Extracting design knowledge from online product reviews to support design creativity

ABSTRACT

E-commerce has made customer-generated product reviews accessible for analysis. Each customer review summarizes the product's unique customer experience and features. In product development processes, it is essential to reach the information content of customer reviews early. Using customer content as data provides designers with comprehensive, cost-effective, and rapid insights into product evaluation, user experience, and even identification of new product features and creative design interventions. Despite all these superior potentials, analyzing unstructured and mass product review data takes time and effort with conventional methods. This study proposes to utilize product reviews as input for developing user experience-based products and to support designers' creativity in the early design phases. Therefore, in this study, the opinions of consumers about a product were subjected to a text mining analysis at different levels, and mood values were determined for each category and sub-product aspect with their justification. In the last part of the study, the essential product improvement areas based on the comment/sentiment score are presented, and the potential of product comments as information content about design creativity is discussed.

KEYWORDS:

• Creativity
• industrial design
• design knowledge
• online product reviews
• sentiment analysis

Disclosure statement

The anonymized user review data supporting this study's findings are available from amazon.com. All ideas and opinions about the products used within the scope of the study belong solely to the product reviewer and do not reflect the author's statement about the product.