managing customers for profit - pearsoncmg

Praise for Managing Customers for Profit“Dr. V. Kumar is one of the world’s leading experts in customer relationshipmanagement (CRM). In this book, he offers practical guidance to managerson how to implement CRM strategies in their own firms. It is a must havebook for anyone interested in developing profitable and stronger relation-ships with their customers.”

—Russ Winer, Executive Director Marketing Science Institute and William Joyce Professor of Marketing Stern School of Business,New York University

“Not only have I had the opportunity to participate in one of Dr. Kumar’spresentations on Managing Customers for Profit, but we also followedthrough with him in bringing the know-how to our company. We defi-nitely see tremendous value in his concepts and strategies described in thisbook as evidenced by successes seen in other companies. Currently, we areimplementing the framework prescribed in his book in India.”

—Maninder Singh Juneja, Senior General Manager, Head–Retail ChannelLiabilities Group, ICICI Bank Limited, India

“This book is the antidote that marketers have needed to satisfy the press-ing demand for accountability. The concepts and metrics are grounded inthe realities of customer behavior, while speaking the language of seniormanagement.”

—George S. Day, Geoffrey T. Boisi Professor; Professor of Marketing, Co-Director, Mack Center for Technological Innovation, Director, EmergingTechnologies Management Research Program

“Marketing leaders face many pressing challenges and opportunities in arapidly changing global business environment and, as a result, are always onthe lookout for fresh insight, new learning, and real-world experiences thatthey can leverage. Dr. Kumar’s new book is a must read for marketing man-agers in B2C- as well as B2B-focused businesses who are looking for astrategic approach to maximizing customer profitability. Kumar’s bookprovides a different and proven model. Marketers should have to read it.”

—Dennis Dunlap, CEO, American Marketing Association

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“Customer management has become a key business function as organiza-tions seek to complement an understanding of what they do with theirbrands with a deep knowledge of those they serve: customers. Dr. Kumar’sbook is an essential resource for those who wish to optimize their cus-tomer investments. Strategically, it ties customer-facing activities to thefirm’s objectives. Operationally, it has an insightful analysis of the activitiesthat will lead to the achievement of those objectives. And in terms ofaccountability, it has the marketing metrics to calibrate success in execu-tion, including diagnostic information for learning organizations. Dr.Kumar’s pre-eminent academic credentials combined with his extensiveindustry practice are married to make this book of immense value to bothacademics and practitioners.”

—John Roberts, Scientia Professor, Faculty of Business, University of NewSouth Wales, Sydney, Australia and Professor of Marketing, LondonBusiness School

“Firms that view their customer base as a portfolio and manage that port-folio most effectively will continue to outperform those that do not…In this important and comprehensive look at how to manage customers for profit, V. Kumar lays out the issues, dispels the myths, and providestemplates for success. I recommend you read this book before your com-petitors beat you to it.”

—Gary L. Lilien, Distinguished Research Professor of Management Scienceand Co-founder and Research Director, Institute for the Study ofBusiness Markets (ISBM), Penn State

“One of the best books in marketing that analyzes and demonstrates how tosimultaneously manage both customer loyalty and company profitability bytargeting and reallocating the four Ps of Marketing.”

—Jagdish N. Sheth, Charles H. Kellstadt Professor of Marketing, GoizuetaBusiness School, Emory University

“Today’s hyper-competitive financial services marketplace makes it moreimportant than ever to manage our business to maximize the lifetime valueof our customer relationships. V. Kumar has been a leading practitioner aswell as a pioneer in extending the state of the art in this area. Now with thepublication of this book, he has put together a compelling overview of thefundamental theory and key tools required to optimally manage customerrelationships.”

—Jim Pedrick, Senior Vice President of Strategic Marketing, ING Financial Services

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M A N A G I N GC U S T O M E R SF O R P R O F I T

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M A N A G I N GC U S T O M E R SF O R P R O F I T

STRATEGIES TO INCREASE PROFITS AND BUILD LOYALTY

V. Kumar

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© 2008 by Pearson Education, Inc.

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Dedicated, with love, to Anita & Rohan, and Prita.

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CONTENTS

Foreword . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .xiiiPreface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .xvAcknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .xviiiAbout the Author . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .xix

Chapter 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1Customer Lifetime Value . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4

Aligning Customer Management Strategies with the CLV Metric . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .8

Endnotes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .10

Chapter 2 Maximizing Profitability . . . . . . . . . . . . . . . . . . . . . . . .11Loyalty Programs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .12

How Do Loyal Customers Really Perform? . . . . . . . . . . . . . . . . . .16

Are Loyal Customers Profitable? . . . . . . . . . . . . . . . . . . . . . . . . . .17

Debunking the Myths . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .22

Where Do Firms Go Wrong? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .23

The Problem with Measuring Loyalty . . . . . . . . . . . . . . . . . . . . . .24

When to Stop Investing in a Customer . . . . . . . . . . . . . . . . . . . . .25

Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .26

Endnotes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .27

Chapter 3 Customer Selection Metrics . . . . . . . . . . . . . . . . . . . . . . . .29Traditional Metrics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .30

The Need for a Forward-Looking Metric . . . . . . . . . . . . . . . . . . .35

Introducing Customer Lifetime Value (CLV) . . . . . . . . . . . . . . . . .37

Advanced Model for Measuring CLV . . . . . . . . . . . . . . . . . . . . . . .49

Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .56

Endnotes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .56

Chapter 4 Managing Customer Profitability . . . . . . . . . . . . . . . . . .59Typical CLV Drivers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .60

A Specific B2B Case Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .61

A B2C Case Study in the Retailing Industry . . . . . . . . . . . . . . . . .66

Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .73

Endnotes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .73

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Chapter 5 Maximizing Customer Profitability . . . . . . . . . . . . . . . .75The Wheel of Fortune . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .75

Customer Selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .78

Managing Loyalty and Profitability Simultaneously . . . . . . . . . .79

Optimal Allocation of Resources . . . . . . . . . . . . . . . . . . . . . . . . . .80

Pitching the Right Product to the Right Customer at the Right Time . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .81

Preventing Customer Attrition . . . . . . . . . . . . . . . . . . . . . . . . . . .83

Managing Multichannel Shoppers . . . . . . . . . . . . . . . . . . . . . . . . .84

Linking Investments in Branding to Customer Profitability . . . .85

Acquiring Profitable Customers . . . . . . . . . . . . . . . . . . . . . . . . . . .85

Viral Marketing Strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .86

Implementation/Interaction Orientation . . . . . . . . . . . . . . . . . . .87

The Future of Customer Management . . . . . . . . . . . . . . . . . . . . . .88

The Power of CLV and the Wheel of Fortune . . . . . . . . . . . . . . . .89

Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .90

Endnotes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .90

Chapter 6 Managing Loyalty and Profitability Simultaneously . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .93

Behavioral and Attitudinal Loyalty . . . . . . . . . . . . . . . . . . . . . . . .93

Customer Segmentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .95

A Framework for Building and Sustaining Loyalty . . . . . . . . . . .99

Cultivating Attitudinal Loyalty . . . . . . . . . . . . . . . . . . . . . . . . . . .102

Linking Loyalty to Profitability . . . . . . . . . . . . . . . . . . . . . . . . . .103

Operationalizing the Framework . . . . . . . . . . . . . . . . . . . . . . . . .103

Evolution of Loyalty Programs . . . . . . . . . . . . . . . . . . . . . . . . . .107

Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .110

Endnotes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .110

Chapter 7 Optimal Allocation of Resources across Marketing and Communication Strategies . . . . . . .113

