Fundraising Analytics: Using Data to Guide Strategy / Edition 1

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Praise for Fundraising Analytics Using Data to Guide Strategy

"Birkholz has shown in print why he's such a sought-after presenter: his ability to humanize descriptive analytics and provide real-world applications of modeling to fundraising challenges. At the same time, the book presents analysts and statisticians with a clear window into the theory and business practices of philanthropy. Fundraising Analytics belongs on every advancement professional's bookshelf!"
—Robert D. Scott, Executive Director of Development Services

Massachusetts Institute of Technology

"Identifying and analyzing your best prospects is fundamental to successful fundraising. Particularly for institutions blessed with large databases, the knowledge developed through the use of analytic tools can transform the institution's ability to realize its fundraising potential. By applying science to the art of fundraising, organizations are able to bring hard evidence to management decision-making and better define the optimal size, scope, and makeup of the fundraising enterprise."
—Richard K. Naum, Vice President of Development

Memorial Sloan-Kettering Cancer Center

"Companies and institutions in every industry are increasingly discov-ering the power of predictive analytics in gaining competitive advantage and driving success. In Fundraising Analytics, Josh Birkholz paints a clear picture of the application of predictive analytics in the world of nonprofit fundraising. The book establishes an easy-to-follow framework for creating a data-driven approach to decision-making and paves the way for nonprofits to transform their advancement strategies."
—Jack Noonan, CEO

SPSS Inc., a global leader in predictive analytics software

"Josh Birkholz makes a complex topic totally accessible. Any organization that doesn't understand the use of analytics today risks not being around tomorrow. This book is a must-have for every development shop."
—Arthur J. Ochoa, Esquire, Senior Vice President of

Community Relations, Cedars-Sinai Medical Center

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Product Details

  • ISBN-13: 9780470165577
  • Publisher: Wiley
  • Publication date: 4/4/2008
  • Series: AFP/Wiley Fund Development Series , #174
  • Edition description: New Edition
  • Edition number: 1
  • Pages: 240
  • Sales rank: 371,738
  • Product dimensions: 6.00 (w) x 9.00 (h) x 0.69 (d)

Meet the Author

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.

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Table of Contents



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.


Frequency Distribution.

Cross Tabulation.

Recoding Variables.


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.


Model Evaluation.

Final Thoughts on Predictive Modeling.

Final Thoughts on Fundraising Analytics.

Glossary of Common Analytics Terminology.

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