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

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Appendix B

Twenty-One Applications of Predictive Analytics

These applications—ways in which predictive analytics is employed—are covered in some detail within the Chapters noted. Others beyond these twenty-one are listed in this book’s Central Tables.

Targeting Direct Marketing (See Chapters 1 and 7)

1. What’s predicted: Which customers will respond to marketing contact.
2. What’s done about it: Contact customers more likely to respond.

Predictive Advertisement Targeting (See Chapter 1)

1. What’s predicted: Which ad each customer is most likely to click.
2. What’s done about it: Display the best ad (based on the likelihood of a click as well as the bounty paid by its sponsor).

Black Box Trading (See Chapter 1)

1. What’s predicted: Whether a stock will go up or down.
2. What’s done about it: Buy stocks that will go up, and sell those that will go down.

Pregnancy Prediction (See Chapter 2)

1. What’s predicted: Which female customers will have a baby in coming months.
2. What’s done about it: Market relevant offers for soon-to-be parents of newborns.

Employee Retention (See Chapter 2)

1. What’s predicted: Which employees will quit.
2. What’s done about it: Managers take the predictions for those they supervise into consideration, at their discretion. This is an example of decision support rather than feeding predictions into an automatic decision process.

Crime Prediction (See Chapter 2)

1. What’s predicted: The location of a future crime.
2. What’s done about it: Police ...

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