Communication Channels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .115

Type and Frequency of Communication . . . . . . . . . . . . . . . . . . .116

Resource-Allocation Strategy and CLV Maximization . . . . . . . .119

Optimal Resource Allocation: A Case Study . . . . . . . . . . . . . . . .122

Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .124

Endnotes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .125

x Contents

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Chapter 8 Pitching the Right Product to the Right Customer at the Right Time . . . . . . . . . . . . . . . . . . . . . . .127

What Companies Have Been Doing . . . . . . . . . . . . . . . . . . . . . . .128

The Question of “What Next?” . . . . . . . . . . . . . . . . . . . . . . . . . . .129

An Integrated Approach to Predicting Customer Behavior . . . .132

Increasing the Cross-Sell Ratio: Path to Profitability . . . . . . . . .138

Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .142

Endnotes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .142

Chapter 9 Preventing Attrition of Customers . . . . . . . . . . . . . . . .143Impact of Attrition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .145

Case Study: Telecommunication Industry . . . . . . . . . . . . . . . . .146

Preventing Attrition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .147

Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .161

Endnotes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .162

Chapter 10 Managing Multichannel Shoppers . . . . . . . . . . . . . . . .163Search First, Then Purchase . . . . . . . . . . . . . . . . . . . . . . . . . . . . .164

Who Are Multichannel Shoppers? . . . . . . . . . . . . . . . . . . . . . . . .166

Are Multichannel Shoppers More Profitable? . . . . . . . . . . . . . . .173

Determining the Next Channel a Customer Adopts . . . . . . . . . .174

Are Multichannel Customers More Profitable? . . . . . . . . . . . . . .182

Does Order of Channel Adoption Matter? . . . . . . . . . . . . . . . . . .183

Managing Multichannel Resources . . . . . . . . . . . . . . . . . . . . . . .184

Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .184

Endnotes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .185

Chapter 11 Linking Investments in Branding to Customer Profitability . . . . . . . . . . . . . . . . . . . . . . . . . . . .187

Aggregate versus Individual Brand Value . . . . . . . . . . . . . . . . . .190

Framework for Linking Brand Value to CLV . . . . . . . . . . . . . . . .190

How to Link the IBV to CLV . . . . . . . . . . . . . . . . . . . . . . . . . . . . .197

Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .204

Endnotes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .204

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Chapter 12 Acquiring Profitable Customers . . . . . . . . . . . . . . . . . .205Pitfalls to Balancing Acquisition and Retention . . . . . . . . . . . . .207

Solution to Balancing Acquisition and Retention: ARPRO . . . . .212

The Profit-Maximizing ARPRO Strategy . . . . . . . . . . . . . . . . . . .217

Which Is More Critical: Acquisition or Retention Spending? . . .218

Maximum Profits, Acquisition Likelihood,and Relationship Duration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .219

Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .220

Endnotes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .220

Chapter 13 Managing Customer Referral Behavior . . . . . . . . . . .223Customer Referral Value (CRV) . . . . . . . . . . . . . . . . . . . . . . . . . .225

Calculating CRV: A Typical Customer . . . . . . . . . . . . . . . . . . . . .230

Are CLV and CRV Related? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .233

Typical Marketplace Phenomenon . . . . . . . . . . . . . . . . . . . . . . .235

Managerial Implications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .245

Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .248

Endnotes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .248

Chapter 14 Organizational and Implementation Challenges . .249Organizational Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .251

Implementation Challenges . . . . . . . . . . . . . . . . . . . . . . . . . . . . .259

Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .265

Endnotes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .266

Chapter 15 The Future of Customer Management . . . . . . . . . . . .267Customer Groups . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .270

Marketing Strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .271

Aligning Marketing Strategies to Customer Groups . . . . . . . . .272

Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .280

Endnotes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .280

Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .283

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Foreword

Whilst corporations continue to strive to improve customer loyalty andcustomer profitability, the conventional customer profitability modeloffers a great opportunity for enhancement. Based on my experienceover the last two decades across three different industries, quite often, thelink between customer satisfaction, customer loyalty and customer prof-itability is tenuous. Secondly, since customer satisfaction and loyalty aremeasured across the customer base, corrective actions are designed uni-formly for all customers. However, neither the customers nor the cus-tomer behavior is uniform!

With organizational resources being scarce and improvement of mar-keting return on investment (ROI) being a key challenge for businessmanagers, it is imperative to have a fresh perspective to customer rela-tionship management (CRM) with customer profitability and the notionthat different customers should be managed and satisfied differently asits focus. This profit-based strategy draws upon robust CRM researchthat lays emphasis on future customer value. The future value of cus-tomer profitability can be measured through the customer lifetime value(CLV) metric. Dr. Kumar has developed innovative quantitativeapproaches to calculate CLV, which can be leveraged for CRM decisionsrelating to customer acquisition, retention and attrition.

CLV is a powerful tool that could potentially be the source of competi-tive advantage for organizations and provide the armory to win in themarketplace. This book is recommended for business managers inter-ested in nurturing long-lasting relationships with customers to driveprofitable growth.

—Sangeeta PendurkarChief Marketing Officer, HSBC Bank Middle East Limited

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Preface

This book is aimed at top/mid-level management of small, medium, andlarge business-to-business (B2B) and business-to-consumer (B2C)enterprises that have the power and resources to change customer man-agement strategies in their organization. This book also serves as a guidefor executives-on-the-rise to understand the importance of customer-oriented strategies.

What constitutes an effective customer management strategy? Is itenhancing customer loyalty, widening the customer base, or maximizingcustomer profitability? Although conventional wisdom suggests thatenhancing customer loyalty and widening the customer base are effectivestrategies, this book focuses on the profitability angle and establishesthat managing customers based on their profitability is the most effectiveapproach to customer management.

This book identifies three paths to profitability a firm can undertake:operational excellence, brand equity, and relationship marketing. If rela-tionship marketing is selected as a path to profitability, managing cus-tomer loyalty becomes crucial. While managing loyalty programs,companies have traditionally placed undue emphasis on maximizing cus-tomer loyalty. This book adopts a fundamentally different approachtoward customer management and demonstrates that stable healthygrowth of a company is built on the profitability of customers, not just ontheir numbers or loyalty. This book also shows that loyal customers arenot always profitable, and not all profitable customers are loyal. Therefore,when firms are developing a customer management strategy, they mustadopt an approach that closely links loyalty with profitability.

To effectively manage loyalty programs, firms use several customer selec-tion metrics, such as Recency-Frequency-Monetary value (RFM), PastCustomer Value (PCV), Share of Wallet (SOW), and Customer LifetimeValue (CLV). This book concludes that CLV outscores other metrics whenit comes to profitable customer management. CLV outscores the othermetrics in this regard because it is a forward-looking metric and becauseit factors future customer behavior into current marketing initiatives.

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xvi Preface

Empowered with CLV, firms can reevaluate and overhaul their existingcustomer management strategies. This book offers nine strategies to man-age customers profitably. These strategies aim to select the right cus-tomers, manage them profitably, and retain them through optimalallocation of resources. Furthermore, these strategies demonstrate thebenefit of pitching the right products to the right customers at the righttime, holding on to profitable customers, encouraging multichannelshopping, increasing brand value for customers, acquiring potentiallyprofitable customers, and identifying customers who provide valuethrough referrals. The knowledge obtained through implementing thesestrategies can then be leveraged to acquire prospective customers with ahigher profit potential.

Although CLV can be an effective tool to measure and manage direct(transactional) contributions made by customers, it overlooks the indi-rect (referral, word-of-mouth) contributions toward firm profitability.To maximize profit, the crucial contribution made by customer referralbehavior has to be carefully monitored and managed. This book intro-duces Customer Referral Value (CRV) as a metric that firms can use tomaximize the indirect contributions made by customers. CLV, used inconjunction with CRV, will enable marketers to implement strategicallydesigned marketing initiatives to profitably manage customer loyalty.

