Monitoring and improving Greek banking services using Bayesian Networks: An analysis of mystery shopping data

Mystery shopping is a well known marketing technique used by companies and marketing analysts to measure quality of service, and gather information about products and services. In this article, we analyse data from mystery shopping surveys via Bayesian Networks in order to examine and evaluate the quality of service offered by the loan departments of Greek Banks. We use mystery shopping visits to collect information about loan products and services and, by this way, evaluate the customer satisfaction and plan improvement strategies that will assist banks to reach their internal standards. Bayesian Networks not only provide a pictorial representation of the dependence structure between the characteristics of interest but also allow to evaluate, interpret and understand the effects of possible improvement strategies.

► We use Bayesian Networks (BNs) to analyse data gathered from mystery shoppers’ report.
► We evaluate the quality of service offered by the loan departments of Greek Banks.
► The key factors that influence global satisfaction are identified via BNs.
► Using BNs real time results regarding the effect improvement action are obtained.