Estimating Clv Using Aggregated Data : the Tuscan Lifestyles Case Revisited

The Tuscan Lifestyles case (Mason 2003) offers a simple twist on the standard view of how to value a newly acquired customer, highlighting how standard retention-based approaches to the calculation of expected CLV are useless in a noncontractual setting. Using the data presented in the case, it is a simple exercise to compute an estimate of expected five-year CLV. However, if we wish to arrive at an estimate of CLV that includes the customer's life beyond five years or are interested in, say, sorting out the purchasing process (while alive) from the attrition process, we need to use a formal model of buying behavior. To tackle this problem, we utilize the Pareto/NBD model developed by Schmittlein, Morrison and Colombo (1987). However, existing analytical results do not allow us to estimate the model parameters using the data summaries presented in the case. We therefore derive an expression that enables us to do this. The resulting parameter estimates and subsequent calculations offer useful insights that could not have been obtained without the formal model. For instance, we were able to decompose the lifetime value into four factors, namely purchasing while active, dropout, surge in sales in the first year and monetary value of the average purchase. We observed a kind of triple jeopardy in that the more valuable cohort proved to be better on the three most critical factors