The timing of the recent U.S. Presidential election brought a lot of attention to data analysis and the ability of statisticians to predict outcomes. Expect to hear a lot more about the power of statistics in the future.
Predictive analytics (PA) is defined as “technology that learns from experience (data) to predict the future behavior of individuals in order to drive better decisions.” A new generation of data geeks makes news almost daily now by digging into data to find the patterns and connections that can predict behavior.
In an entertaining fashion, this book does a good job of making PA look seductive, and shows real company examples of the profit potential for businesses using such analysis to predict behavior.
Author Eric Siegel relates a powerful case where his client yielded a lucrative increase in online traffic solely due to better decision-making about which ads to display for website visitors.
True geeks will enjoy reading of the power of machine learning, when today’s computers can be programmed to make decisions on the basis of behavior. While computers can’t think and don’t know the difference between a house and an ocean, they can analyze patterns of data and, fed the right variables and combinations, can quickly predict outcomes.
Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die is a lively format with significant details on business success stories and can serve as a good education for new statistics workers and managers handling large amounts of data.
Yet, Predictive Analytics is not too technical and geeky to be an enjoyable reading experience for all savvy consumers. There are great data tables, illustrating amazing results in corporate use, such as how Hewlett Packard can predict employee “flight risk” by evaluating patterns of employee development and quitting
A big news story developed in 2010 when a writer explored Target’s ability to predict pregnancy by evaluating shopping behavior. Was it data gathering or privacy invasion? What makes prediction a science and what makes data predictive?
Today, computers can diagnose cancer, can discern whether you’re telling the truth, and can predict premature birth, as well as the 2012 U.S. election that was predicted with near-perfect accuracy by more effective analysis of behavior.
Surely business people reading Predictive Analytics will find ways to better know their business, customers and employees, through better data analysis. We can also hope the future will be aided by increased use of predictive analytics for the benefits it might bring for important issues such as public safety, healthcare, and society.