Neuro-Affective Customer Analytics in Fashion Retail: A Model for Emotion-Driven Product Design and Marketing Strategy
Abstract
Responsible customer analytics to address emotion-driven behavior has become the cornerstone of fashion retail. In this paper, we draw our attention to the integration of a neuro- affective model, as a conceptual framework which aims to align its product design and marketing strategy to consumer emotions. Acknowledging the complexity of this dynamic context, this study applies an empirical research design drawing on comparative case studies of customer analytics initiatives in fashion organizations. Afterwards, we focus on the interaction between affective analytics practices and strategic design strategies to create a cohesive narrative around their products and consumer experience. The parametric survival method is used to test the hypotheses proposed. In order to do so, we adopted a mixed-method approach to explore how the fashion retailers systematically employed forms of sentiment analysis to capture emotions and predict purchasing outcomes. The findings add to the literatures on consumer analytics and emotion- driven marketing in retail organizations by uncovering the significance of affective responses, its predictive value, and its managerial implications. In comparing the baseline and extended models, the results show significantly stronger effects on the customer journey in the route “emotion– design–purchase” for the fashion sector. This study builds evidence that neuro-affective initiatives can foster innovation and contribute to the development of an adaptive capability for product design via customer analytics. We conclude the article with suggestions for managerial practice around the alignment between analytics, design practices and marketing practices.