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

  • Authors:
  • Claudia Tarantola;Paola Vicard;Ioannis Ntzoufras

  • Affiliations:
  • Department of Economics and Quantitative Methods, University of Pavia, Italy;Department of Economics, University Roma Tre, Italy;Department of Statistics, Athens University of Economics and Business, Italy

  • Venue:
  • Expert Systems with Applications: An International Journal
  • Year:
  • 2012

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Abstract

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.