This book identifies organizational and implementation challenges thatfirms might encounter when adopting a CLV-based approach and sug-gests appropriate guidelines to overcome such challenges. Firms need toadopt an “interaction-orientation” approach when dealing with cus-tomers. By establishing a strong firm-customer relationship, and by treat-ing customers as a resource, managers can effectively implement theCLV-based strategies. Because CLV is a dynamic approach, marketingstrategies have to be constantly updated for sustained profitability. Thisbook recommends a balanced approach, keeping in mind the ethicalissues involved in collecting and managing customer-level information.This book also outlines issues that firms might potentially face whenimplementing a CLV-based approach and suggests the necessary strate-gies to stay ahead of the competition.

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Organization of the Book

This book adopts a strategic approach toward profitable customer man-agement and illustrates the strategies needed to manage customers effi-ciently. It presents techniques to aid in customer-oriented marketinginitiatives using the concept of Customer Lifetime Value. The book con-sists of 15 chapters.

Chapter 1 introduces key concepts of customer management. It describesthe different paths to profitability and identifies relationship marketingas the one that leads to profitable customer management. It also dis-cusses the role of loyalty programs in bringing firms and customerscloser to each other. Chapter 2 links loyalty with profitability and dis-cusses the drivers of profitable customer loyalty. After establishing theneed for managing customers for profit, Chapter 3 reviews the popularmetrics used to measure customer loyalty. The concept of Customer Life-time Value is discussed, as is how to measure CLV. Chapter 4 describeshow to build and sustain profitable customer loyalty and calls for a fun-damental outlook change to manage customer loyalty. Chapter 5 outlinesnine strategies available to managers to maximize CLV. These strategieswill help firms decide how to select the best customers (Chapter 5), makeloyal customers profitable (Chapter 6), optimally allocate resources(Chapter 7), pitch the right products to the right customers at the righttime (Chapter 8), prevent customer attrition (Chapter 9), encouragemultichannel shopping behavior (Chapter 10), maximize brand value(Chapter 11), and link acquisition and retention to profitability (Chap-ter 12). Chapter 13 introduces the concept of Customer Referral Value(CRV), which firms can use to measure the indirect impact (referrals,word-of-mouth) made by customers toward the firm’s profit. Chapter 14discusses potential organizational and implementation challenges whenadopting a CLV-based approach, and Chapter 15 covers potential issuesthat need to be addressed to sustain profitable customer management.

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Acknowledgments

I want to thank Andrew Petersen, Denish Shah, Morris George, BharathRajan, Magesh Nandagopal, and Saurabh Bhargava for their assistance in the preparation of this manuscript. I also want to thank Archana Muppaka for her assistance in the operational details. I would particu-larly like to thank Keith Cline and Renu for copy editing the manuscriptand Jovana San Nicolas-Shirley for managing the publication process.I also want to thank my coauthors in each of the studies referenced in thisbook for their contributions. I am also thankful to Martha Cooley for hersupport in the process of streamlining the content of this book. Finally,special thanks are owed to Peter Fader for making this book happen,and Dave Reibstein and George Day for their encouragement and guid-

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ance. I am deeply indebted to the editorial team of Prentice Hall for accepting this manuscript for publication.

About the Author

Dr. V. Kumar (VK) is the inaugural holderof the Richard and Susan Lenny Distin-guished Chair Professor in Marketing, andthe Executive Director of the Center forExcellence in Brand and Customer Man-agement, in J. Mack Robinson College ofBusiness at Georgia State University. Pre-viously, Dr. Kumar was the ING chair pro-fessor of marketing and the executivedirector of the ING Center for FinancialServices in the School of Business at theUniversity of Connecticut. He was recentlyranked among the top five marketingscholars worldwide based on his researchproductivity. Dr. Kumar has been recog-

nized with many teaching and research excellence awards and has pub-lished numerous articles in premier journals of marketing, such as theHarvard Business Review, Journal of Marketing, Journal of MarketingResearch, Marketing Science, and Operations Research. He has won severalawards for his research publications in scholarly journals, including theDon Lehmann Award twice for the best paper published in the Journalof Marketing/Journal of Marketing Research in a two-year period and theMSI/Paul H. Root Award twice for two different Journal of Marketingarticles contributing to the best practice of marketing. He has coau-thored more than 100 articles, book chapters, and textbooks, such asMarketing Research, International Marketing Research, and CustomerRelationship Management: A Databased Approach. He is currently on theeditorial review board of several scholarly journals and has lectured onmarketing-related topics in various universities and organizations in theUnited States, Europe, Australia, and Asia. His current research focuseson international diffusion models, customer relationship management,customer lifetime value analysis, sales and market-share forecasting,international marketing research and strategy, marketing resource allo-cation, sales promotion, and interaction orientation.

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Dr. Kumar is also a consultant to many Fortune 500 firms, for whom he has helped design suitable marketing strategies to identify the mostprofitable customers. His work with IBM and P&G has been recognizedby INFORMS as award-winning entries in the 2006 and 2007 PracticePrize Competition, respectively. Recently, Dr. Kumar was conferred withtwo Lifetime Achievement Awards from the American Marketing Association Special Interest Groups for his contributions to the fields ofmarketing strategy and interorganizational marketing. He received hisPh.D. from the University of Texas at Austin.

Dr. Kumar can be reached by email at ([email protected]).

xx About the Author

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1

1Introduction

“Customer is king” is a centuries-old corporate saying.Not much has changed in the current century other thanthe fact that your company’s customer can also be themost sought after. Because of advances in technology andglobalization, you never know in what form competitionwill emerge to attract your customers. For example, theincumbent books-retailer leader Barnes & Noble wasovershadowed by a then-innocuous Internet-basedcompany, Amazon; IBM was challenged by the newentrant Dell; and American car companies are currentlyrunning huge losses at the expense of Japanese andKorean car manufacturers.

Acommon factor governing the success or failure of any firm isalmost always the ability of the firm to service its customersbetter or offer superior value propositions. So, what’s new? It is

common wisdom that customer relationship initiatives are expected todeliver superior financial performance. However, reality often beliesexpectation.

Consider Continental Airlines, for example.1 In late 1994, Continentalhad lost an average $960 million per year for the previous four years.Customers were annoyed by the way the airline was being operated—unreliable, dirty, and frequently losing passenger baggage. TheDepartment of Transportation ranked Continental last on the list basedon its on-time airline rankings. By March 1995, Continental had movedfrom last to first in the on-time rankings. In 2000, Continental Airlineswas ranked number one in customer satisfaction by J. D. Power and

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Associates. An unprecedented recovery! The biggest underlying successfactor was Continental’s ability to win back customer satisfaction.There was no doubt that Continental had a winning customer manage-ment formula. But, was the formula profitable? What about the cost ofsatisfying the customers? Between 2001 and 2005, Continental Airlinesreported an average net loss of about $200 million per year.

In the mid 1990s, Dell Corporation introduced a novel e-commercebusiness model.2 The company’s strategy of selling directly over theInternet with no intermediaries (such as retail outlets) was the mosttalked about success story of the early twenty-first century. Dell’srevenues and earnings grew by more than 30% year after year, and thecompany reported a return on invested capital of 243% for 2000.Fortune magazine listed Dell as America’s third-most admired com-pany. Television audiences in the United States were treated to an exten-sive advertising campaign by Dell that showed Dell employees puttingin long hours in their customer contact centers to service customers.Was Dell’s success profitable in the long run? Dell’s stock has tumbledmore than 40% over the past two years on decreased sales and slimmerprofit margins. In March 2007, Dell reported a 33% drop in fourth-quarter profits and warned that growth and profit margins will remain“under pressure” for the next few quarters.

