Fundraising Analytics: Using Data To Guide Strategy (Afp Fund Development Series)

Fundraising Analytics: Using Data to Guide Strategy Fundraising Analytics shows you how to turn your nonprofit?s organizational data?with an appropriate focus on donors?into actionable knowledge. The result? A vibrant, donor-centered nonprofit organization that makes maximum use of data to reveal the unique diversity of its donors. It provides step-by-step instructions for understanding your constituents, developing metrics to gauge and guide your success, and much more.

Joshua M. Birkholz is a principal at Bentz Whaley Flessner, a leading fundraising consulting firm, and director of its analytics division, DonorCast. He has built data mining solutions for leading universities, medical centers, and cultural nonprofits throughout the United States. His areas of specialty include metrics for nonprofit fundraising, constituency analysis, segmentation, and integrated prospect identification systems. He is a sought-after speaker and presenter in the field of analytics, prospecting, and constituent relationship management.

Acknowledgments.
Foreword.
Chapter 1. Overview of Fundraising Analytics.
Defining Analytics.
The Mind of an Analyst.
What to Expect.
Enjoy the Journey.
Chapter 2. Understanding Your Constituents.
Portfolio Assignment.
Derived Segments.
Philanthropic Motivations.
Cluster Analysis Case Study.
Final Thoughts on Understanding Your Constituents.
Chapter 3. Analytics and Prospecting.
Development Business Process.
Integrated Prospecting System.
Analytics as Part of the Prospecting Systems.
Final Thoughts on Analytics and Prospecting.
Chapter 4. Analytics and Campaign Planning.
Assessing Campaign Factors.
Incorporating Campaign Factors.
Campaign Pyramid.
Final Thoughts on Campaign Analytics.
Chapter 5. Data-Driven Prospect Management.
Prospect Management.
Final Thoughts.
Chapter 6. Annual Giving Analytics.
Constituent Life Cycles.
Traditional Donor Segments.
Predictive Modeling for Annual Giving and Membership.
Metrics for Annual Giving.
Final Thoughts on Annual Giving Analytics.
Chapter 7. Selecting Data for Mining.
Selection Criteria.
Variables to Include in Your File.
Format for Your Data File.
Chapter 8. Descriptive Analysis: Basic Statistics and Scoring Models.
Descriptives.
Frequency Distribution.
Cross Tabulation.
Recoding Variables.
Correlation.
Correlation Ranking.
Calculating Database Capacity.
RFM Analysis.
Attachment Score.
Chapter 9. Regression Analysis.
Define Business Need or Goal.
Determine Required Data Elements.
Model Selection.
Prepare the Data for Modeling.
Modeling.
Model Evaluation.
Final Thoughts on Predictive Modeling.
Final Thoughts on Fundraising Analytics.
Glossary of Common Analytics Terminology.