Everyone wants to make “data informed decisions” especially during periods of strategic planning and solicitation plan development. Yet, we often underutilize vital data-informed positions such as Prospect Development, which traditionally is viewed as a resource primarily for leadership and major giving. But what would it look like if we took prospect development and applied advancement data analytics to serve as a resource for all University Advancement? Come learn from Texas State University how their restructuring took prospect development, data analytics, and business processes and turned it into a strategic arm serving the entire advancement organization. Learn about holistic pipeline development when leveraging both prospect development and analytics together to advise and inform strategy development for alumni relations, annual giving, AND major giving.

There has been increased interest in leveraging predictive AI by non-profits to generate new major and legacy gift prospects and for improving annual fund prioritization. Last year we looked at how the principles of Exploratory Data Analysis (EDA) could help build better models. This year we will dive a little deeper into exploring potential factors using tools such as partial regression plots and diagnostics such as Hadi’s Influence and Cook’s Distance. We’ll also discuss approaches for effectively activating the results. Come see how we can make statistical modeling fun.

This session will examine the processes, policies, and opportunities for building and maintaining alumni employment dashboards in your advancement shop. The speakers will use examples from projects at multiple institutions to discuss ways to scale the project, define your data goals, prioritize output based on institutional priorities, and build sustainable workflows for advancement data teams of various sizes and technical expertise.

In fundraising, it is often difficult to calculate the probability that a given prospect will make a gift, or the likelihood that our organization will reach a specific fundraising dollar goal. The usual measures used in identifying probability don’t always work when it comes to human activity, and donative behavior is no different.
During this presentation, Dr. Gregory Duke will review several methods of identification of probability and identify which of these methods can give you a better understanding of your prospects’ likelihood to give. Dr. Duke will also use other measures of probability used in games, sports, medicine, and nature to illustrate the depth and breadth of donor possibilities. Lastly, Dr. Duke will demonstrate a technique to put all these together to create a predictive model of donor behavior over time.

It’s been almost nine months since the world’s first fully autonomous fundraiser interacted with its first assigned donor. During that time, 11 higher educational institutions joined together as a cohort to engage donors with an AI-powered Virtual Engagement Officer (and a second cohort is now live), but more importantly research, develop, and accelerate the deployment of autonomous fundraising for our entire industry.

In this session, Jennifer Shimp-Bowerman of Bucknell University and Natalie Spring of VCU will present the results they’ve seen from autonomous fundraising – donors engaged, dollars raised, and pipeline built, in addition to their experience being the first organizations in the world to deploy a Virtual Engagement Officer to a portfolio of their donors.

We’ll present what we learned, what we got right, where course corrections were needed, and how we navigated AI in a field defined by relationships. We’ll share all of our findings including portfolios for autonomous fundraisers, sourcing engagement content independently, accuracy, data collection, and more.

Finally, we’ll conclude by looking at where we are going, how we can continue to further personalize donor journeys led by donor engagement data, how to push the outer limits of technology, and more.

Discover how R can simplify your work by automating repetitive tasks, from data analysis to generating reports and PowerPoint presentations. This session explores how to create reproducible workflows that save time and increase efficiency. Learn practical methods for integrating machine learning and GenAI to enhance your analytics and presentation game. Whether you're a seasoned data scientist or just starting, you'll walk away with actionable techniques to restructure your process and maximize impact.

Pipeline development is a major challenge facing our profession. Donor bases are declining, retention rates are sliding, younger alumni are less inclined to engage with their alma maters, and the principal gifts concentration is only increasing. The University of Nebraska Foundation has developed multiple data-driven, innovative strategies to “double down” on its pipeline development work. Combined, these programs have already resulted in 14,000 prospects contacted, 3,000 personal meetings, 300 qualified major gift prospects, $10 million in new gifts, and 82% retention of leadership annual donors. Explore the strategic intent, data, and processes leveraged to build a new, innovative approach to comprehensive pipeline development.

Recent trends in U.S. giving indicate a consistent decline in donor retention rates over the past decade. This trend threatens the sustainability of crucial programs and initiatives. To combat this, organizations must harness the power of data-informed strategies to better understand donor behaviors, identify gaps, and optimize outreach efforts.
This presentation will explore innovative ways to leverage data analytics to reverse declining donor trends. Key areas of focus will include donor segmentation, predictive modeling, personalized communication strategies, and the significance of donor lifecycle analysis. By integrating these approaches, we aim to cultivate more meaningful relationships with donors, enhance retention rates, and foster long-term support.