A common underlying theme of these two examples is the importanceof sustaining successful customer management initiatives in the longrun. In other words, although it might be possible to keep customershappy and loyal in the short run, the greater challenge often lies inachieving that objective with both growth and profits in the long run.

It may be argued that operational efficiencies are also important. Wedon’t deny that fact. However, operational efficiency cannot hold prece-dence over customer focus. Consider the case of First USA & CapitalOne, for example.3 Both companies are prominent players in the creditcard industry. However, what sets them apart is their customer man-agement approach. First USA is “laser focused on operating efficiencyand to pass those savings on to customers,” according to formerChairman Richard Vague. In contrast, Capital One’s primary goal is to“deliver the right product, at the right price, to the right customer, atthe right time.” This is an interesting paradox between two players ofthe same industry selling exactly the same product.

2 Managing Customers for Profit

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First USA transacted its business with little differentiation across its cus-tomers. This approach was consistent with its corporate structure, whichwas organized around products or functions. The company’s customeracquisition strategy was based on luring customers from other creditcard companies and using affinity partners. The company did not makean investment in archiving customer data. Therefore, it lacked the abil-ity to compute individual customer profitability. Employees were man-dated to try to retain all customers irrespective of whether they appearedas good or bad prospects in the long run. In 1999, the bank discontinuedthe policy of allowing a grace period for late payments and raised late-fee penalties. This policy was applied uniformly across the board, acrossall customers. Not surprisingly, a mass exodus of customers (both prof-itable and unprofitable) resulted. The company was later forced torevoke its policy. However, the damage was done.

In contrast, Capital One’s primary focus is customers. The companyconducts business by microsegmenting its customer base so that eachcustomer can be individually serviced in consonance with the cus-tomer’s value potential. Furthermore, Capital One set up a customerdata warehouse that has an unmatched ability to mine any customer’sinformation in a matter of seconds. For instance, when a customercalls, computers instantly access the full history of the customer andcross-reference it with millions of other customers. If a valuable cus-tomer calls to cancel a credit card, the call-routing system automaticallyrattles out three attractive counteroffers that the customer service rep-resentative can use to negotiate. In a nutshell, each customer is treateddifferently. Capital One’s deep commitment to knowing its customer isevident from the fact that in 2000, Capital One ran 45,000 tests onproduct variants, procedural changes, and customer interactions.

So, what was the financial consequence of these two approaches? As thecredit environment worsened, First USA’s customer attrition rate grewby 50%, contributing to a 23% decline in revenue in 2000, and thecompany’s first ever loss. On the other hand, Capital One earned 40%more interest income from each customer as compared to First USA,with double the profit margin, despite being half the size.

The bottom line is that the bottom line matters. To manage and sustainprofitability, we need to come up with the right marketing strategies,

Chapter 1 Introduction 3

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backed by the right marketing metrics. Although there are 50+ impor-tant metrics that every executive should know,4 this book focuses onone particular metric: the Customer Lifetime Value (CLV) metric. Thisbook takes an in-depth look at how marketing strategies based on thispowerful metric can help manage customer relationship and profitabil-ity simultaneously.

Customer Lifetime ValueCustomer Lifetime Value refers to the net present value of future profitfrom a customer. The beauty of the metric lies in the fact that it is forward-looking, unlike traditional measures based on past contribu-tions to profit. Hence, it enables marketers to adopt the right marketingactivities today to increase future profitability. Moreover, CLV is theonly metric that incorporates all the elements that drive profitability:revenue, expense, and customer behavior. Thus, the metric keeps thefocus on the customer (rather than the product) as the driver of prof-itability. In fact, in recent times, the importance of CLV has evolvedfrom merely being an important metric to a way of thinking and ofdoing business.

Figure 1.1 shows a typical life cycle curve of a customer. If a manager attime (t) were to make a managerial decision regarding this customer,would it make sense to decide based on the customer’s past customervalue, or would it make sense to decide based on the customer’s futurevalue. If the customer’s future revenue is expected to drop as comparedto past revenue (as seen in Figure 1.1), it may make sense moving for-ward to reduce the marketing expenditure for this customer.


Acquisition Retention Attrition

Time = t

CustomerValue

Time

Figure 1.1 Typical life cycle of a customer

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Because the metric is forward-looking, the value associated with theCLV is an estimate or a prediction. Therefore, it is imperative thatproper methods be employed to measure CLV.

CLV can be measured in two fundamental ways: top down andbottom up.

Top-Down ApproachAs shown in Figure 1.2, the top-down approach involves estimating theaverage customer equity (or lifetime value) of the customer. This can beaccomplished by identifying and measuring the drivers of customerequity at the firm or customer segment level. For example, Lemon, Rust& Zeithaml define the drivers of customer equity as comprising thevalue equity, brand equity, and relationship equity.5 These drivers aremeasured based on the customer’s objective and subjective assessmentsof these three drivers of customer equity. The drivers are typically meas-ured using a survey-based methodology because the drivers includesubjective assessments of the customer that are not directly observed(such as the customer’s attitude toward the firm’s brand and the cus-tomer’s brand awareness). It is practically infeasible to measure thesedrivers from each customer through a questionnaire. This is particularlytrue for large firms having millions of geographically dispersed cus-tomers. Hence, the drivers are typically measured on a small sample ofcustomers and then extrapolated across the population to arrive at thecustomer equity at the firm level or the customer segment level.

The customer equity at the firm or the customer segment level can thenbe divided by the total number of customers of the firm/segment toarrive at the average lifetime value of a customer.

Drivers of customer equity

Divide by the number of customers

Average customer lifetime value

Total customer equity

Figure 1.2 Top-down approach to measuring CLV

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Another way to compute customer equity using the top-downapproach is by applying observed aggregate measures pertaining to cus-tomers at the firm level. These measures include the total number ofcustomers of the firm, their growth, the average margin per customer,the average customer retention rate, the average customer acquisitioncost, and the discount rate for the firm.6 Using these measures, firmscan easily calculate customer equity at the firm level.

The main benefit of top-down approaches is the ability to measure cus-tomer equity without the need for customer-level information for allcustomers of the firm. Such an approach offers a simple way to computethe overall customer equity of a firm. However, a potential drawback isthat all customers of the firm (or customer segment level) have the sameCLV. Therefore, they are all treated as equal. In reality, customer valuescan differ significantly within the customer base (or segment). In fact,most firms swear by the Pareto principle (the 80/20 rule). That is, 20%of customers usually provide 80% of the total value to the firm. In sucha scenario, it is advisable to adopt a computation method that recog-nizes the individual-level differences in customer value.

Bottom-Up ApproachAs shown in Figure 1.3, the bottom-up approach involves first estimat-ing the lifetime value of each customer of the firm. Thereafter, the indi-vidual CLV measures are summed up across the customerbase/segments to arrive at the total customer equity at the firm/customer segment level.


Customer equity

Sum up the CLV of all customers

Measure individual CLV

Customer transaction data

Figure 1.3 Bottom-up approach to measuring CLV

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A key requirement of this approach is that it needs data at the customerlevel. Not all firms may meet this criterion. Further, estimation of CLVfor each customer could be time-consuming, especially for large firmswith millions of customers. However, the bottom-up approach offersrich customer-level insights (such as individual customer behavior,response to promotion, and individual customer value) that might haveotherwise been lost due to aggregation under the top-down approach.Our contention is reinforced by new challenges infused by the changingbusiness landscape of the twenty-first century, as shown in Figure 1.4.


