Purpose – The purpose of this paper is to develop a framework for retail banks to leverage their service quality customized to the opportunities and challenges that arise within digitization.
Design/methodology/approach – In this paper the maturity of digitization of retail banks was analyzed and the lack of a holistic approach for digitization for service quality improvement was identified. Subsequently, a service quality framework was developed interrelating stateof-the-art data analytics technologies with service quality management. The framework was then validated in a German retail bank using a single case study with embedded units.
Findings – The findings emphasize that the collection and analysis of data compose an increasingly role for service quality improvement. Therefore data mining can be implemented to process customer data and enable retail banks to predict future customer journeys to provide high service quality which is a prerequisite tostrengthen customer relations.
Research limitations/implications – This research is limited to retail banks that offerservices through online and offline channels.
Practical implications – Retail banks can apply our framework to improve service quality through customer data and new technologies.
Originality/value – This paper is valuable since it offers guidance to improve service quality on an operational level tailored to the requirements of retail banks. It is the first paper thatutilizes data mining in order to proactively provide banking services to customers.
Service quality, retail banking, digitization, customer journey