Investigating Purchasing Patterns for Financial Services using Markov, MTD and MTDg Models

In the past, several authors have found evidence for the existence of a priority pattern of acquisition for durable goods, as well as for financial services. Its usefulness lies in the fact that if the position of a particular customer in this acquisition sequence is known, one can predict what service will be acquired next by that customer. In this paper, we analyse purchase sequences of financial services to identify cross-selling opportunities as part of a CRM (customer relationship management). Hereby, special attention is paid to transitions, which might encourage bank- or insurance only customers to become financial services customers. We introduce the Mixture Transition Distribution model (MTD) as a parsimonious alternative to the Markov model for use in the analysis of marketing problems. An interesting extension on the MTD model is the MTDg model, which is able to represent situations where the relationship between each lag and the current state differs. We illustrate the MTD and MTDg model on acquisition sequences of customers of a major financial-services company and compare the fit of these models with that of the corresponding Markov model. Our results are in favor of the MTD and MTDg models. Therefore, the MTD as well as the MTDg transition matrices are investigated in order to reveal cross-sell opportunities. The results are of great value to the product managers as they clarify the customer flows among product groups. In some cases, the lag-specific transition matrices of the MTDg model are better for the guidance of cross-sell actions than the general transition matrix of the MTD model.