Personalization through co-creation: Segmenting customers by expectations and willingness to pay.

Abstract

In an era defined by hyper-connectivity and data-driven decision-making, understanding the nuanced preferences of customers is essential for developing effective segmentation strategies. Drawing on a quantitative dataset of 202 survey responses and framed by Customer-Dominant Logic (CDL) and configuration theory, the study applies exploratory factor analysis and K-means clustering to explore six distinct customer segments. Each cluster reveals a unique combination of cognitive, economic, hedonic, utilitarian, and uniqueness-seeking value orientations, highlighting the heterogeneity of customers and their perceptions of personalized experiences. The findings challenge the sufficiency of demographic segmentation and demonstrate that willingness to pay (WTP) is shaped more by perceived personalization value and contextual factors than income or frequency of travel. This study contributes to the literature by offering a novel customer typology that supports more ethically grounded and strategically targeted personalization and pricing practices. It also provides actionable insights for managers seeking to implement dynamic, data-driven segmentation strategies that enhance customer satisfaction and profitability.