Choice Modeling

In: Business and Management

Submitted By gameover
Words 4630
Pages 19
Choice Modeling: Marketing Engineering Technical Note 1
Table of Contents
Introduction Description of the Multinomial Logit (MNL) Model Properties of the MNL Model S-shaped response function Inverted “U” Marginal response Elasticity of response Proportional Draw Logit Model Estimation via Maximum Likelihood Using Logit Models for Customer Targeting Using Logit Models for Customer Segmentation Determining the number of latent segments in MNL models Summary References

Introduction
Firms today have access to increasing amounts of market response data at the level of individual customers, including data from scanner panels, direct marketing efforts, online retailing, loyalty programs, and the like. These data include both the marketing effort directed at a customer (e.g., price discount, or specific email sent to that customer) and the associated specific behaviors (e.g., purchase, customer support) of that customer. Consequently, there is also increasing interest among marketers in developing and using response models specified at the individual level. Analyses of individual-level data are useful for firms even for making decisions about aggregate marketing actions, such as TV advertising. After all, markets are composed of individuals, and acknowledging

This technical note is a supplement to the materials in Chapter 1,2, and 7 of Principles of Marketing Engineering, by Gary L. Lilien, Arvind Rangaswamy, and Arnaud De Bruyn (2007). © (All rights reserved) Gary L. Lilien, Arvind Rangaswamy, and Arnaud De Bruyn. Not to be re-produced without permission.

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and incorporating customer heterogeneity can be beneficial in a wide variety of marketing decision contexts. One of the most widely used approaches for modeling individual customer behavior is the multinomial logit model (MNL), which can be used to explain and predict the choices that customers make…...

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