Segmentation of Local Skincare Consumers Based on Electronic Word of Mouth (e-WOM) Characteristics: A Hierarchical Cluster Analysis Approach
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The rapid development of the local skincare industry in Indonesia has encouraged changes in consumer behavior in accessing and responding to digital information, particularly through electronic word of mouth (e-WOM). This study aims to map the e-WOM characteristics of local skincare consumers based on similarities in response patterns using cluster analysis. e-WOM was measured through three dimensions—intensity, valence of opinion, and content—adapted from Goyette et al. (2010), using six statements rated on a five-point Likert scale. A descriptive quantitative survey was conducted with 73 female students at Universitas Negeri Surabaya who actively used local skincare products and had been exposed to online reviews. The instrument was valid (item-total correlations ranging from 0.610 to 0.824, exceeding the critical value of 0.229) and reliable (Cronbach's Alpha = 0.843). Data were analyzed using Hierarchical Cluster Analysis with Ward's Method and Squared Euclidean Distance. The analysis identified three e-WOM clusters: Cluster 1 (High/Active e-WOM, 49.3%), Cluster 2 (Moderate e-WOM, 46.6%), and Cluster 3 (Low/Passive e-WOM, 4.1%). These findings indicate that consumers' responses to e-WOM are heterogeneous and form distinct behavioral patterns, providing a basis for consumer segmentation and more targeted digital marketing strategies.
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