Segmentation of Mobile Banking Users Based on Expectations: A Clustering Technique

The increasing trend of mobile phone owners reveals the importance of mobile banking on these days. Understanding the user's expectations helps banks to increase the market share. The aim of this study is to segment mobile banking users based on expectations. In this study, Agriculture bank of Iran is selected as the case study. Based on a mixed approach of type qualitative → quantitative, mobile banking user's expectations were identified within 4 main expectation as: expectations of the main services, added service, facilitating conditions for using and perceived usefulness for using mobile banking. Data has been collected from 308 users of mobile banking through the closed questionnaire. In the next step, after determining the optimal number of clusters by Ward method, data mining technique of K-Means has been used for clustering. Based on Anova test applied on identified expectations, the results showed that the average of expectations between clusters is different because the significance level of this expectations was lower than 0.001.