Most universities look to raise charitable donations from alumni and other stakeholders – but bombarding potential donors with fundraising requests can be ineffective, or even counterproductive. How could MSU find a smarter way?
By mining alumni and stakeholder records, social media and other unstructured data-sets with text analytics software, MSU gains insights into the engagement, sentiments and behavior of current and potential donors.
Uncoversnew insights into donors’ engagement, sentiment and behavior
Measureshow donors feel about MSU by calculating “affinity scores”
Up to 85 percentof alumni are likely to donate if their affinity scores are high enough
Business challenge story
Getting closer to potential donors
Home to a diverse community of scholars, athletes and artists, scientists and leaders, Michigan State University (MSU) is one of the top research universities in the world.
Monique Dozier, AVP Advancement Information Systems and Donor Strategy, Michigan State University, explains: “We have more than 500,000 alumni, many of whom provide generous philanthropic donations to the university. The objective of University Advancement is to build deep and long-term relationships with alumni, stakeholders and other potential partners, in the hope of investing them in the life of the university. In turn, we hope they will willingly become benefactors and advocates for the university.”
The University Advancement team wanted to find more ways to engage with current and potential benefactors. Traditional wealth and asset research methodologies continue to drive prospective donor capacity ratings, and IBM® SPSS® Modeler is now also being used to help the data team provide prospect leads to gift officers based on a variety of factors.
“We wanted the ability to provide our gift officers with a much richer sense of who their current or prospective donors are, what their interests are, what they feel about MSU, and so on,” explains Monique Dozier.
Unlocking value from unstructured data
One thing the University Advancement team didn’t lack was structured data: it had a vast database with over 100 million entries, detailing biographical data, records of committee and board meetings, reports from volunteering initiatives, student and staff records, and donation histories. It also had access to a wealth of other unstructured data in the form of blogs, forums and social media content on the MSU website and elsewhere. Finally, it purchased sets of external consumer and media data from providers such as LexisNexis.
“We wanted a solution that could help us mine all this structured and unstructured information for insights about our alumni and donors,” says Monique Dozier. “Text analytics was the key, and we recognized IBM SPSS Modeler as the most powerful toolset with the strongest roadmap – as well as the easiest to integrate with our corporate reporting and dashboarding solution, IBM Cognos Business Intelligence.”
Working with Ironside Group, an IBM Premier Business Partner, the University Advancement team now has the power to implement and integrate the solution and develop custom libraries for text analytics at its finger-tips. Monique Dozier’s team of eight data scientists is able to build sophisticated sentiment analyses and predictive models whose findings are revolutionizing the way fundraising works within MSU.
Finding the key factors for successful fundraising
Sentiment analysis techniques have revealed a number of insights into prevalent opinions among the donor community about what MSU is doing right, and what it needs to improve.
“Text analytics revealed that donors love the events that we hold for them, especially if they are given the opportunity to meet with our President,” says Monique Dozier. “So it is no surprise that we continue to create opportunities for our alumni and benefactors to engage with our President.”
Equally, a common theme from the analysis was that MSU needs to ensure that donors’ contributions are acknowledged and receipted in a timely fashion. This has led to the University Advancement team evaluating operational processes to eliminate bottlenecks and reduce delays.
The team has also developed an analytical model that calculates an “affinity score” for each potential donor. By analyzing 177 different variables – for example, whether an alumnus has given his address to the alumni engagement team, how many alumni events he attends, and whether he is a member of any university boards or committees – the affinity model provides sophisticated insight into how alumni feel about the university, and hence, how likely they are to donate.
“We were particularly interested in finding out how much influence the affinity scores have on actual donor levels of giving,” comments Monique Dozier. “What we discovered was fascinating. There is a probability of between 65 and 85 percent that potential donors will make a gift at their rated wealth capacity if their affinity scores are sufficiently positive. This means that if we can focus on raising their affinity scores by bringing them into closer engagement with MSU, we can substantially increase the success rate for fundraising.”
To that end, MSU is working hard to equip its alumni engagement and gift officer teams with the insights they need to be successful at securing support for MSU in a variety of ways.
“The combination of IBM technologies makes it easy for us not only to extract these vital new insights, but also to present them in an intuitive, graphical way that our data scientists can easily communicate to managers and fundraising teams,” concludes Monique Dozier.
“By unlocking the knowledge that has been hidden in our structured and unstructured data and embedding it into our everyday fundraising processes, we have a much greater chance of matching the right benefactors with the right opportunities, and maximizing their potential as supporters of this great university.”
About Michigan State University
Michigan State University (MSU) is a public research university, consistently ranked among the top 100 research universities in the world. With nearly 50,000 students and over 10,000 staff, the university offers more than 200 programs of undergraduate, postgraduate and professional study.
- Cognos Analytics
- SPSS Modeler
- SPSS Modeler
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