Abstract:

Higher education fundraising in Australia is typically conducted by a university office called ‘Advancement’. This office is responsible for encouraging and securing the university’s fundraising and development activities. While investment in alumni giving is consistent and increasing in Australia currently, much can still be done to increase the effectiveness and success of fundraising activities - specifically what is referred to as the annual fund. One appropriate technique to help in this mission is data mining where even high level data analysis can provide great insight into the data. Clustering algorithms can group donors based on shared characteristics and hopefully help the advancement team at the university in understanding their alumni and donors, what engages these groups and how an initial gift can be used to build long term relationships. By improving donor understanding and developing donor profiles the advancement team can personalize their targeted messaging and enhance donor engagement. The use of cluster analysis can also improve the effectiveness of annual fund raising campaigns and returns on investment by using data driven strategies. For best insights the underlying data must be clean, consistent and available; this is a challenge of implementing data driven strategies.