Sell products

Traditional Business Twenty-First Century Business

Market orientation

Philosophy

Orientation

Management Criteria

Strategy Motivation

Selling Approach

Strategy Outcome

Portfolio of products

Increase customer satisfaction

Increase customer profitability

How many customers can we sell this product to?

How many products can we sell to this customer?

Sales maximization

Interaction orientation

Serve customers

Portfolio of customers

Customer Lifetime Valuemaximization

Figure 1.4 Changing business landscape of the twenty-first century

The shift in focus from products to customers has been a significantdevelopment of the twenty-first century. State-of-the-art marketing isnow concerned with servicing each customer differently. These devel-opments have been accelerated by technological advances. Increase in computation power and reduction in data-storage costs haveprompted several companies to set up huge IT infrastructures toarchive customer-level data. The proof lies in the ubiquity of grocerycards, retailer credit cards, and point-based loyalty schemes (such asairline frequent-flyer programs). All these measures are a means to acommon end: collection of customer-level data in an effort to know thecustomer better. So, if you don’t know your customers, your competi-tion will! Further proof comes from companies that have succeeded in

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knowing and managing their customers at the individual level. Suchorganizations have been richly rewarded because of an improvement inboth cost and profit efficiencies. For example, Harrah’s Entertainment,a prominent casino and gaming resort chain, has consistently outplayedits competition and recorded impressive financial performance despitea weak economy. The critical success factor: superior ability to cater toits customers based on a forward-looking metric.

The concepts covered in this book apply to disparate relationships,regardless of whether the customer is contractual or noncontractual,whether the firm sells a product or a service, or whether transactionswith specific customers occur repeatedly or are just one-off (and perhapswith follow-up services). CLV can be measured across all these situations, but how it is measured will vary. Chapter 3, “Customer SelectionMetrics,” covers CLV measurement issues across various scenarios.

Therefore, the adoption of the CLV metric seems to be not only suffi-cient but a necessary condition of business in the twenty-first century.Given the increasing focus on customers, this book strongly advocatesthe bottom-up approach to CLV estimation. The bottom-up approachenforces customer-centricity within an organization, as you will dis-cover in the subsequent chapters of this book. The full potential of theCLV metric is realized when all customer-level marketing strategies ofthe firm are aligned and integrated with the CLV metric.

Aligning Customer Management Strategies withthe CLV MetricFigure 1.5 illustrates a typical customer life cycle scenario. Based on thelocation of the customer on the life cycle plot, the firm can extendacquisition, retention, or customer win-back strategies in an effort tospeed acquisition, increase revenue during retention, and delay attri-tion. The net result is a lift in customer value. This is denoted as strate-gic impact in Figure 1.5.


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The rest of this book takes an in-depth look at powerful customer-levelstrategies relevant to virtually any business in the business-to-consumer(B2C) or business-to-business (B2B) domain. With regard to the cus-tomer acquisition stage, this book covers how firms can go aboutacquiring profitable customers, the best metric to use while acquiringcustomers, and how to use customer referral as a strategic tool toacquire new customers. With regard to the retention stage, this bookexamines how firms can manage customer value, loyalty, and profitabil-ity simultaneously; that is, how can they pitch the right product to theright customer at the right time. With regard to the customer attritionstage, this book discusses dynamic proactive strategies to prevent losingcustomers. Deployment of these customer-level strategies has resourceallocation consequences that lead to greater cost and profit efficiencies.This book talks about reallocation of resources across different channelsto increase the level of interaction and hence spending per customer.Resource allocation across customers helps in the prudent reallocation of


Traditional CLV Curve

Return on Marketing Investments

Acquisition Strategies (Chapters 3, 12, and 13)

Retention Strategies (Chapters 2, 4, 5, 6, and 8)

Attrition Strategies (Chapter 9)

Across Channels (Chapter 10)

Organizational and Implementation Challenges

(Chapter 14)

Across Customers (Chapter 7)

Across Marketing Activities (Chapters 11 and 12)

Customer Value

Time

OPTIMAL RESOURCE ALLOCATION

Strategic Impact

Figure 1.5 Typical customer life cycle scenario

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limited marketing budgets from low-profit customers to customers whoare expected to provide higher profits in the future. Resource allocationacross marketing activities seeks to balance marketing budgets acrossacquisition and retention strategies. The net result of all customer-levelinitiatives is a higher return on marketing activities. However, this isoften an impediment in the wake of strategy-implementation chal-lenges at the organizational level. These challenges have been addressedin a separate chapter of the book. The book chapters relevant to eachstrategy/topic are indicated in parentheses in Figure 1.5. All strategiesare state-of-the-art, with a proven track record of unprecedented suc-cess when implemented at select Fortune 500 corporations.

Endnotes1 The Continental Airlines example is based on the following sources: (a) B.

O’Reilly, “The Mechanic Who Fixed Continental,” Fortune, April 23, 1999:176–186; (b) Continental Airlines annual reports.

2 The Dell example is based on the following sources: (a) Rangan V. Kasturi andMarie Bell, “Dell-New Horizons,” Harvard Business Review Case Study 9-502-022,October 10, 2002; (b) Dell Corporation annual reports; (c) Kelley Rob, “Dellreports steep decline in profits,” CNNMoney.com, March 1, 2007.

3 George Day, “Creating a Superior Customer-Relating Capability,” MSI WorkingPaper Series, Issue One, No. 03-001 (2003): 21–36.

4 Paul W. Farris, Neil T. Bendle, Philip E. Pfeifer, and David J. Reibstein. Marketing

5 Katherine N. Lemon, Roland T. Rust, and Valarie A. Zeithaml, “What DrivesCustomer Equity,” Marketing Management, Spring 2003: 21–25.

6 Sunil Gupta and Donald R. Lehmann, Managing Customers as Investments


001_0132352214_01.qxd 12/5/07 9:37 AM Page 10

Metrics: 50+ Metrics Every Executive Should Master (Prentice Hall, 2006).

(Prentice Hall, 2006).

Index

283

AA&P, 274acquiring customers. See customer

acquisitionacquisition rate, 207

profitability versus, 207-209across-customer strategies

(maximizing CLV), 76active customers, probability of,

44-45active word-of-mouth marketing, 21actual behavior (making referrals),

intentions versus, 225-226aggregate approach, calculating

Customer Lifetime Value (CLV),40-43

aggregate brand value, individualvalue versus, 190

airline industry, loyalty programs in,14, 23

Albertsons, 14aligning customer management

strategies with Customer LifetimeValue (CLV), 8-10

allocating resources. See marketingresource allocation strategy (maximizing CLV)

Allocating Resources for Profit. SeeARPRO strategy

always-a-share scenario (customerattrition), 144, 149-150

Amazon, 1American Airlines, 14American Express, 258, 276

AMGC (average gross contributionmargin), calculating, 45

AOL, 149Apple, 144, 149, 195Apple iTunes, 251ARPRO (Allocating Resources for

Profit) strategy, 212-218AT&T, 149, 277attitudinal loyalty, 21, 79

behavioral loyalty versus, 93-94brand value and, 189customer referral behavior and,

86-87, 223-248measuring and cultivating, 102

attrition. See customer attrition;customer retention strategy (maximizing CLV)

average gross contribution margin(AMGC), calculating, 45

average inter-purchase time (CLVdriver), 63

BB2B (business-to-business) setting

bidirectional communication, 118CLV drivers, 61-65loyalty programs in, 12marketing resource allocation

strategy, 122-124B2C (business-to-consumer) setting

bidirectional communication, 118CLV drivers, 66-73loyalty programs in, 12

Bank of America, 235

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Barnes & Noble, 1Bayesian estimation, 131behavioral loyalty, 21, 79, 170

attitudinal loyalty versus, 93-94brand value and, 189building, 99-102customer referral behavior and,

