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The Definitive Guide to Marketing Analytics and Metrics (Collection) by David Reibstein, Phillip E. Pfeifer, Neil Bendle, Ronald T. Wilcox, Paul Farris, Rajkumar Venkatesan, Cesar Brea

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13. Logistic Regression

Introduction

Almost all of us are familiar with odds. What are the chances one thing will happen versus another? What are the chances you will succeed at work today? What are the chances your favorite game-show contestant will win today versus the chances he or she will lose?

What you might not be familiar with is how odds can be applied to marketing analytics. What are the chances a customer will buy your product versus the chances he or she won’t? What are the chances you will retain a customer versus the chances you will lose him or her?

When you are using odds, you are examining two opposing outcomes. Any such unknown (one that can only be one thing or another) is known as a dummy variable. But if you know how to ...

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