Statistical Methods in Customer Relationship Management E-Book

V. Kumar

• Herausgeber: John Wiley & Sons
• Kategorie: Wissenschaft und neue Technologien
• Sprache: Englisch

Seitenzahl: 387

Veröffentlichungsjahr: 2012

Beschreibung

Statistical Methods in Customer Relationship Management focuses on the quantitative and modeling aspects of customer management strategies that lead to future firm profitability, with emphasis on developing an understanding of Customer Relationship Management (CRM) models as the guiding concept for profitable customer management. To understand and explore the functioning of CRM models, this book traces the management strategies throughout a customer’s tenure with a firm. Furthermore, the book explores in detail CRM models for customer acquisition, customer retention, customer acquisition and retention, customer churn, and customer win back.

Statistical Methods in Customer Relationship Management:

• Provides an overview of a CRM system, introducing key concepts and metrics needed to understand and implement these models.
• Focuses on five CRM models: customer acquisition, customer retention, customer churn, and customer win back with supporting case studies.
• Explores each model in detail, from investigating the need for CRM models to looking at the future of the models.
• Presents models and concepts that span across the introductory, advanced, and specialist levels.

Academics and practitioners involved in the area of CRM as well as instructors of applied statistics and quantitative marketing courses will benefit from this book.

Leseprobe

Contents

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

This edition first published 2012 © 2012 John Wiley & Sons, Ltd

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Library of Congress Cataloging-in-Publication Data:

Kumar, V., 1957–

Statistical methods in customer relationship management / V. Kumar, J. Andrew Petersen.

p. cm.

Includes bibliographical references and index.

ISBN 978-1-119-99320-9 (cloth)

1. Customer relations–Management. 2. Customer relations–Management—Statistical models.

I. Petersen, J. Andrew. II. Title.

HF5415.5.K864 2012

658.8′12015195—dc23

2012012175

A catalogue record for this book is available from the British Library.

ISBN: 978-1-119-99320-9

Dedicated with LoveTo my parents, Patta & Viswanathan and uncle Kannan,Other family members – Prita, Anita, Rohan and Aparna, andMy in-laws Dr. Lalitha and Ramamurthy

– V. Kumar

Dedicated with LoveTo Katie: my wife, sweetheart, and the mother of our twowonderful children Alexa and William

– J. Andrew Petersen

Preface

Companies invest millions of dollars in Customer Relationship Management (CRM) systems and strategies. The primary objectives of these systems are to (a) acquire profitable customers, (b) retain profitable customers, (c) prevent profitable customers from migrating to competition, and (d) winning back ‘lost’ profitable customers. These four objectives collectively lead to increasing the profitability of an organization. While most firms recognize the benefits of establishing CRM systems and strategies, not all firms have been successful in their CRM implementations. So, why did they fail?

Traditional marketing theory and practice have always recommended that a company focus on expanding the customer base will lead to increased profitability. But, what about retaining the customers? Additionally, what about preventing customers from churning and winning back ‘lost’ customers? This book, at its core, explores these topics that are an integral part of the customer management process. Information and understanding these topics will contribute towards an enhanced financial performance of companies. Companies such as IBM, Zappos, Continental Airlines, Henkel, and Hewlett-Packard have understood the importance and relevance of all these four customer management topics as they apply to their organizations, thereby becoming leaders in their respective domains through the implementation of CRM programs. In order to understand the managerial relevance of these four customer management topics and successfully implement CRM systems, it is important to understand the engines that drive these systems – the quantitative models.

This book focuses on the quantitative and modeling aspects of customer management strategies that lead to future firm profitability. The book stresses on developing an understanding of the statistical models used in CRM applications as the guiding concept for profitable customer management. To understand and explore the functioning of models used in CRM applications, this book traces the management strategies throughout a customer's tenure with a firm. Specifically, the book will review five sets of models that will facilitate effective customer management strategy development and CRM implementation. They are:

1. Models for customer acquisition. A customer's tenure with a firm starts with his/her acquisition by the firm. Here, the firm's decisions include identifying the right customers to acquire, forecasting the number of new customers, and the response of promotional campaigns, among others.

2. Models for customer retention. During the customer's tenure with the firm, the firm would be interested in retaining this customer for a longer period of time. This calls for investigating the role of trust and commitment with the firm, metrics for customer satisfaction, and the role of loyalty and reward programs, among others. Additionally, decisions on who will buy, what the customers will buy, when they will buy, and how much they will buy are explored through a discussion of the various models used in the literature.

3. Integrated models for acquiring and retaining customers. This set of models focuses on the small subset of the literature that has linked customer acquisition and retention. Establishing this link is crucial as it has important implications for customer profitability and optimal allocation of marketing resources between acquisition and retention.