86-87, 223-248BellSouth, 149bi-directional communication (CLV

driver), 65, 118Blockbuster, 159BMG, 251Boeing, 256Boots, 14bottom-up approach, measuring


BP, 193brand advocacy, 197

as part of brand behavior, 195brand affect, as part of brand

attitude, 193brand attitude, 193-194brand awareness, as part of brand

knowledge, 192brand behavior, 195-196brand behavior intention, 194-195brand equity, 5, 65

customer equity and, 189brand image, as part of brand

knowledge, 192-193brand intimacy, 193brand knowledge, 192-193brand loyalty, as part of brand

behavior, 195brand price premium behavior, as

part of brand behavior, 195brand satisfaction, 197brand trust, as part of brand

attitude, 193

brand valueaggregate versus individual

value, 190individual brand value, linking to


loyalty and, 189profitability and, 187-189

brand value strategy (maximizingCLV), 85, 187-204

British Airways, 194business dimension (implementa-

tion challenges to CLV-basedframework), 251-253, 255-258

business-to-business (B2B) settingbidirectional communication, 118CLV drivers, 61-65loyalty programs in, 12marketing resource allocation

strategy, 122, 124business-to-consumer (B2C) setting

bidirectional communication, 118CLV drivers, 66-73loyalty programs in, 12

CCaesar’s Palace, 251calculating

average gross contribution margin (AMGC), 45


aggregate approach, 40-43bottom-up approach, 6-8components of, 48-49in contractual relationships,

54-55individual-level approach

approach, 43-47in one-time purchases with

add-on products/services, 55


016_0132352214_Index.qxd 12/5/07 9:46 AM Page 284

purchase-frequency model,49-54

top-down approach, 5-6Customer Referral Value (CRV),

230-233net present value (NPV), 45-46

calibration sample (logistic regression model), 151

campaign-based marketing strategies, 271

segmented customers (in customer management evolution) and, 274-275

Capital One, 2-3casino industry, loyalty programs

in, 14channel adoption, order of, 183-184channel adoption drivers, 174-175

channel-adoption duration, 181channel-related attributes,

175-177customer demographics, 179-180frequency-related attributes, 179implementation of, 181-182purchase-related attributes,

177-179channel-adoption duration (channel

adoption drivers), 181channel mix. See communication;

marketing resource allocationstrategy (maximizing CLV)

channel-related attributes (channeladoption drivers), 175-177

channelsin intervention strategy, 159multiple channels

benefits of, 163-164communication via, 170-172research shoppers and,

164-166choice model strategy, 128, 133

churn. See customer attritionCLV. See Customer Lifetime

Value (CLV)CM. See customer managementCoca-Cola, 192, 194

customer management evolution,267-268

market segmentation, 271communication. See also marketing

resource allocation strategy (maximizing CLV)

frequency of, 116, 179bidirectional communication,

118inter-contact time, 117risk of overcommunication,

116-117web-based contacts, 118-119

in linking individual brand valueto Customer Lifetime Value(CLV), 199

modes of, 115-116via multiple channels, 170-172product offering strategies,

128-129communication of initiatives

(implementation challenges toCLV-based framework), 260-261

competitor actions (ARPRO strategy), 216

contact-mix interactions, 172contact strategy. See communica-

tion; marketing resource allocationstrategy (maximizing CLV)

Continental Airlines, 1contractual relationships,

calculating Customer LifetimeValue (CLV), 54-55

contribution margin, as customerbehavior outcome, 197

cost of intervention strategy, 158

Index 285

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cross-buying (CLV driver), 62, 70,167, 178

cross-selling strategy, 129, 138-141cruise lines, loyalty programs in, 15CRV (Customer Referral Value), 87,

225-230aspects of, 227-230calculating (telecommunications

company example), 230-233relationship with Customer

Lifetime Value (CLV), 233-235implementing referral

programs based on, 235-245CSS (Customer Spending Score), 249customer acquisition strategy

(maximizing CLV), 85-86, 205-220balancing with customer

retention, 219-220acquisition versus retention

spending, 218-219ARPRO (Allocating Resources

for Profit), 212-218independent versus integrated

strategies, 211-212law of diminishing returns,

207-209selection bias, 212short-term versus long-term

profitability, 209-211with high Customer Lifetime

Value (CLV), 203customer actions (ARPRO

strategy), 215customer attrition, 143-145. See also

customer retention strategy (maximizing CLV)

impact of, 145-146preventing, 147

intervention strategy, 155-161predicting churn, 147-154

telecommunications industrycase study, 146-147, 160-161

customer behavior outcomes,linking brand value and CustomerLifetime Value (CLV), 196-197

customer characteristicsARPRO strategy, 215CLV driver, 61of multichannel shoppers,

167-170customer churn. See customer

attritioncustomer concept (interaction

orientation component), 256customer demographics

channel adoption drivers,179-180

for multichannel shoppers, 172customer empowerment (interac-

tion orientation component), 256customer equity. See also Customer

Lifetime Value (CLV)brand equity and, 189drivers of, 5, 65

customer groups (customer management evolution), 269-271

aligning marketing strategieswith, 272-277

customer interaction strategy (maximizing CLV), 87-88, 249-264

Customer Lifetime Value (CLV),4-5, 25, 36-40. See also customerequity

aligning customer managementstrategies with, 8-10

bottom-up approach, 6-8calculating, 40-48

aggregate approach, 40-43components of, 48-49


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in contractual relationships,54-55

individual-level approach,43-47

in one-time purchases withadd-on products/services, 55

purchase-frequency model,49-54

combining with Share of Wallet(SOW), 122

drivers of, 60-61business-to-business (B2B)

case study, 61-65business-to-consumer (B2C)

case study, 66-73implementation challenges for

frameworkbusiness dimension, 251-258communication of initiatives,

260-261data-driven factors, 260IBM example, 249-251metrics dashboards, 261-264people dimension, 259

in intervention strategy, 156linking to individual brand value,

190-191brand attitude, 193-194brand behavior, 195-196brand behavior intention,

194-195brand knowledge, 192-193customer behavior outcomes,

196-197implementation of, 197-203

maximizing strategies, 75-78customer acquisition strategy,

85-86, 205-220customer referral strategy,

86-87, 223-248

customer retention strategy,83, 143-161

customer selection strategy,78-79

future of customer management, 88-89, 267-280

Individual Brand Value (IBV)strategy, 85, 187-204

interaction-orientationapproach strategy, 87-88,249-264

loyalty program strategy,79-80, 93-110

marketing resource allocationstrategy, 80-81, 113-124

multichannel shopping management strategy, 84-85,163-184

purchase sequence predictionstrategy, 81-83, 127-141

relationship with CustomerReferral Value (CRV), 233-235

implementing referral programs based on, 235-245

for strategic decisions, 59top-down approach, 5-6

customer managementaligning with Customer Lifetime

Value (CLV), 8-10evolution of, 268-269

Coca-Cola example, 267-268customer groups, 270-271marketing strategies, 271-277

future of, 88-89, 267-280harmful uses of, 277-278

customer probability cube, 133-134customer profitability metrics,

262-264

Index 287

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customer purchase behavior. Seealso purchase sequence predictionstrategy (maximizing CLV)

