Conjoint is the leading methodology for understanding which elements of the proposition customers value and at which price points. It is an extremely powerful statistical tool that pulls out which elements of a proposition customers really value/trade off (price included), and that will influence the purchase decision, through a survey that mimics real-life shopping experiences and observes consumer choices. These shopping experiences are repeated multiple times so the shoppers’ purchase intentions can be measured at a range of price points and competitive contexts.
It offers considerable advantages over direct questioning techniques by teasing out which elements really matter to consumers, rather than taking what respondents state as being important at face value. It allows us to model any combination of features in a near-market like environment even though only a sub-set of propositions have been tested and to test scenarios that might not be present in the real market. Respondent-level data allows for subgroup analyses, consumer segments and contexts for the development of tailormade strategies for different groups of customers, channels and contexts.