4. Models for customer churn. In modeling customer attrition, some of the important decisions made by a firm include identifying whether the customer will churn or not, and if so what will be the probability of the customer churning, and when.

5. Models for customer win-back. Customer win-back refers to ‘reacquiring’ customers after the customer has terminated the relationship with the firm. Here, it is important to understand what CRM models and strategies can do to bring the customer back to the firm in both B2C and B2B settings.

The above-mentioned five sets of models – customer acquisition, customer retention, customer acquisition and retention, customer churn, and customer win-back – form the core of this book. Apart from covering these models, the book will also investigate the need for such CRM models, review the implementation of these models, and look into the future of these models.

1 Need for this Book

A review of the literature on CRM thus far shows the sheer volume, variety, and range of models and the research problems addressed. For academics and practitioners interested and/or involved in the area of CRM, this range becomes too wide to cover and may therefore lead to the development of ineffective CRM systems.

The foremost objective of this book is to serve as a guide to all the models in the CRM literature by classifying them into four sections: customer acquisition, customer retention, customer churn, and customer win-back. These four sections also happen to be the stages a customer goes through during his/her tenure with a firm. By traversing the path of a customer's lifetime with a firm, this book will enlighten and educate the readers on all the models involved in the four stages and help them build effective CRM systems.

2 Supplements to the Book

These are as follows:

1. The chapters pertaining to the five sets of CRM models will contain sample datasets to explain the working of the models described. These chapters will contain the SAS codes and SAS outputs for the sample datasets at the end of the respective chapters, and the sample datasets used (in Excel format) will be uploaded to the book's companion website located at www.wiley.com/go/customer_relationship.

2. Downloadable PowerPoint presentations are available for all chapters via the text's website.

3 Organization of the Book

The book adopts a model-based approach toward CRM. It illustrates and reviews the quantitative and modeling aspects needed to understand and implement CRM strategies. The modeling techniques presented here form the foundation for designing and implementing strategic marketing decisions. A brief description of the chapters contained in this book is as follows:

Chapter 1: Introduction. This chapter provides an overview and functioning of a CRM system. It introduces key concepts and metrics needed to understand and implement CRM models. It also describes the process of building and developing CRM models.Chapter 2: Need for CRM models. This chapter outlines the need for CRM models by emphasizing the developments thus far in the CRM literature. Further, this chapter discusses the overall structure of CRM models, and their uses and benefits from a business/marketing standpoint, rather than a technical one. The framework adopted in this book will be whether the models are deterministic or stochastic, and whether they are discrete or continuous. Thus all the models discussed in the book should fall into one of the five chapters that follow.Chapter 3: Models for customer acquisition. This chapter starts the discussion on the first stage of CRM – acquiring new customers. The objectives of customer acquisition modeling include identifying the right customers to acquire, predicting whether customers will respond to company promotion campaigns, forecasting the number of new customers, and examining the short- and long-run effects of marketing and other business variables on customer acquisition. The model specifications that are covered in this chapter include logit, probit, Tobit, linear regression, log-linear, vector autoregression, hazard function, and decision calculus. Besides covering the modeling aspects of customer acquisition, this chapter also reviews a large number of studies that focus on the effects of marketing variables as drivers or predictors of customer acquisition.Chapter 4: Models for customer retention. After customers have been acquired, this chapter talks about the second step of CRM – retaining customers. Customer retention strategies are used in both in contractual (where customers are bound by contracts such as cell (mobile) phone subscription or magazine subscription) and in non-contractual settings (where customers are not bound by contracts such as grocery purchases or apparel purchases). In providing the models for customer retention, the primary objectives of this chapter include examining the factors influencing customer retention, predicting customers' propensity to stay with the company or terminate the relationship, and predicting the duration of the customer–company relationship. In examining these factors on retention, this chapter reviews model specifications that include logit, probit, Tobit, multinomial logit, hazard function, discrete-hazard function, proportional hazards function, discrete proportional hazards function, random intercepts, Pareto/NBD, shifted-beta geometric distribution, log-normal, negative binomial, Poisson, linear regression, system of regressions, and deterministic methods.Chapter 5: Integrated models for acquiring and retaining customers. While most studies consider customer acquisition and retention as independent processes, only a few have linked them together. This chapter focuses on studies which seek to model the two processes simultaneously. Researchers have used several metrics in their studies, including acquisition spending per solicited prospect and the retention spending per customer, potential revenue streams for retention and acquisition, customers' probability to engage in a relationship and the duration of customers' relationship with the firm, and the time that elapses before a prospective customer acquires a particular service and the subsequent duration for which the customer retains service before dropping it. To understand the integrated approach to model acquisition and retention, this chapter reviews model specifications such as probit, Tobit, decision calculus, and simulation techniques. Therefore, the chapter focuses on models that help companies explore the optimal way of allocating resources on customer acquisition and retention, and the variables impacting the trade-off between customer acquisition and retention.Chapter 6: Models for customer churn. This chapter focuses on preventing customer churn, which is an important function in the CRM process of any firm. Specifically, the chapter describes customer churn models that focus on areas such as (a) modeling churn with time-varying covariates, (b) analyzing the mediation effects of customer status and partial defection on customer churn, (c) modeling churn using two cost-sensitive classifiers, (d) dynamic churn modeling using time-varying covariates, (e) factors inducing service switching, (f) antecedents of switching behavior, and (g) impact of price reductions on switching behavior. In understanding the above-mentioned topics in customer churn, this chapter reviews model specifications such as binomial logit, time-series regression, logistic regression, hierarchical logistic regression, hazard function, proportional hazards function, neural networks, decision trees, Markov models, and fuzzy logic.Chapter 7: Models for customer win-back. This chapter deals with the fourth component of CRM called customer win-back, reacquisition, reactivation, or regain – an area that lacks research interest. Specifically, the chapter will cover several models and topics that are applied in customer win-back such as (a) a conceptual approach for winning back customers, (b) adopting a lifetime value framework as a basis for customer win-back, (c) optimal pricing strategies for recapture of lost customers, and (d) a model for the perceived value of a win-back offer. The model specifications reviewed in this chapter include split-hazard function and ANOVA design.Chapter 8: Implementing CRM models. This chapter provides the implementation details about CRM models, as they apply to B2B and B2C companies. Specifically, the critical things required for an effective implementation of CRM models are data, technology enablement, a skilled workforce, and a relevant strategy to be followed based on the model outputs. This chapter also touches upon the financial benefits of building and implementing CRM models. Case studies highlighting the key factors for successful implementation are discussed.Chapter 9: The Future of CRM. This chapter discusses future directions with respect to quantitative model building and development. The chapter highlights emerging areas and topics such as social media, mobile marketing, and customized campaigns that are prime areas for future research. The popular commercial uses and expected future development trends are also identified for each of the three marketing methods. This chapter also highlights the gaps in current research and advocates areas in need of better models.

