A Study on User Technology Readiness in the Context of E-Banking Lounge Service

The primary objective of this research is to utilize smart delivery platforms' technical capabilities to identify homogeneous groups of banking customers in North India, considering their traits related to optimism, innovativeness, discomfort, and insecurity with technology-based banking services. By employing the K-means cluster analysis with the Euclidean distance algorithm, the study processed data from 1050 clients with access to self-service e-banking lounges, resulting in the formation of three distinct user clusters: pioneers, explorers, and laggards. Notably, the majority of users were classified as explorers, followed by pioneers and laggards. Age played a significant role, with older customers demonstrating resistance to automation, while younger age groups showed more inclination and demand for technological solutions. Surprisingly, technologically savvy individuals expressed higher satisfaction with automated services compared to their less tech-savvy counterparts. Intriguingly, customer experience did not directly influence cluster formation for the e-banking lounge. This innovative study represents the first attempt at utilizing cluster analysis to identify potential e-banking lounge customer segments based on technology readiness characteristics. The resulting market segmentation insights hold immense potential for creating targeted marketing plans and strategies within the banking sector, effectively leveraging the power of smart delivery platforms.