Automatic Construction of Conjoint Attributes and Levels from Online Customer Reviews

Conjoint analysis continues to be an area of active research due to its enormous (and often delivered) promise of improved marketing decision-making. However, despite much methodological progress, the literature has remained curiously silent on a fundamental design question: "How does one choose the attributes and levels in the first place?" In this paper, we present a method to support conjoint study design by automatically eliciting an initial set of attributes and levels from online customer reviews. While existing computer science research aims to learn attributes from reviews, our approach is uniquely motivated by the conjoint study design challenge: how to identify both attributes and their associated levels. Our proposed method has at least three advantages. First, we generate attributes and levels using the language of the consumer rather than that of designers and manufacturers. Second, the approach runs automatically. Automated analysis supports the trend towards shorter product lifecycles and rapid prototyping. Third, we support rather than supplant managerial judgment. The method is parameterized to allow survey designers to vary the number of attributes and/or levels that are generated. Managers can choose to use our method either in a stand-alone manner or as a point of departure for the surveys and focus groups used in common practice.

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