You are previewing Innovating Analytics: How the Next Generation of Net Promoter Can Increase Sales and Drive Business Results.
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Innovating Analytics: How the Next Generation of Net Promoter Can Increase Sales and Drive Business Results

Book Description

How does a CEO, manager, or entrepreneur begin to sort out what defines and drives a good customer experience and how it can be measured and made actionable? If you know how well the customer experience is satisfying your customers and you know how to increase their satisfaction, you can then increase sales, return visits, recommendations, loyalty, and brand engagement across all channels. More reliable and more useful data leads to better decisions and better results. Innovating Analytics is also about the need for a comprehensive measurement ecosystem to accurately assess and improve the other elements of customer experience. This is a time of great change and great opportunity. The companies that use the right tools and make the right assessments of how to satisfy their customers will have the competitive advantage.

Innovating Analytics introduces an index that measures a customer's likelihood to recommend and the likelihood to detract. The current concept of the Net Promoter Score (NPS) that has been adopted by many companies during the last decade—is no longer accurate, precise or actionable. This new metric called the Word of Mouth Index (WoMI) has been tested on hundreds of companies and with over 1.5 million consumers over the last two years.

Author Larry Freed details the improvement that WoMI provides within what he calls the Measurement Ecosystem. He then goes on to look at three other drivers of customer satisfaction along with word of mouth: customer acquisition, customer loyalty, and customer conversion.

Table of Contents

  1. Cover Page
  2. Title Page
  3. Copyright
  4. Contents
  5. Introduction
  6. Chapter 1: Customer Experience 2.0
    1. Accelerated Darwinism
  7. Chapter 2: NPS—What It Is and What It Does Well
  8. Chapter 3: NPS—Fundamentally Flawed
    1. Accuracy
    2. Margin of Error
    3. Oversimplification
    4. Detractors Don't Always Detract, and Promoters Don't Always Promote
    5. Where's the Growth?
    6. Insufficient Information
    7. Simple Is Just … Simple
  9. Chapter 4: WoMI—The Next Generation of NPS
    1. WoMI Distinguishes between Positive Word of Mouth and Negative Word of Mouth
    2. Negative Word of Mouth
    3. The WoMI Research Approach and the Validity of the Results
    4. Phase 1: ForeSee Independent Research
    5. Phase 2: Initial Client Testing
    6. Phase 3: Later Client Testing
    7. WoMI Testing Results
    8. NPS and WoMI Score Differences
    9. Recommend and Discourage Scores
    10. Continuing Implementation
    11. In Virtually Every Industry, We See a Massive Overstatement of Detractors
    12. Using WoMI with NPS
  10. Chapter 5: The Four Drivers of Business Success
    1. Customer Retention
    2. Upsell
    3. Marketing-Driven Customer Acquisition
    4. Word-of-Mouth-Driven Customer Acquisition
    5. Customer Intent and True Conversion Rate
    6. The Common Thread
  11. Chapter 6: Why the Customer Experience Matters
    1. Why Measure Customer Experience?
    2. How to Measure the Customer Experience and Answer the Big Three Questions
    3. Measuring the Customer Experience at the Brand Level
    4. Measuring the Customer Experience in Contact Centers
    5. Measuring the Customer Experience in Stores
    6. Measuring the Customer Experience on Websites
    7. Measuring the Customer Experience with Mobile Experiences
    8. How to Measure the Multichannel Consumer
  12. Chapter 7: The Customer Experience Measurement Ecosystem
    1. Behavioral Data
    2. Getting Sticky
    3. Mobile Complexity
    4. Challenging Behavioral Metrics
    5. Observation and Usability
    6. Voice of Customer Measurement
  13. Chapter 8: Best Customer Experience Practices
    1. Amazon
    2. Zappos
    3. Panera Bread
    4. Government Agencies
    5. Eddie Bauer
    6. Nutrisystem
    7. House of Fraser
    8. ABC
    9. Testing New Store Programs Impact on the Customer Experience
    10. Word-of-Mouth Index (WoMI)
    11. Best Practices
  14. Chapter 9: Big Data and the Future of Analytics
    1. Big Data Volume
    2. Big Data Variety
    3. Big Data Velocity
    4. The World of Big Data
    5. Big Data Creates Value
    6. Big Data and Retail
    7. The Trap of Big Data
    8. Innovation
  15. Afterword: Measuring Customer Experience—A Broader Impact and the Start of a Journey
  16. Appendix A: Satisfaction, WoMI, Net Promoter, and Overstatement of Detractors for Top Companies
    1. The Top 100 U.S. Brands
    2. The Top 100 U.S. Online Retailers
    3. Top 40 U.K. Online Retailers
    4. Seven Largest U.S. Banks
    5. The Top 29 U.S. Retail Stores
    6. The 25 Top Mobile Retail Sites and Apps
    7. Seventeen Mobile Financial Services Sites and Apps
    8. Twenty-Five Mobile Travel Sites and Apps
  17. Appendix B: Are Those Least Likely to Recommend Actually the Most Likely to Discourage?
    1. Least Likely to Recommend: 1s
    2. Least Likely to Recommend: 1s and 2s
    3. Low Likelihood to Recommend: 1 to 3 on a 10-Point Least Likely Scale
    4. Low Likelihood to Recommend: 1 to 4 on a 10-Point Scale
    5. Low Likelihood to Recommend: 1 to 5 on a 10-Point Scale
    6. Low Likelihood to Recommend: 1 to 6 on a 10-Point Scale
  18. Appendix C: Eleven Common Measurement Mistakes
    1. Common Measurement Mistake #1: Drawing Conclusions from Incomplete Information
    2. Common Measurement Mistake #2: Failing to Look Forward
    3. Common Measurement Mistake #3: Assuming That a Lab Is a Reasonable Substitute
    4. Common Measurement Mistake #4: Forgetting That the Real Experts Are Your Customers
    5. Common Measurement Mistake #5: Confusing Causation and Correlation
    6. Common Measurement Mistake #6: Confusing Feedback and Measurement
    7. Common Measurement Mistake #7: Gaming the System
    8. Common Measurement Mistake #8: Sampling Problems
    9. Common Measurement Mistake #9: Faulty Math
    10. Common Measurement Mistake #10: Measurement by Proxy
    11. Common Measurement Mistake #11: Keep It Simple—Too Simple
  19. Appendix D: An Overview of Measurement and Model Analysis Methods
    1. Introduction
    2. The Three Essential Questions for Managers
    3. The Theoretical Framework
    4. What Are the Technology Platforms Used by ForeSee?
    5. Measurement
    6. Model Analysis Provides Prescriptive and Prognostic Capabilities
    7. The Use of 10-Point Scales
    8. Bibliography
  20. Acknowledgments
  21. Index