RFM and CLV: Using Iso-Value Curves for Customer Base Analysis

RFM and CLV: Using Iso-value Curves for Customer Base Analysis We present a new model that links the well-known RFM (recency, frequency, monetary value) paradigm with customer lifetime value (CLV). While previous researchers have connected the two conceptually, none has presented a formal model that requires nothing more than RFM inputs to make specific lifetime value projections for a set of customers. Key to this analysis is the notion of “iso-value” curves, which enable us to group together individual customers who have different behavioral histories but similar future valuations. Iso-value curves make it easy to visualize and summarize the main interactions and tradeoffs among the RFM measures and CLV. Our stochastic model, featuring a Pareto/NBD framework to capture the flow of transactions over time and a gamma-gamma sub-model for dollars per transaction, reveals a number of subtle but important non-linear associations that would be missed by relying on observed data alone. We conduct a number of holdout tests to demonstrate the validity of the model’s underlying components, and then focus on our iso-value analysis to estimate the net present value for a large group of customers of the online music site, CDNOW. We summarize a number of substantive insights and point out a set of broader issues and opportunities in applying such a model in actual practice. Keywords: customer lifetime value, CLV, RFM, customer base analysis, Pareto/NBD