Customer satisfaction and natural language processing

Yolande Piris and Anne-Cécile Gay

Journal of Business Research, 2021, vol. 124, issue C, 264-271

Abstract: This study uses natural language processing in order to increase knowledge concerning customer satisfaction. A total of 12,000 customer returns were analyzed, 6,800 of which contained freely expressed qualitative feedback. Eight themes emerge from the analysis and bring to light the factors influencing satisfaction. It is also noted that satisfaction is not vertical or horizontal but can involve a more or less important combination of themes. This study also shows the link between the level of satisfaction and the number of themes addressed, thus challenging traditional approaches that do not seem to distinguish the discursive differences between satisfied and dissatisfied customers. Finally, this investigation lays the foundations for automatic and personalized processing of customer comments.

Keywords: Satisfaction; Customer experience; Customer voice; NLP; Artificial intelligence (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (7)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jbrese:v:124:y:2021:i:c:p:264-271

DOI: 10.1016/j.jbusres.2020.11.065

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