Print ISSN : 2708-616X | Online ISSN : 2708-6178 | DOI: https://doi.org/10.62458/160224
Volume 7 | Number 1 | January – June 2022 | DOI: https://doi.org/10.62458/jafess.160224.7(1)21-29
Received : April 2022 | Revised: May 2022 | Accepted: June 2022
Huseyin Güngör, Ph.D.
University of Amsterdam Business School, Netherlands
Email: [email protected]
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
