Author: Eric Siegel
Author: Eric Siegel
What if someone could foretell your future, using purely scientific methods? What if they could predict what you would buy and when you would die?
That is exactly what is happening now. Big businesses are watching, collecting, and analyzing your current behavior in order to determine your future behavior, and therefore, accurately select which advertisements to send you. Insurance companies predict accidents and death in order to structure insurance premiums. Employers foresee which employees are a flight risk so that they can intervene before you quit. Creditors determine which card holders are likely to miss a payment so they can raise the interest rate in advance. There’s even a website that predicts your likelihood of getting a divorce, based on personal factors.
Predictive analytics was used by the Obama For America Campaign to predict which voters would be positively persuaded by which type of advertising. This information was used to influence millions of voters in swing states.
Computers are reading your mind, as it were, and while they cannot be 100 percent accurate, they know enough to make a huge difference for those who use them.
It’s all very fascinating, and Eric Segal’s well-written book, Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die will keep you turning the pages until the end.
In the mid-1990s, a brilliant, young researcher by the name of Dr. John Elder, created a program to predict the stock market. He believed that his program could do what no one else had been able to do: foretell which stocks to buy and sell on any given day. He believed in his program so wholeheartedly that he persuaded his wife Elizabeth to let him place all of their money—including their entire savings and retirement account—into buying stocks predicted by his program. I won’t spoil the story, but what happened is fascinating.
The sexy centerfold in the middle of the book is a large, colorful chart showing the actual names of companies, organizations, and groups, what they predicted, how much money they spent, and what the result was.
One of my favorite chapters—being in the mortgage industry myself—is chapter 4, which reveals how Chase Bank predicted mortgage risk and why prediction couldn’t prevent the global financial crisis.
But I also loved “Far Out, Bizarre, and Surprising Insights.” There I learned such things as:
· 60 percent of people who buy Barbie dolls buy one of three types of candy bars.
· The word awesome gets a better response than the word sexy on dating sites.
· Vegetarians miss fewer airline flights.
The book ends with ten predictions for the first hour of 2020. It’s all very fascinating indeed.
Personally, I think having an understanding of predictive analytics is empowering. Therefore, I highly recommend this book for all people who like to think for themselves and determine their own destiny.
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