Key decisions determine the success of big data strategy Dynamic Customer Strategy: Big Profits from Big Data is a comprehensive guide to exploiting big data for both business-to-consumer and business-to-business marketing. This complete guide provides a process for rigorous decision making in navigating the data-driven industry shift, informing marketing practice, and aiding businesses in early adoption. Using data from a five-year study to illustrate important concepts and scenarios along the way, the author speaks directly to marketing and operations professionals who may not necessarily be big data savvy. With expert insight and clear analysis, the book helps eliminate paralysis-by-analysis and optimize decision making for marketing performance. Nearly seventy-five percent of marketers plan to adopt a big data analytics solution within two years, but many are likely to fail. Despite intensive planning, generous spending, and the best intentions, these initiatives will not succeed without a manager at the helm who is capable of handling the nuances of big data projects. This requires a new way of marketing, and a new approach to data. It means applying new models and metrics to brand new consumer behaviors. Dynamic Customer Strategy clarifies the situation, and highlights the key decisions that have the greatest impact on a company's big data plan. Topics include: Applying the elements of Dynamic Customer Strategy Acquiring, mining, and analyzing data Metrics and models for big data utilization Shifting perspective from model to customer Big data is a tremendous opportunity for marketers and may just be the only factor that will allow marketers to keep pace with the changing consumer and thus keep brands relevant at a time of unprecedented choice. But like any tool, it must be wielded with skill and precision. Dynamic Customer Strategy: Big Profits from Big Data helps marketers shape a strategy that works.

Table of Contents:
Foreword xi Preface xv Acknowledgments xvii Part One: Big Data and Dynamic Customer Strategy Chapter 1: Big Strategy for Big Data 3 Beyond the Hype 4 The Value of Accelerated Learning 6 Introducing Dynamic Customer Strategy 7 DCS Complements Design School 19 Barriers to Big Data and DCS 20 Summary 24 Notes 24 Chapter 2: Mapping Dynamic Customer Strategy 27 Theory as Strategy 28 Concepts 29 Relationships 31 Establishing Causality through Control 34 Conditions 39 Making the Model Operational 40 Target’s Behavioral Loyalty Model 40 Simple versus Complex Models 42 Summary 43 Notes 43 Chapter 3: Operationalizing Strategy 45 Conceptual to Operational 45 Operational Definitions 48 From Strategy to Action 53 Microsoft’s DCS and Fail-Fast Mentality 53 Experiments and Decisions 54 Managing Decision Risk 57 Using Big Data Effectively 59 Summary 63 Notes 64 Part Two: Big Data Strategy Chapter 4: Creating a Big Data Strategy 69 Avoiding Data Traps 70 An Airline Falls into a Data Trap 71 Creating the Data Strategy 73 Summary 83 Notes 83 Chapter 5: Big Data Acquisition 85 Measurement Quality 88 The Truth and Big Data 89 Acquiring Big Data 90 Making Good Choices 98 The Special Challenge of Salespeople 99 Summary 100 Notes 101 Chapter 6: Streaming Insight 103 The Model Cycle 103 Applications of Statistical Models 108 Types of Data—Types of Analytics 112 Matching Data to Models 113 Summary 118 Chapter 7: Turning Models into Customers 119 Mac’s Avoids Mindless Discounting 120 Decision Mapping 121 Conversations and Big Data 123 Cascading Campaigns 127 Cascading Campaigns Accelerate Learning 130 Accelerating the Process with Multifactorial Experimental Design 131 Summary 133 Notes 133 Chapter 8: Big Data and Lots of Marketing Buzzwords 135 Customer Experience Management 136 Value and Performance 138 Performance, Value, and Propensity to Relate 140 Responsiveness 142 Citibank MasterCard Responds at Market Level 143 Transparency 144 Community 146 Cabela’s Journey to Customer Experience 147 Summary 149 Notes 150 Chapter 9: Big Data Metrics for Big Performance 151 The Big Data of Metrics 152 Variation and Performance 154 Creating a Tolerance Range 156 Visualization 158 Creating the Right Metrics 164 Summary 170 Notes 170 Part Three: Big Data Culture Chapter 10: The Near-Simultaneous Adoption of Multiple Innovations 173 Building Absorptive Capacity 176 People, Process, and Tools 177 Managing the Change 183 Empowering Your Entrepreneurs 188 Konica-Minolta’s Awesome Results 190 One Result: Customer Knowledge Competence 191 Global Implementation 193 Summary 194 Notes 195 Chapter 11: Leading (in) the Dynamic Customer Culture 197 Leadership, Big Data, and Dynamic Customer Strategy 198 Leadership and Culture 203 Movements 207 Exploiting Strategic Experimentation 212 Big Data, Big Decisions, Big Results 213 Notes 213 Afterword 215 Additional Readings 219 About the Author 221 Index 223