The Past, Present and Future of Measuring Customer Satisfaction with Artificial Intelligence and Machine Learning

Huseyin Güngör
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Huseyin Güngör: University of Amsterdam Business School - University of Amsterdam Business School

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Abstract: ABSTRACT This article briefly sketches the evolution of Customer Satisfaction (C-Sat) measurements from a historical point of view and contributes to the future discussion from both academic and practitioner point of views. Firstly, this article argues that traditional methods of measuring C-Sat do not adequately meet current business needs. Secondly, this article suggests that Artificial Intelligence (AI) and Machine Learning (ML) tools and algorithms are capable of complementing or even replacing traditional C-Sat measurements and are even able to help predicting C-Sat before customers themselves enter a transaction. A global managerial survey confirms these propositions. Keywords: Customer satisfaction; CES; NPS; Artificial Intelligence; Machine Learning

Keywords: Customer satisfaction; CES; NPS; Artificial Intelligence; Machine Learning (search for similar items in EconPapers)
Date: 2022
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Published in Journal of Accounting, Finance, Economics, and Social Sciences, 2022, 7 (1), pp.21-29. ⟨10.62458/jafess.160224.7(1)21-29⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-04552977

DOI: 10.62458/jafess.160224.7(1)21-29

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