Review of Eric Siegel’s Predictive Analytics Book

Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die by Eric Siegel is currently the number 1 book in various categories for a good reason. Eric has done a good job explaining what predictive analytics is and what it can be used for. He provides many case studies from various fields to show the impact of predictive analytics. Some of these case studies include: prediction of employees who are likely to leave, Target’s famous use for acquiring new customers by predicting pregnancy, and crowdsourcing of model development as seen in Netflix’s $1M prize. Eric also devotes a chapter on IBM’s Watson as well as a chapter on concepts of machine learning, mainly focusing on decision trees. This book also has some tables that along with the application of predictive analytics, list various surprising insights. For example, did you know that Orbitz likely shows expensive options to Mac users, because it learned that Mac users spend up to 30% more money than Windows users.

One of the negatives of this book is the overuse of quotations. I found too many quotations distracting. Maybe, it was because I was reading the Kindle version that filled up pages with quotations. Apart from this minor irritation, I think this is a great book to introduce predictive analytics to non-practitioners and management members, or to scare and provide evidence to the Luddites. Please note that this book, on purpose, omits the “how-to’s” of machine learning or predictive analytics. To learn those topics in detail either refer to Data Mining: Practical Machine Learning Tools and Techniques or Pattern Recognition and Machine Learning.

Disclaimer: I received this book for free from Wiley in exchange for an honest review.

About the Author

A co-author of Data Science for Fundraising, an award winning keynote speaker, Ashutosh R. Nandeshwar is one of the few analytics professionals in the higher education industry who has developed analytical solutions for all stages of the student life cycle (from recruitment to giving). He enjoys speaking about the power of data, as well as ranting about data professionals who chase after “interesting” things. He earned his PhD/MS from West Virginia University and his BEng from Nagpur University, all in industrial engineering. Currently, he is leading the data science, reporting, and prospect development efforts at the University of Southern California.