TY - JOUR
KW - Business Intelligence
KW - Business Analytics
KW - Business Decision Making
KW - Clustering
KW - Machine Learning
AU - Eva Asensio
AU - Alejandro Almeida
AU - Aida Galiano
AU - Juan-Manuel Martín-Álvarez
AB - 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.
IS - Special Issue on Artificial Intelligence in Economics, Finance and Business
M1 - 3
N2 - 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.
PY - 2022
SP - 96
EP - 102
T2 - International Journal of Interactive Multimedia and Artificial Intelligence
TI - Using Customer Knowledge Surveys to Explain Sales of Postgraduate Programs: A Machine Learning Approach
UR - https://www.ijimai.org/journal/sites/default/files/2022-02/ijimai7_3_9.pdf
VL - 7
SN - 1989-1660
ER -