The authors present a new model that links the well-known RFM (recency, frequency, and monetary value) paradigm with customer lifetime value (CLV). Although previous researchers have made a conceptual link, none has presented a formal model with a well-grounded behavioral “story.” Key to this analysis is the notion of “iso-value” curves, which enable the grouping of individual customers who have different purchasing histories but similar future valuations. Iso-value curves make it easy to visualize the interactions and trade-offs among the RFM measures and CLV. The stochastic model is based on the Pareto/NBD framework to capture the flow of transactions over time and a gamma-gamma submodel for spend per transaction

Loyalty programs lead to a natural split of a firm's customer base into members and nonmembers. To manage both groups effectively, it is essential to know how marketing activities, such as promotions, affect both groups' contributions to revenues. The authors model each group's contribution as the number of daily buyers times their average expenditures. The model also includes the number of nonbuyers because they may return as customers. Moreover, nonbuyers may influence the expenditures of other customers through crowding effects, and they use personnel time

The authors develop a general parametric modeling framework for bidding behavior in Internet auctions. Toward this end, they incorporate four key components of the bidding process under their framework: whether people bid on an auction, (if so) who bids, when they bid, and how much they bid over the entire sequence of bids in an auction. This integrated framework is based on a single, latent, time-varying construct of consumer willingness to bid, which bidders have and update for a particular auction item over the course of the auction duration