Acknowledgments

We wish to thank Alan Zhang and Bharath Rajan for their assistance and contribution in the preparation of this text. We would also like to thank our colleagues in various universities for giving us valuable suggestions in developing this book. We owe additional thanks to Renu for proofreading the manuscript.

Chapter 1

Customer Relationship Management

1.1 Introduction

Henkel, a European multinational corporation that operates in three business areas (home care, personal care, and adhesive technologies), also operates in a highly competitive, fast-moving consumer-goods industry that also has a global outreach. Some of the key operational challenges include low product margins on its products and a lack of direct customer contact, among other region-specific challenges. Henkel has managed to overcome these challenges by implementing customer relationship management(CRM) practices. Management at Henkel realized the importance of identifying and understanding the needs of individual high-value customers, in order to target, establish, develop, and retain long-lasting relationships with customers. Through these practices, Henkel has actively pursued the development of strong relationships with its customers, and at the same time increased its profitability [1].

Just like Henkel, many corporations are increasingly adopting CRM as a means to forge their competitive advantage – the ability to understand individual customer needs, and therefore to manage their marketing efforts more efficiently. Such firms are also under tremendous pressure to adjust quickly to rapid changes in the marketplace with regard to the customer, technology and marketing functions. Customers are becoming not only more value-conscious, but also less loyal and less tolerant of low service levels. Consequently, markets are becoming more fragmented, making differentiation more difficult and competition more intense. These changes are driving companies to be customer-centric, and shifting their marketing functions from product-based to customer-based ones. At the same time, the exponential growth in data storage technology has made it possible for firms to process a much more substantial amount of customer-level information. All of these changes have had a significant influence on the rapid growth, increasing the awareness and adoption of CRM worldwide.

While most firms recognize the benefits of adopting CRM practices, not all firms have been successful in their CRM implementations. We believe that having the right approach to CRM planning is critical to a firm's success. Over the years, while technology has played a key role in the success of CRM implementation, it is but one component of CRM implementation. An important part of CRM is identifying the different types of customers and then developing specific strategies for interacting with each customer. Examples of such strategies are developing better relationships with customers, not customers. That means locating and attracting customers who will be profitable, and finding appropriate strategies for unprofitable customers, which could mean eventually terminating the relationship with customers who are causing the firm to lose money.