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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.
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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.
Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.
Produktdetails
- Produktdetails
- Verlag: John Wiley & Sons
- Seitenzahl: 240
- Erscheinungstermin: 1. September 2020
- Englisch
- ISBN-13: 9781119782353
- Artikelnr.: 60113179
- Verlag: John Wiley & Sons
- Seitenzahl: 240
- Erscheinungstermin: 1. September 2020
- Englisch
- ISBN-13: 9781119782353
- Artikelnr.: 60113179
- Herstellerkennzeichnung Die Herstellerinformationen sind derzeit nicht verfügbar.
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.
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.
Acknowledgments xi
Foreword xiii
Chapter 1 Overview of Fundraising Analytics 1
Defining Analytics 3
The Mind of an Analyst 6
What to Expect 11
Enjoy the Journey 14
Chapter 2 Understanding Your Constituents 17
Natural Segments 17
Portfolio Assignment 18
Derived Segments 19
Cluster Analysis Case Study 25
Final Thoughts on Understanding Your Constituents 30
Chapter 3 Analytics and Prospecting 31
Development Business Process 31
Integrated Prospecting System 38
Analytics as Part of the Prospecting System 42
Final Thoughts on Analytics and Prospecting 50
Chapter 4 Analytics and Campaign Planning 51
Assessing Campaign Factors 52
Incorporating Campaign Factors 62
Campaign Pyramid 68
Final Thoughts on Campaign Analytics 70
Chapter 5 Data-Driven Prospect Management 71
Elements of Successful Fundraising Organizations 72
Prospect Management 75
Final Thoughts 113
Chapter 6 Annual Giving Analytics 115
Constituent Life Cycles 117
Traditional Donor Segments 127
Predictive Modeling for Annual Giving and Membership 128
Metrics for Annual Giving 133
Final Thoughts on Annual Giving Analytics 135
Chapter 7 Selecting Data for Mining 137
Selection Criteria 138
Variables to Include in Your File 138
Format for Your Data File 152
Chapter 8 Descriptive Analysis: Basic Statistics and Scoring Models 153
Descriptives 154
Frequency Distribution 159
Cross Tabulation 162
Recoding Variables 164
Correlation 170
Correlation Ranking 173
Calculating Database Capacity 175
RFM Analysis 184
Attachment Score 186
Chapter 9 Regression Analysis 189
Define Business Need or Goal 189
Determine Required Data Elements 190
Model Selection 192
Prepare the Data for Modeling 193
Modeling 197
Model Evaluation 207
Final Thoughts on Predictive Modeling 210
Final Thoughts on Fundraising Analytics 211
Glossary of Common Analytics Terminology 213
AFP Code of Ethical Principles and Standards of Professional Practice 217
A Donor Bill of Rights 218
Index 219
Foreword xiii
Chapter 1 Overview of Fundraising Analytics 1
Defining Analytics 3
The Mind of an Analyst 6
What to Expect 11
Enjoy the Journey 14
Chapter 2 Understanding Your Constituents 17
Natural Segments 17
Portfolio Assignment 18
Derived Segments 19
Cluster Analysis Case Study 25
Final Thoughts on Understanding Your Constituents 30
Chapter 3 Analytics and Prospecting 31
Development Business Process 31
Integrated Prospecting System 38
Analytics as Part of the Prospecting System 42
Final Thoughts on Analytics and Prospecting 50
Chapter 4 Analytics and Campaign Planning 51
Assessing Campaign Factors 52
Incorporating Campaign Factors 62
Campaign Pyramid 68
Final Thoughts on Campaign Analytics 70
Chapter 5 Data-Driven Prospect Management 71
Elements of Successful Fundraising Organizations 72
Prospect Management 75
Final Thoughts 113
Chapter 6 Annual Giving Analytics 115
Constituent Life Cycles 117
Traditional Donor Segments 127
Predictive Modeling for Annual Giving and Membership 128
Metrics for Annual Giving 133
Final Thoughts on Annual Giving Analytics 135
Chapter 7 Selecting Data for Mining 137
Selection Criteria 138
Variables to Include in Your File 138
Format for Your Data File 152
Chapter 8 Descriptive Analysis: Basic Statistics and Scoring Models 153
Descriptives 154
Frequency Distribution 159
Cross Tabulation 162
Recoding Variables 164
Correlation 170
Correlation Ranking 173
Calculating Database Capacity 175
RFM Analysis 184
Attachment Score 186
Chapter 9 Regression Analysis 189
Define Business Need or Goal 189
Determine Required Data Elements 190
Model Selection 192
Prepare the Data for Modeling 193
Modeling 197
Model Evaluation 207
Final Thoughts on Predictive Modeling 210
Final Thoughts on Fundraising Analytics 211
Glossary of Common Analytics Terminology 213
AFP Code of Ethical Principles and Standards of Professional Practice 217
A Donor Bill of Rights 218
Index 219
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.
