Traditional choice-based conjoint methods are based on an unrealistically rational model of consumer decision-making. These methods work accurately only if we assume that consumers can process all the information given to them, weigh it up and make a calculated, accurate decision. Modern discoveries in behavioural economics make it clear that these assumptions are incorrect. To accurately understand consumers’ decisions and preferences, conjoint methods must be updated to include behavioural understanding. This paper presents five ways in which this can be done: rank-finding conjoint, goal-attribute conjoint, intangible-attribute conjoint, algorithmic conjoint and contextual conjoint. Each of these extensions to the standard conjoint method can explore a specific aspect of the decision-maker’s psychology, and together they result in a much deeper and more accurate reading of consumer behaviour and desires.
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