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Behavioural profiles of potential students as basis for more effective university recruiting

Kuiper, F.J. (2018) Behavioural profiles of potential students as basis for more effective university recruiting.

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Abstract:Purpose - Large amounts of data are being collected at a dramatic pace. However, organizations often have difficulties to extract knowledge from data and selecting appropriate Machine Learning and User Profiling approaches to fully harness the potential of Behavioural Targeting techniques. This paper aims to develop a framework of Unsupervised Machine Learning (UML) algorithms for User Profiling with respect to important data properties. Moreover, the aim is to discover high converting behavioural profiles among Dutch website visitors of the University of Twente (UT) interested in Master studies. Methodology - A literature review is conducted and the process of Knowledge Discovery in Databases is used as a research methodology. Data was collected between October 2016 and August 2017 from the UT CRM-system and Google Analytics. Complete Linkage and K-modes are used for data analysis. Findings – The proposed framework provides two-stage clustering approaches for categorical, numerical, and mixed types of data with respect to the data size and data dimensionality. Six behavioural profiles were discovered of which two are most significant in terms of conversions. A model is developed that allows for a multi-criteria evaluation on different types of User Profiling. Practical Implications - The results can support researchers and practitioners to determine which UML algorithms are appropriate for developing robust User Profiles. The discovered profiles provide valuable insights for the UT M&C department to improve marketing efforts. Theoretical Implications - The framework and model contribute to literature regarding approaches and methodologies for UML and User Profiling in a marketing context.
Item Type:Essay (Master)
Faculty:BMS: Behavioural, Management and Social Sciences
Subject:54 computer science, 70 social sciences in general, 81 education, teaching, 85 business administration, organizational science
Programme:Business Administration MSc (60644)
Link to this item:http://purl.utwente.nl/essays/77027
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