How To Predict If a Prospect Will Buy With Logistic Regression in Excel

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What Is Logistic Regression?

● Logistic Regression is used to calculate the probability of an event occurring ● Logistic Regression is used when the dependent variable in a regression (Y) is binary (can only be 1 or 0)● Marketers use Logistic Regression to create quality scores that calculate the probability of a prospect buying

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An Example of Marketing Use of Logistic Regression

We have historic customer data for the following customer attributes for each past prospect: 1) Whether or not the prospect purchased 2) Prospect’s age and gender

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Available Data On Past Prospects

Use the Excel Solver To Calculate the Predictive Equation

To Solve for the Predictive Equation P(X),You Need To Solve for L (the Logit)

You Will Use the Excel Solver to Solve for “Solver Decision Variables” (A, B, and Constant) Which Cause the Predictive

Equation P(X) To Be As Accurate As Possible

As Before Running the Solver, Create the Following Data Columns on a Spread Sheet

The Fundamental Basis for Logistic Regression Is Solving For The Above Equation

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The Excel Solver finds “Solver Decision Variables” (A, B, and Constant) that maximize the sum of the last column

The Solver Dialogue Box

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The Solver Finds the Solver Decision Variables (A, B, and Constant) that Optimize the Predictive Equation as Above

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You May Have To Adjust the Solver Constraints To Find the Most Accurate Predictive Equation

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