I’m pleased to share that Ashutosh Nandeshwar and I have co-authored a book Data Science for Fundraising: Build Data-Driven Solutions Using R, which is expected to release Feb 2018.
Please share with anyone interested in learning about data science and how to build machine learning solutions with step-by-step recipes.
Check out the attached link for more details about our data science giveaway!
Acquiring new donors can be difficult and expensive for any annual giving program. Fortunately, predictive modeling can make the challenge of converting non-donors into donors easier and more efficient. Creating and applying a simple scoring system can help you to determine which non-donors are most likely to respond to direct appeals and which marketing channels will yield the highest return for various segments.
WHAT YOU’LL DISCOVER
- Methods for building low cost donor acquisition models in-house using Excel
- Guidelines for applying model scores to prioritize prospects and non-donor segments
- Advice for allocating your resources to each of your marketing channels based on model outcomes
- Tips for assessing the strength and effectiveness of your models and your acquisition efforts
- Examples from other institutions, and more!
Thanks to the Annual Giving Network (AGN) team for inviting me to present on predictive modeling for donor acquisition.