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Analytics and Dynamic Customer Strategy: Big Profits from Big Data

Book Description

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

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