In this article we propose an approach to study the effect of consumer-specific information on (complete) rank ordered preference data by means of Bradley-Terry type models. The main idea is to transform the ranking data into paired comparison data, which can be modelled within the Generalised Linear Model framework by means of a log-linear model for a corresponding contingency table. Therefore, standard software can be used to estimate model parameters and a goodness-of-fit can be assessed in the usual way. This approach allows to simultaneously estimate object-specific parameters which, in the marketing context, can be interpreted as attractions of the analysed objects, as well as subject-object interaction parameters that represent the effects of consumer-specific variables on the attractions. The interaction parameters offer a statistically motivated approach for customer segmentation and market targeting. The outlined methodology is applied to preference judgements within a local daily newspaper market. It is shown that certain socio-economic characteristics of the consumers have significant influences on their preference structures.