Durian is a fruit that is predominantly found in Southeast
Asia, and it is famously known for being a polarizing fruit — people either love it or hate it.
Suppose you were modelling durian ice cream using the traditional conjoint method,
and if the proportion of individuals who love the fruit is equal to the proportion who hate it,
the importance of the durian flavour for the population of respondents will be understated. This
outcome, however, would be misleading because it would suggest that the presence of durian in the
ice cream has no bearing on consumers’ preferences, which is not true. They either hate it or love
it.
Similar examples exist in most markets, for instance, mobile phones or razors or
soft drinks. Some people like small phones that fit into their pockets, others prefer larger
screens. Some individuals like more blades on their razors, other don’t. Some like more sugar,
others want less.
Aggregation clouds the individual differences in these heterogeneous markets,
leading to erroneous conclusions.
Because individual preferences differ, market models in general should be created
at the individual level. Hierarchical Bayes (HB) choice modelling provides the framework for doing so.
The HB model is called “hierarchical” because it subsumes two levels of parameter
estimates — the individual (i.e., each respondent) and the aggregate. The individual-level
parameters reflect individuals’ preferences.
This approach yields more accurate estimates of the share of preferences. The
individual-level models reveal market niches and segments that marketers can target with
differentiated products catering to the distinct needs and preferences of groups of customers.
