Deep Learning for Distribution Channels' Management

Abstract

This paper presents an experiment of using deep learning models for distribution channel management. We present an approach that combines self-organizing maps with artificial neural network with multiple hidden layers in order to identify the potential sales that might be addressed for channel distribution change/ management. Our study aims to highlight the evolution of techniques from simple features/learners to more complex learners and feature engineering or sampling techniques. This paper will allow researchers to choose best suited techniques and features to prepare their churn prediction models.

Keywords

• Artificial Neural Network
• Distribution Channel
• Self-Organizing Maps
• Deep Learning