Article
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Online Review Analysis from a Customer Behavior Observation Perspective for Product Development
Version 1
: Received: 24 March 2024 / Approved: 25 March 2024 / Online: 25 March 2024 (08:18:31 CET)
A peer-reviewed article of this Preprint also exists.
Lee, Y.U.; Chung, S.H.; Park, J.Y. Online Review Analysis from a Customer Behavior Observation Perspective for Product Development. Sustainability 2024, 16, 3550. Lee, Y.U.; Chung, S.H.; Park, J.Y. Online Review Analysis from a Customer Behavior Observation Perspective for Product Development. Sustainability 2024, 16, 3550.
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 in 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 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. Through empirical data analysis, we validated that indirect observation based on customer reviews can be performed more efficiently than traditional methods. Additionally, we observed that the customer behavior VOC (Voice of Customer) identified during the CJM mapping process offers unique insights that are distinct from traditional product feature-centric review analyses. To verify the usefulness of these behavior VOC, we evaluated the quantitative analysis results of the same reviews through product development experts. Experts recognized these customer behavior VOC as useful information for developing new products.
Keywords
online review analysis; customer journey map; customer observation; text mining; customer behavior
Subject
Business, Economics and Management, Business and Management
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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