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by J. Andrew Petersen, V. Kumar
Statistical Methods in Customer Relationship Management
Cover
Title Page
Copyright
Dedication
Preface
1 Need for this Book
2 Supplements to the Book
3 Organization of the Book
Acknowledgments
Chapter 1: Customer Relationship Management
1.1 Introduction
1.2 What is CRM?
1.3 What is Needed to Implement CRM Strategies?
1.4 Analytical Methods
1.5 Conclusion
References
Chapter 2: CRM in Action
2.1 Introduction
2.2 The Importance of Customer Acquisition
2.3 The Significance of Customer Retention
2.4 The Impact of Customer Churn
2.5 The Benefits of Customer Win-back
2.6 Conclusion
References
Chapter 3: Customer Acquisition
3.1 Introduction
3.2 Response Probability
3.3 Number of Newly Acquired Customers and Initial Order Quantity
3.4 Duration/Time
3.5 Firm's Performance (LTV, CLV, and CE)
3.6 Chapter Summary
Customer acquisition – SAS code
Customer acquisition – SAS output
References
Chapter 4: Customer Retention
4.1 Introduction
4.2 Repurchase or Not (Stay or Leave)
4.3 Lifetime Duration
4.4 Order Quantity and Order Size
4.5 Cross-buying
4.6 SOW
4.7 Profitability (CLV)
4.8 Chapter Summary
Customer retention – SAS code
Customer retention – SAS output
References
Chapter 5: Balancing Acquisition and Retention
5.1 Introduction
5.2 Acquisition and Retention
5.3 Optimal Resource Allocation
5.4 Chapter Summary
5.5 Balancing acquisition and retention – SAS code
5.6 Balancing acquisition and retention – SAS output
References
Chapter 6: Customer Churn
6.1 Introduction
6.2 Customer Churn
6.3 Chapter Summary
Customer churn – SAS Code
Customer churn – SAS Output
References
Chapter 7: Customer Win-back
7.1 Introduction
7.2 Customer win-back
7.3 Chapter Summary
Customer win-back – SAS code
Customer win-back – SAS output
References
Chapter 8: Implementing CRM Models
8.1 Introduction
8.2 CLV Measurement Approach
8.3 CRM Implementation at IBM
8.4 CRM Implementation at a B2C Firm
8.5 Challenges in Implementing the CLV Management Framework
References
Chapter 9: The Future of CRM
9.1 Introduction
9.2 Social Media
9.3 Mobile Marketing
9.4 Customized Marketing Campaigns
9.5 Conclusion
References
Appendix A: Maximum Likelihood Estimation
References
Appendix B: Log-linear Model—An Introduction
References
Appendix C: Vector Autoregression Modeling
C.1 Unit-Root Testing: Are Performance and Marketing Variables Stable or Evolving?
C.2 Cointegration Tests: Does a Long-Run Equilibrium Exist between Evolving Series?
C.3 VAR Models: How to Capture the Dynamics in a System of Variables?
C.4 Impulse-Response Function Derivation
C.5 Impulse-Response Functions: Mathematical Derivations
References
Appendix D: Accelerated Lifetime Model
References
Appendix E: Type-1 Tobit Model
References
Appendix F: Multinomial Logit Model
References
Appendix G: Survival Analysis – An Introduction
References
Appendix H: Discrete-Time Hazard
References
Appendix I: Proportional Hazards Model
References
Appendix J: Random Intercept Model
References
Appendix K: Poisson Regression Model
References
Appendix L: Negative Binomial Regression
References
Appendix M: Estimation of Tobit Model with Selection
References
Index
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Appendix B: Log-linear Model—An Introduction
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Appendix C: Vector Autoregression Modeling
Reference
1.
Knoke, D. and Burke, P.J. (1980)
Log-linear Models
, Sage, Beverly Hills, CA.
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