Uncovering Psychographic Segments in Indonesia’s Modest-Fashion Market Using VALS and K‑Means Clustering

Abstract

Background: The Muslim fashion industry in Indonesia continues to expand rapidly, reflecting the dynamic intersection between cultural values and global-style trends. However, many small and medium-sized enterprises (SMEs) still rely on conventional demographic segmentation, focusing on age, income, and marital status, while neglecting the deeper psychographic elements that drive purchasing behavior. Consequently, marketing initiatives often fail to capture consumers’ emotional and motivational dimensions, leading to suboptimal engagement and brand differentiation.
Purpose: This study aims to uncover psychographic segments among Indonesian modest-fashion consumers by analyzing their lifestyle orientations and motivational patterns. The objective is to provide SMEs with sharper evidence-based insights that enable the creation of more targeted, emotionally resonant, and culturally aligned marketing strategies.
Design/methodology/approach: A structured survey was conducted among 450 Indonesian Muslim women. Applying the VALS framework, three core psychographic dimensions social status-driven, experience-seeking, and religiously motivated were identified and further analyzed through K-Means clustering. Statistical validation using ANOVA and silhouette analysis confirmed the robustness and internal consistency of the segmentation results.
Findings/Result: The analysis revealed three well-defined consumer clusters: social status-driven (32%), experience-seeking (52%), and Religiously Motivated (16%). Although these groups shared similar demographic profiles, their underlying motivations and purchasing behaviors differed markedly, highlighting the limitations of demographic segmentation.
Conclusion: Psychographic segmentation provides a richer and more actionable understanding of consumer diversity in Indonesia’s modest fashion market, enabling SMEs to design marketing strategies that align with their values, aspirations, and lifestyles.
Originality/value (State of the art): This study offers one of the first applications of the VALS framework integrated with machine learning clustering within a Muslim-majority context. This produces data-driven insights that bridge theory and practice to enhance SME competitiveness and market performance.

Keywords:   marketing strategy, psychographic segmentation, Modest fashion, VALS, K-Means Clustering