Evolving segments of online clothing buyers: an emerging market study

Abstract

Purpose While marketers want to drive higher repurchases for better business sustainability, repeat shopping experiences may change customer perceptions of the online channel, resulting in the emergence of new segment typologies. Therefore, the purpose of this paper is to explore the segmentation of online clothing shoppers using a repeat online clothing shopper base. Further, it analyses segment positions in a perceptual space to derive relevant positioning insights for the various segments. Design/methodology/approach Segmentation is done using dual bases of e-lifestyle and website quality factors for which the scales are derived from literature and then adapted and validated using a two-phase process across two samples of 271 and 644 experienced shoppers, respectively, in India. Positions of the segments are explored using the discriminant analysis-based perceptual mapping technique. Findings Three segments are found, namely disengaged averse online shoppers, interactive convenience seekers and adept online shopping optimists with the latter two having a higher propensity to purchase clothes online. Perceptual mapping of the segment positions reveals dimensions, which can be used for appropriate positioning. Research limitations/implications The research methodology may be replicated for other products and country contexts, and additional factors may be explored for further insights. Practical implications The study reveals insights on the evolving nature of segments as shoppers gain experience of online shopping for clothes and highlights the varied reasons for the growing acceptability of the online channel. The findings reveal key targeting and positioning strategies for e-marketers. Originality/value This is one of the first studies of its kind in India, which explores the segmentation of repeat online clothing shoppers in India using dual bases. Another distinctive feature of the study is its use of the perceptual mapping technique to draw inferences about factors that differentiate multi-segment buying behavior.