About the Book

This book is intended for a broad audience of marketers in both business to consumer and business to business industries, though it is more likely that business to consumer marketers will be early adopters. The goal is to inform marketing practice and aid business leaders navigating through the competitive storms unleashed by technological change. Using data from a five-year study, as well as case studies and other research, this book provides a process for rigorous decision making, eliminating the paralysis and optimizing decision making for marketing performance.

About the Author

John F. Tanner Jr. is Professor of Marketing at Baylor University's Hankamer School of Business and an active consultant in the areas of marketing strategy and customer relationship management. He has published over 70 scholarly articles in the leading marketing journals, as well as 14 books, including The Hard Truth of Soft Selling, Selling: Building Partnerships, and Principles of Marketing: How Marketing Gets Done. Dr. Tanner speaks on marketing strategy at professional conferences around the world, including the Retailing Information Systems conference, Marketing Science Institute conferences, CRM Evolution 2013, Teradata's Partners Users Group, INFORMS, and the Expo!Expo!

Table of Contents:
Foreword Preface Acknowledgments Part One: Big Data and Dynamic Customer Strategy Chapter 1: Big Strategy for Big Data Beyond the Hype The Value of Accelerated Learning Introducing Dynamic Customer Strategy DCS Complements Design School Barriers to Big Data and DCS Summary Notes Chapter 2: Mapping Dynamic Customer Strategy Theory as Strategy Concepts Relationships Establishing Causality through Control Conditions Making the Model Operational Target's Behavioral Loyalty Model Simple versus Complex Models Summary Notes Chapter 3: Operationalizing Strategy Conceptual to Operational Operational Definitions From Strategy to Action Microsoft's DCS and Fail-Fast Mentality Experiments and Decisions Managing Decision Risk Using Big Data Effectively Summary Notes Part Two: Big Data Strategy Chapter 4: Creating a Big Data Strategy Avoiding Data Traps An Airline Falls into a Data Trap Creating the Data Strategy Summary Notes Chapter 5: Big Data Acquisition Measurement Quality The Truth and Big Data Acquiring Big Data Making Good Choices The Special Challenge of Salespeople Summary Notes Chapter 6: Streaming Insight The Model Cycle Applications of Statistical Models Types of Data--Types of Analytics Matching Data to Models Summary Chapter 7: Turning Models into Customers Mac's Avoids Mindless Discounting Decision Mapping Conversations and Big Data Cascading Campaigns Cascading Campaigns Accelerate Learning Accelerating the Process with Multifactorial Experimental Design Summary Notes Chapter 8: Big Data and Lots of Marketing Buzzwords Customer Experience Management Value and Performance Performance, Value, and Propensity to Relate Responsiveness Citibank MasterCard Responds at Market Level Transparency Community Cabela's Journey to Customer Experience Summary Notes Chapter 9: Big Data Metrics for Big Performance The Big Data of Metrics Variation and Performance Creating a Tolerance Range Visualization Creating the Right Metrics Summary Notes Part Three: Big Data Culture Chapter 10: The Near-Simultaneous Adoption of Multiple Innovations Building Absorptive Capacity People, Process, and Tools Managing the Change Empowering Your Entrepreneurs Konica-Minolta's Awesome Results One Result: Customer Knowledge Competence Global Implementation Summary Notes Chapter 11: Leading (in) the Dynamic Customer Culture Leadership, Big Data, and Dynamic Customer Strategy Leadership and Culture Movements Exploiting Strategic Experimentation Big Data, Big Decisions, Big Results Notes Afterword Additional Readings About the Author Index