CUSTOMER BASE ANALYSIS - AN INDUSTRIAL PURCHASE PROCESS APPLICATION

customer base analysis is concerned with using the observed past Purch ase behavior of customers to understand their current and likely futur e purchase patterns. More specifically, as developed in Schmittlein et al. (1987), customer base analysis uses data on the frequency, timing , and dollar value of each customer's past purchases to infer the numb er of customers currently active, how that number has changed over tim e, which individual customers are most likely still active, how much l onger each is likely to remain an active customer, and how many purcha ses can be expected from each during any future time period of interes t. In this paper we empirically validate the model proposed by Schmitt lein et al. In doing so, we provide one of the few applications of sto chastic models to industrial purchase processes and industrial marketi ng decisions. Besides showing that the model does capture key aspects of the purchase process, we also present a more effective parameter es timation method and some results regarding sampling properties of the parameter estimates. Finally, we extend the model to explicitly incorp orate dollar volume of past purchases. Our results indicate that this kind of customer base analysis can be both effective in predicting pur chase patterns and in generating insights into how key customer groups differ. The link of both these benefits to industrial marketing decis ion making is also discussed.