EconPapers    
Economics at your fingertips  
 

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

Huseyin Güngör
Additional contact information
Huseyin Güngör: University of Amsterdam Business School

Journal of Accounting, Finance, Economics, and Social Sciences, 2022, vol. 7, issue 1, 21-29

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 (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations:

Downloads: (external link)
https://jafess.com/index.php/home/article/view/44 Abstract page (text/html)
https://jafess.com/index.php/home/article/download/44/34 Full text (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:euj:jafess:v:7:y:2022:i:1:id:44

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

Access Statistics for this article

More articles in Journal of Accounting, Finance, Economics, and Social Sciences from CamEd Business School
Bibliographic data for series maintained by Narin Choeun ().

 
Page updated 2026-08-01
Handle: RePEc:euj:jafess:v:7:y:2022:i:1:id:44