cross-selling strategy, 138-141predicting, 129

accuracy, lack of, 130-132joint-probability strategy,

132-137sample size, 131-132

customer referral strategy (maximizing CLV), 86-87, 223-248

Customer Referral Value (CRV), 87,225-230

aspects of, 227-230calculating (telecommunications

company example), 230-233relationship with Customer

Lifetime Value (CLV), 233-235implementing referral pro-

grams based on, 235-245customer referrals, as customer

behavior outcome, 197customer relationships, effect on

profit and growth, 1-4customer retention strategy

(maximizing CLV), 83, 143-161balancing with customer

acquisition, 219-220acquisition versus retention

spending, 218-219ARPRO (Allocating Resources

for Profit), 212-218independent versus integrated

strategies, 211-212law of diminishing returns,

207-209selection bias, 212short-term versus long-term

profitability, 209-211

customer segmentation, 95-98by profitability and purchasing

behavior, 101-102Share of Wallet (SOW),

combining with CustomerLifetime Value (CLV), 122

customer selection metrics. Seeloyalty metrics

customer selection strategy (maximizing CLV), 78-79

Customer Spending Score (CSS), 249

customer-centric approach, chang-ing from product-centric approach

business dimension of, 251-258people dimension of, 259

customer-initiated contacts (multichannel shopper characteristics), 169

customer tenure (multichannelshopper characteristics), 170

customer value management (interaction orientation component), 257

customersactive customers, probability of,

44-45firing, 277-278loyal customers. See loyal

customers; loyalty programsCVS/Pharmacy, 14

Ddata-driven factors (implementation

challenges to CLV-based framework), 260

defection. See customer attritionDell Corporation, 1-2, 144, 149demographics. See customer

demographics


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diminishing returns, law of, 207-209direct marketing expenditures,

optimizing, 205-206direct referrals, 227discount rate (d), calculating

Customer Lifetime Value (CLV), 48Disney Cruise Line, 15distribution channels. See channelsDorothy Lane Market, 12duration of relationship (CLV

driver), 70dynamic churn model, 83

EEarthLink, 235Eastman Kodak, 27480/20 rule, 6EMI, 251endogeneity, 53entire-market customers

(in customer management evolution), 270

mass-marketing strategies and,273-274

exchange characteristics (CLV driver), 60

Ffailure of loyalty programs, reasons

for, 23-24firing customers, 277-278firm actions (ARPRO strategy), 215First USA, 2-3focused buying (CLV driver), 62Ford, Henry, 270frequency of purchase (CLV

driver), 71frequency-related attributes

(channel adoption drivers), 179

frequent-flier programs. See loyaltyprograms

future of customer management,88-89, 267-280

G–HGeneral Motors, 271Grand Casinos, 15grocery stores, loyalty programs

in, 14growth, effect of customer

relationships on, 1-4

Harley Davidson, 195Harrah’s Entertainment, 8, 14,

251, 273hazard models (predicting churn),

151-154heterogeneity, 53Hewlett-Packard, 256Hilton, 14hotel industry, loyalty programs

in, 14Hyatt, 14

IIBM, 1, 256-258, 262-264, 275-276IBV (Individual Brand Value)

strategy (maximizing CLV), 85,187-204

indirect referrals, 227individual brand value

aggregate value versus, 190linking to Customer Lifetime

Value (CLV), 190-191brand attitude, 193-194brand behavior, 195-196brand behavior intention,

194-195

Index 289

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brand knowledge, 192-193customer behavior outcomes,

196-197implementation of, 197-203

Individual Brand Value (IBV) strategy (maximizing CLV), 85,187-204

individual customers (in customermanagement evolution), 270

interaction-based marketingstrategies and, 275-277

one-to-one marketing strategiesand, 272-273

individual-level approach,calculating Customer LifetimeValue (CLV), 43-47

ING Direct, 277intentions (making referrals), actual

behavior versus, 225-226inter-contact time, 117inter-purchase time (CLV driver),

63, 144interaction-based marketing

strategies, 272advantages of, 278-280individual customers (in

customer management evolution) and, 275-277

interaction orientation, 254components of, 256-258improving, 255-256

interaction-orientation approachstrategy (maximizing CLV), 87-88,249-264

interaction response capacity (interaction orientation component), 256

intervention strategy, preventingcustomer attrition, 155-161

investment in loyal customers,stopping, 25-26

IPT (inter-purchase time), 63, 144

J–Kjoint-probability strategy

(purchase behavior predictions),132-137

customer probability cube,133-134

likelihood function, 133purchase sequence analysis, 132technology manufacturer case

study, 134-137traditional models versus, 137

Knox, Steve, 224

LLatin Pass, 24law of diminishing returns, 207-209lifetime duration, as customer

behavior outcome, 196lifetime value. See Customer

Lifetime Value (CLV)likelihood function (purchase

behavior predictions), 133Linux, 256logistic regression model (predicting

churn), 150-151long-term profitability, short-term

profitability versus, 209-211lost-for-good scenario (customer

attrition), 144, 148-149Louis Vuitton, 196loyal customers. See also loyalty

programsmyths about

debunking, 22-23lower cost of service for, 18-19marketing efforts by, 20-21price sensitivity of, 19-20

profitability of, 17-18stopping investment in, 25-26


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loyalty. See also attitudinal loyalty;behavioral loyalty

brand loyalty, 195brand value and, 189profitability and. See also

Customer Lifetime Value (CLV)behavioral loyalty versus atti-

tudinal loyalty, 93-94customer segmentation, 95-98linking in loyalty

programs, 103loyalty instruments (CLV driver), 64loyalty metrics, 24-25, 29

compared, 79CLV (Customer Lifetime Value),

36-40calculating, 40-55

PCV (Past Customer Value),34-35

drawbacks to, 36RFM (Recency-Frequency-

Monetary value), 30-32drawbacks to, 36

SOW (Share of Wallet), 32-33drawbacks to, 36

loyalty programs. See also loyal customers

effect of, 16evolution of, 107-110framework for, 99

attitudinal loyalty, measuringand cultivating, 102

behavioral loyalty, building,99-102

loyalty and profitability,linking, 103

two-tier rewards strategy,103-106

history of, 12-16

maximizing CLV with, 79-80,93-110

profitability and, 11-12reasons for failure, 23-24

Mmarket orientation, 254market segmentation (in customer

management evolution), 270-271campaign-based marketing

strategies and, 274-275marketing

communication. Seecommunication

decisions, stopping investment inloyal customers, 25-26

efforts by loyal customers, 20-21optimizing direct marketing

expenditures, 205-206marketing actions (CLV driver), 61marketing contact frequency (CLV

driver), 64marketing cost (M), calculating

Customer Lifetime Value (CLV), 48marketing resource allocation

strategy (maximizing CLV), 80-81,113-124. See also communication

marketing strategies (customermanagement evolution), 269-272

advantages of interaction-basedmarketing, 278-280

aligning with customer groups,272-277

Marks & Spencer’s, 14Marriott, 14mass-marketing strategies, 128, 271

entire-market customers (in customer management evolution) and, 273-274

Index 291

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maximizing Customer LifetimeValue (CLV), 75-78

customer acquisition strategy,85-86, 205-220

customer referral strategy, 86-87,223-248

customer retention strategy, 83,143-161

customer selection strategy,78-79

future of customer management,88-89, 267-280

Individual Brand Value (IBV)strategy, 85, 187-204

interaction-orientation approachstrategy, 87-88, 249-264

loyalty program strategy, 79-80,93-110

marketing resource allocationstrategy, 80-81, 113-124

multichannel shopping manage-ment strategy, 84-85, 163-184

purchase sequence predictionstrategy, 81-83, 127-141

measuringaverage gross contribution

margin (AMGC), 45Customer Lifetime Value (CLV),

40-48aggregate approach, 40-43bottom-up approach, 6-8components of, 48-49in contractual relationships,