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.
Acknowledgments xi
Foreword xiii
Chapter 1 Overview of Fundraising Analytics 1
Defining Analytics 3
The Mind of an Analyst 6
What to Expect 11
Enjoy the Journey 14
Chapter 2 Understanding Your Constituents 17
Natural Segments 17
Portfolio Assignment 18
Derived Segments 19
Cluster Analysis Case Study 25
Final Thoughts on Understanding Your Constituents 30
Chapter 3 Analytics and Prospecting 31
Development Business Process 31
Integrated Prospecting System 38
Analytics as Part of the Prospecting System 42
Final Thoughts on Analytics and Prospecting 50
Chapter 4 Analytics and Campaign Planning 51
Assessing Campaign Factors 52
Incorporating Campaign Factors 62
Campaign Pyramid 68
Final Thoughts on Campaign Analytics 70
Chapter 5 Data-Driven Prospect Management 71
Elements of Successful Fundraising Organizations 72
Prospect Management 75
Final Thoughts 113
Chapter 6 Annual Giving Analytics 115
Constituent Life Cycles 117
Traditional Donor Segments 127
Predictive Modeling for Annual Giving and Membership 128
Metrics for Annual Giving 133
Final Thoughts on Annual Giving Analytics 135
Chapter 7 Selecting Data for Mining 137
Selection Criteria 138
Variables to Include in Your File 138
Format for Your Data File 152
Chapter 8 Descriptive Analysis: Basic Statistics and Scoring Models 153
Descriptives 154
Frequency Distribution 159
Cross Tabulation 162
Recoding Variables 164
Correlation 170
Correlation Ranking 173
Calculating Database Capacity 175
RFM Analysis 184
Attachment Score 186
Chapter 9 Regression Analysis 189
Define Business Need or Goal 189
Determine Required Data Elements 190
Model Selection 192
Prepare the Data for Modeling 193
Modeling 197
Model Evaluation 207
Final Thoughts on Predictive Modeling 210
Final Thoughts on Fundraising Analytics 211
Glossary of Common Analytics Terminology 213
AFP Code of Ethical Principles and Standards of Professional Practice 217
A Donor Bill of Rights 218
Index 219
Foreword xiii
Chapter 1 Overview of Fundraising Analytics 1
Defining Analytics 3
The Mind of an Analyst 6
What to Expect 11
Enjoy the Journey 14
Chapter 2 Understanding Your Constituents 17
Natural Segments 17
Portfolio Assignment 18
Derived Segments 19
Cluster Analysis Case Study 25
Final Thoughts on Understanding Your Constituents 30
Chapter 3 Analytics and Prospecting 31
Development Business Process 31
Integrated Prospecting System 38
Analytics as Part of the Prospecting System 42
Final Thoughts on Analytics and Prospecting 50
Chapter 4 Analytics and Campaign Planning 51
Assessing Campaign Factors 52
Incorporating Campaign Factors 62
Campaign Pyramid 68
Final Thoughts on Campaign Analytics 70
Chapter 5 Data-Driven Prospect Management 71
Elements of Successful Fundraising Organizations 72
Prospect Management 75
Final Thoughts 113
Chapter 6 Annual Giving Analytics 115
Constituent Life Cycles 117
Traditional Donor Segments 127
Predictive Modeling for Annual Giving and Membership 128
Metrics for Annual Giving 133
Final Thoughts on Annual Giving Analytics 135
Chapter 7 Selecting Data for Mining 137
Selection Criteria 138
Variables to Include in Your File 138
Format for Your Data File 152
Chapter 8 Descriptive Analysis: Basic Statistics and Scoring Models 153
Descriptives 154
Frequency Distribution 159
Cross Tabulation 162
Recoding Variables 164
Correlation 170
Correlation Ranking 173
Calculating Database Capacity 175
RFM Analysis 184
Attachment Score 186
Chapter 9 Regression Analysis 189
Define Business Need or Goal 189
Determine Required Data Elements 190
Model Selection 192
Prepare the Data for Modeling 193
Modeling 197
Model Evaluation 207
Final Thoughts on Predictive Modeling 210
Final Thoughts on Fundraising Analytics 211
Glossary of Common Analytics Terminology 213
AFP Code of Ethical Principles and Standards of Professional Practice 217
A Donor Bill of Rights 218
Index 219
" .is a gift to the massess..a lens into the world of the sophisticated fundraising operations that pump the big bucks into major institutions. Written by Joshua Birkholz, the book s subtitle is Using Data to Guide Strategy" and that s what the book delivers." ( CharityChannel.com , June 6, 2008)