Journal of Marketing Research · 2005 · 561 citations · 23 references
Marketing AnalyticsCustomer SatisfactionConsumer UncertaintyBusiness IntelligenceDigital MarketingCustomer ProfilingRfm MeasuresConsumer ResearchBusiness AnalyticsOnline Customer BehaviorBuying BehaviorCustomer Base AnalysisManagementConsumer BehaviorCustomer Relationship ManagementMarket SegmentationStatisticsQuantitative ManagementCustomer ProfitabilityEconomicsConsumer Decision MakingCustomer RetentionGamma-gamma SubmodelCustomer Lifetime ValueMarketingCustomer LoyaltyCustomer Journey AnalysisInteractive MarketingBusinessMarketing Insights
Prior work linked RFM to CLV conceptually but lacked a formal, behaviorally grounded model; this study introduces iso‑value curves to group customers with differing purchase histories but similar future valuations and discusses broader practical implications. The authors aim to develop a formal model linking RFM to CLV using iso‑value curves. The model employs a Pareto/NBD framework for transaction flow and a gamma‑gamma submodel for spend, uses iso‑value curves to visualize RFM–CLV interactions, and is validated via holdout tests before estimating total CLV for new CDNOW customers.
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. The authors conduct several holdout tests to demonstrate the validity of the model's underlying components and then use it to estimate the total CLV for a cohort of new customers of the online music site CDNOW. Finally, the authors discuss broader issues and opportunities in the application of this model in actual practice.
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