Online Review Analysis from a Customer Behavior Observation Perspective for Product Development

Yeong Un Lee, Seung Hyun Chung and Joon Young Park ()
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Yeong Un Lee: Department of Industrial and Systems Engineering, Dongguk University, 30, Pildong-ro 1-gil, Seoul 04620, Republic of Korea
Seung Hyun Chung: Department of Industrial and Systems Engineering, Dongguk University, 30, Pildong-ro 1-gil, Seoul 04620, Republic of Korea
Joon Young Park: Department of Industrial and Systems Engineering, Dongguk University, 30, Pildong-ro 1-gil, Seoul 04620, Republic of Korea

Sustainability, 2024, vol. 16, issue 9, 1-18

Abstract: Observing customers is one of the methods to uncover their needs. By closely observing how customers use products, we can indirectly experience their interactions and gain a deep understanding of their feelings and preferences. Through this process, companies can design new products that have the potential to succeed on the market. However, traditional methods of customer observation are time-consuming and labor-intensive. In this study, we propose a method that leverages the analysis of online customer reviews as a substitute for direct customer observations. By correlating a customer journey map (CJM) with online reviews, this research establishes a verb-centric analysis that produces a CJM based on online review data. Various text analysis techniques were utilized in this process. When applying online retail site review data, our method of customer observation required one week. This proved to be more efficient in comparison with traditional customer observation methods, which typically need at least one month to complete. Additionally, we observed that the customer behavior-based VOC (voice of customer) identified during the CJM mapping process offers broad insights that are distinct from traditional product feature-centric review analyses. This behavior VOC can be effectively utilized for product improvement, new product development, and product marketing. To verify the usefulness of the behavior VOC, we asked product development experts to evaluate the quantitative analysis results of the same reviews. The experts evaluated the CJM as useful for product conceptualization and selecting technology priorities.

Keywords: online review analysis; customer journey map; customer observation; text mining; customer behavior (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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