With the development of advanced CRM’s and the increase in availability of alumni and donor data, we have the opportunity to become smarter marketers if we learn to listen to what the data is telling us. The University of Connecticut Foundation is using advanced analytics to better understand their constituents’ giving behavior, improve segmentation and shift annual giving strategy to a more donor-centered approach. This session will look at how to create and analyze metrics with the use of dashboards, and how to use these to produce actionable insights for both short-term and long-term success.

The ability to measure activity and understand the relationship between that activity and fundraising productivity are critical to the strategic deployment and maximization of fundraising resources. Furthermore, the capability to identify early intervention points for coaching new gift officers and the continued measurement of seasoned gift officer performance are key in ensuring gift officer success. But what should we be measuring? How should we be measuring it? Who should have access to the metrics? Can predictive solutions be deployed to assist in early intervention? And finally, how can these gift officer metrics be used effectively to inform decision making? The University of Texas at Austin has just completed an 18 month exploratory exercise aimed at building a predictive model to better quantify gift officer performance, establish baseline expectations, and identify early intervention points for coaching new gift officers. Multiple algorithms were explored in partnership with graduate students from UT Austin’s School of Information and members of the university development office’s analytics team. This presentation will detail the process undertaken to arrive at a solution, discuss the insights acquired along the way, and walk attendees through the mechanism produced to distribute scores. Considerations for generating equitable metrics based on role, unit assignment, officer type, and the impact of COVID-19 will be discussed along with an exposition of the final results.

Ever find yourself running the same report for multiple departments or prospect pools? Wanting to re-run an analysis, but forgetting how you undertook it several weeks, months, or years back? Frustrated over how best to combine multiple data sources? Rmarkdown may be a solution for you. This open source solution provides users with a format to combine analytical processes with documentation. It's flexible enough to run workflows in a multitude of languages (R, Python, and SQL, among others), produce various output media, and automate reporting. 

This session will be followed by a Part Two Workshop at 4:00 PM. 

In 2019, CASE’s AMAtlas launched a new survey to measure Alumni Engagement Metrics, which aimed to create a broader understanding of alumni affinity beyond purely philanthropic support. Several challenges arose in the first year, including socializing new metrics, creating a truly global survey, framing the data story, and developing compelling visualizations. In the second year, staff and volunteers incorporated lessons learned to make practical improvements to the survey.

In this session, join members of the AMAtlas team as they discuss their perspectives. The presentation includes a high-level overview about how to incorporate new metrics into existing paradigms and manage expectations externally, creating methods for managing an evolving survey, implementing changes based on feedback, and strategies for developing adaptive reporting using R to match changing expectations.

This will be an interactive workshop based on the Part One Session at 2:45 PM.

Over time, Higher Ed campaigns have become more dependent on big gifts from a few donors. We get focused on those big donors and by the time the campaign is complete, we realize we haven’t cultivated a full pipeline to prepare us for fundraising life post-campaign. As we add the reality of a struggling economy due to the current pandemic, we need to re-think the campaign model.  In this session, Matthew White and Rachel Richards from Utah State University will present their innovative approach to fundraising and campaigns leveraging the full gift pyramid.

The New York University (NYU) Development and Alumni Relations (UDAR) team and the University of Washington (UW)Advancement Analytics team will take you on a journey and share how they were able to jumpstart unique data analytics initiatives from inception to maturity in less than a year. Their journeys center on aligning technology with leadership visions and goals, while also empowering front-line fundraisers and marketers to uncover opportunities and take action on critical business insights. They will share an approach that helps them accelerate the implementation and deployment of specialized dashboards, improve the endorsement of their colleagues, and secure high adoption by diverse teams and non-data users. They will demonstrate how their approach can help instill a data-driven culture, and share strategies on how to tackle unique challenges presented by digital data and legacy systems while trying to provide flexible self-service analysis tools. They will also showcase UW’s Email Marketing Dashboard that serves over 50 units, three campuses and over 100 marketers and advancement staff, and NYU’s BI portal which contains more than 60 Dashboards and self-service reports that serve more than 300 fundraisers and development associates and staff and more than 20 schools and global camps.

Hear from a panel of your peers as they share how their institutions are using engagement metrics to refine their approach to alumni engagement and fundraising. We’ll cover what data they chose to include in their engagement metrics, how they shared the results with their teams to ensure adoption, and how data can be used for future engagement strategy, while also supporting annual giving and major gift efforts. Leave this session with a plan for analyzing your constituent data so you can take the next step to turn that data into meaningful change for your institution.