I recently attended (and gave a keynote address at) the APRA PD Data Analytics Symposium (APRA DAS), an analytics conference co-located with the larger APRA Prospect Development conference. It was held at the expansive David L. Lawrence Convention Center, which overlooks the Allegheny River in downtown Pittsburgh.
With over 170 attendees from universities and other fundraising institutions, APRA DAS provided access to a wide variety of stakeholders in advancement/fundraising analytics. I met people who were analytics team managers, prospect researchers hoping to get into analytics, and data analysts & data scientists working for fundraising organizations. In addition to hearing the conference talks, we networked in person over coffee, and on social media with the hashtag #APRADAS2018. (Photo below via Rodger Devine @xdanalysis on Twitter.)
I gave a talk about “My Journey from Advancement Data Analyst to Data Scientist”, and watched other talks that dove into various aspects of the industry - like prospect management, contact reports, and the future of fundraising analytics - as well as technical topics - like analytics automation & code packaging, dashboard design, forecasting, and text mining.
One idea that was reinforced by attending APRA DAS is that there is a whole lot of opportunity in the world of Advancement Analytics. This is an industry where most organizations’ analytics maturity level appears to be just starting to grow into the “descriptive” and “diagnostic” types of reporting, with a lot of focus on operational reports and task automation, and only a few leading organizations really pushing into predictive modeling and optimization. However, it’s also an industry that cares a lot about collecting and securing data, and putting it into a form usable by front-line fundraisers and program directors.
This conference also reinforced my belief that advancement analytics is an industry of caring innovators. Many analytics shops in higher ed fundraising consist of only one or two analysts, who do everything from SQL development to dashboard design to machine learning. These are self-starters and lifelong learners who care about raising money to do good in the world, and want to learn new tools and techniques to help their organizations help others.
People I met used every analysis tool imaginable to do their work and distribute their reports. Amongst the data scientists, there were people who used Python, R, SAS, Excel, Tableau, Cognos, and other programming languages and software. They were forecasting funds raised, finding major gift prospects, prioritizing phonathon segments, using deep learning to predict donor responses, setting up reporting triggers to inform prospect researchers, developing reusable code packages, and designing beautiful dashboards for end-users who are more used to developing relationships with people than with analytical tools!
I’m excited to be working with several Institutional Advancement organizations as a Data Scientist at HelioCampus, because it gives me a chance to build tools that add to the toolboxes of the analysts and managers at these organizations, and to provide infrastructure that reduces the frustration around working with constituent and gift data, so the focus can be on adding value through advanced analytics and data-driven strategy, taking them beyond simply describing their constituents and giving.
I look forward to continuing to exchange ideas with the people I met at APRA DAS, and hope to be back next year!