Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die

Notes

Introduction

All case examples in the Introduction appear in this book’s Central Tables of examples. See the Notes corresponding to those tables for references.

Further information about predictive analytics for business users and prospective practitioners:

• Predictive Analytics Times, a monthly online newsletter. www.predictiveanalyticstimes.com.
• Eric Siegel, PhD, “Seven Reasons You Need Predictive Analytics Today.” Prediction Impact, Inc. White Paper, September 2010. www.predictiveanalyticsworld.com/signup-whitepaper.php. This white paper reveals seven strategic objectives that can be attained to their full potential only by employing predictive analytics, namely: Compete, Grow, Enforce, Improve, Satisfy, Learn, and Act.
• Eric Siegel, PhD, “Predictive Analytics with Data Mining: How It Works,” published in DM Review’s DM Direct, February 2005. www.predictionimpact.com/predictive.analytics.html.
• Predictive Analytics Guide: Further reading, articles, and resources. www.predictiveanalyticsworld.com/guide.

Leading books for business users of analytics:

• Thomas H. Davenport and Jeanne G. Harris, Competing on Analytics: The New Science of Winning (Harvard Business School Press, 2007).
• James Taylor, Decision Management Systems: A Practical Guide to Using Business Rules and Predictive Analytics (IBM Press, 2011).
• Ian Ayres, Super Crunchers: Why Thinking-by-Numbers Is the New Way to Be Smart (Bantam, 2007).
• Steven Baker, The Numerati (Houghton Mifflin Harcourt, 2008).

Leading foundational ...