When managers and researchers encounter a dataset, they typically ask two key questions: (1) which model (from a candidate set) should I use? and (2) if I use a particular model, when is it going to likely work well for my business goal? This research addresses those two questions, and provides...

Customers often stockpile reward points in linear loyalty programs (i.e., programs that do not reward stockpiling) despite several economic incentives against it (e.g., the time value of money). We develop a mathematical model of redemption choice that unites three explanations for why customers...

Two widely recognized components, central to the calculation of customer value, are acquisition and retention propensities. However, while extant research has incorporated such components into different types of models, limited work has investigated the kinds of associations that may exist...

The widespread popularity and use of both the Poisson and negative binomial models for count data arises, in part, from their derivation as the number of arrivals in a given time period assuming exponenitally distributed interarrival times (without and with heterogeneity in the underlying base...

Hidden Markov Models (HMMs) have emerged as an empirical “workhorse” in the marketing literature in capturing and forecasting within-customer non-stationary behaviors. Extant research has demonstrated that HMMs typically outperform nested benchmarks when examining fit statistics aggregated...

Understanding how customers' service portfolios evolve over the course of their relationship can provide multi-service firms, such as telecommunication and financial service providers, with useful guidance for managerial issues such as customer valuation and targeting. Complicating matters,...