Beyond customer experience models: identifying idiosyncratic perceptions

Purpose: The purpose of this paper is to demonstrate that a deeper analysis of customer experience (CE) can identify idiosyncratic and critical perceptions in the experiences of groups of customers. Design/methodology/approach: The methodology that the authors used is made of three main steps: segmentation analysis, profiling and identification of idiosyncratic clusters’ profiles (i.e. those with a CE perception different respect to the whole sample) and among these idiosyncratic clusters, identification of those that may be critical for the business. Findings: The authors identified clusters of customers showing significant differences in their perceived experience with respect to the holistic CE model. Nevertheless, a sample of bank managers assessed three cluster profiles among them to be critical signals a company. The identification of these idiosyncratic patterns provides managers with interesting additional insights that would be hidden in a holistic CE model. Practical implications: Managers can gain valuable insights of CE from this analysis that should be added to those coming from an holistic CE model. Originality/value: This paper contributes to the scientific research in that it extends the knowledge about CE by showing how personal factors can be identified and how drawing additional managerial insights.