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Analytics and dynamic customer strategy : big profits from big data / John F. (Jeff) Tanner, Jr.

By: Material type: TextTextPublisher: Hoboken, N.J. : Wiley, 2014Description: 1 online resource (xviii, 235 pages) : illustrationsContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781118919781
  • 1118919785
  • 9781118919774
  • 1118919777
  • 1118905733
  • 9781118905739
  • 9781306892926
  • 1306892929
Subject(s): Genre/Form: Additional physical formats: Print version:: Analytics and dynamic customer strategy.DDC classification:
  • 658.8/34 23
LOC classification:
  • HF5415.5
Other classification:
  • BUS019000
Online resources:
Contents:
Cover; Title Page; Copyright; 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 StrategyConceptual 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 InsightThe 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 LevelTransparency; 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 ImplementationNotes; 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; Afterword; Additional Readings; About the Author; Index; EULA
Summary: "Key decisions determine the success of big data strategyDynamic 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"-- Provided by publisher.
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Includes index.

"Key decisions determine the success of big data strategyDynamic 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"-- Provided by publisher.

Print version record and CIP data provided by publisher.

Includes bibliographical references and index.

Cover; Title Page; Copyright; 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 StrategyConceptual 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 InsightThe 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 LevelTransparency; 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 ImplementationNotes; 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; Afterword; Additional Readings; About the Author; Index; EULA

Marketing