The influence of emotions and communication style on customer satisfaction and recommendation in a call center context: An NLP-based analysis

Thomas De Cleen, Philippe Baecke and Frank Goedertier

Journal of Business Research, 2025, vol. 189, issue C

Abstract: We study the impact of customer sentiment, agent sentiment, and emotional matching (i.e., call center agents matching emotional expressive states of customers) on satisfaction and recommendation intentions in a utilitarian service context. We methodologically contribute by text mining observed data using advanced transformer-based NLP algorithms and compare findings with those of previous survey-based research. An analysis of 25,008 call center conversations reveals that positive (vs negative) customer sentiment more strongly impacts satisfaction and recommendation. For recommendation (vs satisfaction) we observe that negative emotional expressions have a relatively stronger weight, albeit less strong than that of positive ones. We find that emotional expressions of call center agents (vs those of clients) have a smaller impact on these outcomes. Emotional matching is observed as beneficial, but not necessarily when faced with negative high-arousal emotional expressions. As conceptual grounding, we refer to theorizing around delight, formality, source credibility, emotional arousal and loss aversion.

Keywords: Call Center; Emotion; Customer Satisfaction; Net promotor score (NPS); Computational Linguistics (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:jbrese:v:189:y:2025:i:c:s0148296325000153

DOI: 10.1016/j.jbusres.2025.115192

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