Understanding the service experience of the banking industry: A data mining approach
Abstract
The purpose of this research is to investigate the banking Service Experience (SE) using text mining, in order to propose management improvements based on the customer's perspective. The data was provided by a bank in Chile & contains structured & unstructured information in text format, collected through a Net Promoter Score (NPS) survey. The methodology used to process data was 6-step Cross Industry Standard Process for Data Mining (CRISP-DM) model (Chapman et al., 2000). An analysis framework is applied to process the customer feedback data, which combines the previous work carried out by Ordenes et al., (2014); McColl-Kennedy et al., (2019) called ARC (Activities, Resources & Context) expanded because it includes Interactions & Client’s role. This research seeks to provide empirical evidence in relation to the application of the ARC model in a different industry, such as banking, which would help to determine key factors that would help improve management in terms of (1) contact points, (2) elements of value creation, (3) emotions, (4) cognitive responses, (5) escape intention.Keywords:
Text mining, Service experience, Customer Journey, Churn intent, Contact point, Activities, Resources, ContextReferences
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