Application of Generalised Additive Logistic Model for Targeted Marketing
Published: 2017
Author(s) Name: K. V. N. K. Prasad, G.V.S.R. Anjaneyulu |
Author(s) Affiliation: Department of Statistics, Acharya Nagarjuna University, Guntur, Andhra Pradesh, India.
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Abstract
This study focuses on how to support marketing decision makers better in identifying better prospective customers by using generalised additive models (GAMs). Compared to logistic regression, GAM relaxes the linearity constraint which allows for complex non-linear fits to the data. In this paper, we examine how GAM-based logistic models perform compared to traditional logistic regression model and also provide some implications.
Keywords: Additive Logistics Model, Targeted Marketing
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