than dissatisfied customers, (2) satisfied customers are less likely to leave the customer base than dissatisfied customers, and (3) previously satisfied customers can be more (or less) likely to be satisfied in the current visit than previously dissatisfied customers. We show that all the main results carry through to these general settings.