Using text-mining-assisted analysis to examine the applicability of unstructured data in the context of customer complaint management

Abstract

In quest of gaining a more holistic picture of customer experiences, many companies are starting to consider textual data due to the richer insights on customer experience touch points it can provide. Meanwhile, recent trends point towards an emerging integration of customer relationship management and customer experience management and thereby availability of additional sources of textual data. Using text-mining-assisted analysis, this study demonstrates the practicality of the arising opportunity with means of perceived justice theory in the context of customer complaint management. The study shows that customers value interpersonal aspects most as part of the overall complaint handling process. The results link the individual factors in a sequence of ‘courtesy → interactional justice → satisfaction with complaint handling’, followed by behavioural outcomes. Academic and managerial implications are discussed.