01524nas a2200217   4500000000100000000000100001008004100002260001200043653001900055653001500074653002100089100003000110700003400140700003300174245007900207856009900286300001000385490000600395520089100401022001401292       2019                            d  c09/201910aDecision-level10aClustering10aMachine Learning1 aRosa María Cantón Croda1 aDamián Emilio Gibaja Romero1 aFernando-Rey Castillo-Villar00aThe Promotion of Graduate Programs through Clustering Prospective Students  uhttps://www.ijimai.org/journal/sites/default/files/files/2019/07/ijimai20195_6_3_pdf_12770.pdf  a23-320 v53 aThe promotion of academic programs, particularly at graduate levels, emerges as a response to market changes. In general, graduate programs are not a first order necessity which makes necessary the right promotion of such programs guarantee the attraction of prospective students, which enroll in some of them, which is essential for the financial sustainability of universities. Notably, the last one is a crucial problem for private universities. In this paper, we analyze the prospective students that enroll in a private to design better promotion strategies by using on data gathered by online sources. Specifically, we use clustering techniques to define marketing strategies based on segments of students. We find that age and city are crucial to promoting graduate programs while marital status and sex does not impact the decision of students in the university that we analyze.  a1989-1660