Dynamic segmentation of financial markets: a mixture latent class Markov approach

The topic of market segmentation is still one of the most pervasive in marketing. Among clustering techniques, finite mixture models have gained recognition as a method of segmentation with several advantages over traditional methods; one variant of finite mixture models, the latent class model is probably the most popular. The latent class approach is innovative and flexible and can provide suitable solutions to several problems regarding the development of marketing strategies, because it takes into account specific features of the data, such as their scale of measure (often ordinal or categorical, rather than continuous), their hierarchical structure and their longitudinal component. Dynamic segmentation is of key importance in many markets where it is unrealistic to assume stationary segments due to the dynamics in consumers’ needs and product choices. In this paper, a mixture latent class Markov model is proposed to dynamically segment Italian households with reference to financial products ownership. Studying portfolio compositions of households gives valuable information about different management styles and what influences them. It is shown that different groups of households exhibit different financial strategies; moreover, some households are not stable over time since ownership varies between stages of the product life cycle and between households, depending on family characteristics and life cycle.