Marketing Automation in der Bewerber-Lead-Generierung von Hochschulen

Abstract

In an increasingly competitive higher education environment, targeting potential students is a key challenge. This master's thesis examines the potential of marketing automation (MA) to optimize the applicant lead generation process (BLGP) at universities. The aim is to develop a theoretically sound and empirically validated MA concept that is applied to the University of Applied Sciences Upper Austria (FH OÖ) as an example. Methodologically, the thesis is based on a structured literature review and a qualitative empirical study in the form of semi-structured expert interviews with six Austrian universities. The results show that universities currently use mainly traditional, at most partially automated measures in the BLGP, which limits efficiency and personalization. The analysis identified key touchpoints along the applicant journey that can be systematically addressed and automated through marketing automation. In the course of the empirical study, best practices from Austrian universities were collected and integrated into a transferable MA concept. This includes measures such as automated recommendation algorithms, hyper-personalization, the use of AI-supported social bots, and AI telephone assistants. The application at the University of Applied Sciences Upper Austria shows that targeted automation enables effective, scalable, and data-based communication with potential applicants. The work makes a practical contribution to digitalization and efficiency improvement in university marketing and university applicant management and offers recommendations for action for the implementation of marketing automation in the education sector.

Date of Award	2025
Original language	German (Austria)
Awarding Institution	Johannes Kepler University Linz
Supervisor	Andreas Auinger (Supervisor)