Fundraising organizations often face uncertainty about when their next donation may come, and how much that donation may be. The use of machine learning can help predict these specific data points, thus helping organizations better plan their communications and team resources. Three founders in the fundraising domain, who each bring their unique perspective to the prospect research problem, join AISC in this interview.
Watch this video to expand you knowledge of fundraising, including terminology, machine learning best-practices in the domain, and how information and insights can be best delivered to clients to maximize buy-in.
Questions asked to the participants:
What is "prospect research." Why is prospect research/annual gift modeling a hard problem? Does the difficulty lie on the technical side, or is it more of a business problem? How do you ensure data is presented to clients in a digestible format? What’s the best format to get buy-in? What sort of data do you work with? What’s the scale of it? Do you train models independently on each customer or train on multiple customers’ data? What privacy concerns come up?
Speakers: Ryan Henry, Jennifer Filla, Marianne Pelletier
Facilitator: Serena McDonnell
Topic - Tips for One-Person Research Shops
Join Staupell Analytics for a discussion on best practices and time-saving tips for one-person research shops. Our team, which has background in one-person shops and in transitioning from one-person to multi-person shops, will discuss their experiences, what worked and what didn't work, and how best to manage precious research time.
Sign up for notifications of important information.