54-55individual-level approach

approach, 43-47in one-time purchases with

add-on products/services, 55purchase-frequency model,

49-54top-down approach, 5-6

Customer Referral Value (CRV),230-233

net present value (NPV), 45-46metrics. See loyalty metricsmetrics dashboards (implementa-

tion challenges to CLV-basedframework), 261-264

MGM Grand, 251modified proportional hazard

model, 180Montgomery Ward, 274multichannel shoppers

channel adoption drivers,174-175

channel-adoption duration, 181

channel-related attributes,175-177

customer demographics,179-180

frequency-related attributes, 179

implementation of, 181-182purchase-related attributes,

177-179drivers for, 166-167

customer characteristics,167-170

customer demographics, 172supplier factors, 170-172

managing resources for, 184order of channel adoption,

183-184profitability of, 173-174, 182-183

multichannel shopping (CLV driver), 70

multichannel shopping manage-ment strategy (maximizing CLV),84-85, 163-184


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multiple channelsbenefits of, 163-164communication via, 170-172research shoppers and, 164, 166

myths about loyal customersdebunking, 22-23lower cost of service for, 18-19marketing efforts by, 20-21price sensitivity of, 19-20

N–Onet present value (NPV),

calculating, 45-46Nokia, 187-189

one-time purchases with add-onproducts/services, calculatingCustomer Lifetime Value (CLV), 55

one-to-one marketing strategies, 271individual customers (in

customer management evolution) and, 272-273

operational efficiencies, customerrelationships versus, 2

opportunity cost from customerattrition, 145

optimizing direct marketing expenditures, 205-206

overcommunication, risk of,116-117

PP&G (Proctor & Gamble), 223, 274Pareto principle, 6passive word-of-mouth

marketing, 21PCV (Past Customer Value), 24,

34-35drawbacks to, 36

people dimension (implementationchallenges to CLV-based framework), 259

Pepsi, 271portfolio management metrics, 262predicting

customer attrition, 147-150hazard models, 151-154logistic regression model,

150-151statistical issues, 154

customer purchase behavior, 129accuracy, lack of, 130-132joint-probability strategy,

132-137sample size, 131-132

Customer Referral Value (CRV),228-230

purchase sequence. See purchasesequency prediction strategy(maximizing CLV)

preventing customer attrition, 147intervention strategy, 155-161predicting churn, 147-154

price discounts, 178price premium behavior, 195price sensitivity of loyal customers,

19-20probability of active customers,

44-45. See also joint-probabilitystrategy (purchase behavior predictions)

Proctor and Gamble (P&G),223, 274

product availability, 176product categories (cross-selling

strategy), 138-141product-centric approach, changing

to customer-centric approachbusiness dimension of, 251-253,

255-258people dimension of, 259

product characteristics (CLV driver), 61, 70

Index 293

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product management metrics, 262product offering strategies, 128-129.

See also purchase sequence predic-tion strategy (maximizing CLV)

product offerings in interventionstrategy, 158

product orientation, 254product returns, 178

as CLV driver, 63, 71multichannel shopper

characteristics, 168-169profitability. See also Customer

Referral Value (CRV)acquisition and retention rates

versus, 207-209ARPRO (Allocating Resources

for Profit) strategy, 212-218brand value and, 187-189cross-selling strategy, impact of,

140-141customer profitability metrics,

262-264effect of customer relationships

on, 1-4loyalty and, 17-18. See also

Customer Lifetime Value (CLV)behavioral loyalty versus atti-

tudinal loyalty, 93-94customer segmentation, 95-98debunking loyalty myths,

22-23linking in loyalty

programs, 103lower cost of service for loyal

customers, 18-19marketing efforts by loyal

customers, 20-21price sensitivity of loyal

customers, 19-20

loyalty programs and, 11-12maximizing CLV with, 79-80,

93-110of multichannel shoppers, 173-

174, 182-183short-term versus long-term

profitability, 209-211proportional hazard model

(predicting churn), 152purchase frequency (CLV driver),

71, 179as customer behavior

outcome, 196multichannel shopper

characteristics, 170purchase-frequency model,

calculating Customer LifetimeValue (CLV), 49-54

purchase intention, 194purchase-related attributes (channel

adoption drivers), 177-179purchase sequence analysis, 132purchase sequence prediction

strategy (maximizing CLV), 81-83,127-141. See also customer purchase behavior

Q–RQuaker Oats, 274Quest Communications, 149

Recency-Frequency-Monetary value(RFM), 24, 30-32

drawbacks to, 36referral programs, implementing

based on CRV/CLV relationship,235-245

referral strategy (maximizing CLV),86-87, 223-248

referral value. See Customer ReferralValue (CRV)


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Regent Cruise Line, 15relationship benefits, 12. See also

loyalty programsrelationship duration (CLV

driver), 70relationship equity, 5, 65research shoppers, multiple

channels and, 164, 166resource allocation. See marketing

resource allocation strategy (maximizing CLV)

retention rate, 207. See alsocustomer retention strategy (maximizing CLV)

profitability versus, 207-209returns, 178

as CLV driver, 63, 71multichannel shopper

characteristics, 168-169revenue loss from customer

attrition, 145rewards strategy, 103-106. See also

loyalty programsRFM (Recency-Frequency-

Monetary value), 24, 30-32drawbacks to, 36

rich modes of communication, 115when to use, 116

SSafeway, 24, 103Sainsbury, 13sample size, predicting customer

purchase behavior, 131-132Samsung, 187-188, 193Sarner, Adam, 16Sears, 274Seemingly Unrelated Regressions

(SURs), 198

segmented customers (in customermanagement evolution), 95-98,270-271

campaign-based marketingstrategies and, 274-275

by profitability and purchasingbehavior, 101-102

selecting customers (maximizingCLV), 78-79

selection bias, 212selling orientation, 254Sephora, 171share of hearts, mind, and markets

metrics, 261Share of Wallet (SOW), 24,

32-33, 216combining with Customer

Lifetime Value (CLV), 122drawbacks to, 36

shared frailty, 180shopping basket size, 177short-term profitability, long-term

profitability versus, 209-211Silversea Cruises, 15social effects from customer

attrition, 145social networks. See customer

referral strategy (maximizing CLV)Somerfield, 14Sony, 251Southwest Airlines, 275SOW (Share of Wallet), 24,

32-33, 216combining with Customer

Lifetime Value (CLV), 122drawbacks to, 36

spending level (CLV driver), 62Sprint Nextel, 277Sprint PCS, 223

Index 295

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standardized modes ofcommunication, 115

when to use, 116Starwood, 14Stop & Shop, 170stopping investment in loyal

customers, 25-26supplier factors for multichannel

shoppers, 170-172SURs (Seemingly Unrelated

Regressions), 198SWABIZ.com, 275

Ttechnology manufacturer case study

(purchase behavior predictions),134-137

telecommunications company casestudy (calculating CustomerReferral Value), 230-233

telecommunications industry case study (customer attrition),146-147, 160-161

Tesco, 14Texas Instruments, 253Time Inc., 159time period (t), calculating

Customer Lifetime Value (CLV), 49timing in intervention strategy,

156-158timing models, 128, 133top-down approach, measuring


traditional models (purchase behavior predictions), joint-probability model versus, 137

travel cost, 175Tropicana (casino), 15two-tier rewards strategy (loyalty

programs), 103-106

U–VUnited Airlines, 235

validation sample (logistic regression model), 151

value equity, 5, 65Verizon, 277viral marketing strategy

(maximizing CLV), 86-87, 223-248Vocalpoint, 223

W–ZWal-Mart, 163, 194web-based contacts, 118-119

multichannel shopper characteristics, 169

Wells Fargo, 252, 256Wheel of Fortune (maximizing CLV

strategies), 75-78within-customer strategies

(maximizing CLV), 76word-of-mouth. See viral marketing

strategy (maximizing CLV)


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