Using Customer Knowledge Surveys to Explain Sales of Postgraduate Programs: A Machine Learning Approach.

Eva Asensio del Arco; Alejandro Almeida Márquez; Aida Galiano Martínez; Juan Manuel Martín Álvarez

doi:10.9781/ijimai.2022.01.008

Authors

Eva Asensio del Arco Universidad Internacional De La Rioja
Alejandro Almeida Márquez Universidad Internacional De La Rioja
Aida Galiano Martínez Universidad Internacional De La Rioja
Juan Manuel Martín Álvarez Universidad Internacional De La Rioja

DOI:

https://doi.org/10.9781/ijimai.2022.01.008

Keywords:

Business Intelligence, Business Analytics, Business Decision Making, Clustering, Machine Learning

Abstract

Universities collect information from each customer that contacts them through their websites and social media profiles. Customer knowledge surveys are the main information-gathering tool used to obtain this information about potential students. In this paper, we propose using the information gained via surveys along with enrolment databases, to group customers into homogeneous clusters in order to identify target customers who are more likely to enroll. The use of such a cluster strategy will increase the probability of converting contacts into customers and will allow the marketing and admission departments to focus on those customers with a greater probability of enrolling, thereby increasing efficiency. The specific characteristics of each cluster and those postgraduate programs that are more likely to be selected are identified. In addition, better insight into customers regarding their enrolment choices thanks to our cluster strategy, will allow universities to personalize their services resulting in greater satisfaction and, consequently, in increased future enrolment.

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