Why choice modeling?

Mô hình lựa chọn cho Marketing bằng R

Elea McDonnell Feit

Assistant Professor of Marketing, Drexel University

Regression modeling relates predictors to numeric outcomes

A linear regression model is used to predict a number.

In marketing, we might use a linear regression to understand how how the sales at a store are related to the features of that store. Sales is a number.

Mô hình lựa chọn cho Marketing bằng R

Many events we want to understand and predict are **choices**

  • Selecting a dress for a special occasion from an online retailer
  • Choosing what to watch on a video streaming service
  • Buying a car
Mô hình lựa chọn cho Marketing bằng R

Choices require their own special type of regression

Multinomial logistic regression or the multinomial logit model is used to predict a choice from a set of alternatives. The prediction is based on the features of each alternative. For instance, we can predict the likelihood of choosing a particular car based on the features of the available cars.

Logistic regression or the logit model is a special case of multinomial logistic regression used to predict binary "yes/no" such as the uptake on a promotional offer.

Mô hình lựa chọn cho Marketing bằng R

Marketing applications for choice models

Designing new products

Understand how product features relate to what people will buy

Pricing

Determine how price is related to market share

Merchandising

Measure the effect of a "customer favorite" flag on which product a online shopper chooses

Mô hình lựa chọn cho Marketing bằng R

What choices are *you* interested in analyzing?

Mô hình lựa chọn cho Marketing bằng R

Preparing Video For Download...