Higher Education

Higher education institutions live and die by

their ability to successfully raise the funds needed to operate. Targeting the highest value individuals among their alumni and potential donors is an essential activity that yields huge dividends when executed correctly. Michigan State University deeply understands the importance of these activities, and have been working with Ironside’s Advanced Analytics team to create predictive models that will maximize their fundraising efforts.

Customer Case Study

Client Information

Industry: Higher Education

Size: >10000 employees; $1 billion in revenue

Areas of Engagement: Advanced Analytics, Business Intelligence

The Challenge.

MSU wanted to reduce their turnaround time on complex data sets and analyses to identify highly qualified donation prospects faster. This meant layering predictive models over their existing BI implementation to automatically calculate affinity scores for potential donors based on the vast array of variables MSU specified. These scores would then be fed back into the BI platform dashboards for easy consumption by MSU stakeholders.

The Journey.

The Ironside Business Intelligence team had already been working with MSU on their environment, so the Advanced Analytics team was already armed with a comprehensive understanding of the infrastructure when they came on board to start the expansion into predictive analytics. The team identified 170 different variables informing an alumnus’s propensity to donate and constructed a model around these findings that streamlined all these data points into a single score rating for each candidate. The team then linked these findings back to the BI instance, pulling them down into reporting packages for easy querying and side-by-side display with other key insights on dashboards.

The Results.

The value that MSU derived from their new predictive analytics is very apparent. They have greatly improved the speed with which they flag prospects for donation, and are able to act in an expedient fashion to capitalize on those recommendations. Furthermore, the integration of the predictive model results with BI reports allowed users to gain even more crucial insights without learning to interpret a new style of output. These factors have led to significant returns on investment and donation rate increases.

Ironside’s Advanced Analytics team  provided the following major benefits at MSU:

  • Boosted business analyst and director productivity, turning multi-week studies into real-time report insights.

  • Increased data visibility across the institution, allowing for quicker action on findings.

  • Achieved a 55% ROI, achieved payback after 2.1 years, and receive an average annual benefit of $34,434 according to a Nucleus Research report.

  • Reduced internal resource cost of identifying strong donation prospects.

Fill out the form to get instant access to the Ironside Lookbook.