Title :
A framework for improving find best marketing targets using a hybrid genetic algorithm and neural networks
Author :
Behzad Soleimani Neysiani;Nasim Soltani;Shima Ghezelbash
Author_Institution :
Department of Software Engineering, Faculty of Electrical &Computer Engineering, University of Kashan, Kashan, Isfahan, Iran
Abstract :
Recently, many companies in Iran use telemarketing to introduce their products. These companies need to detect their best target to following them over seasons and years for more sales. This paper introduces a simple and appropriate method to predict behavior of customers based on behavior of prior customers. First of all, a dataset of customer action should be made and then preprocessed to reduce its attribute and dimension. Then a neural network will be made based on selected features to predict sale behavior of customers. Finally an evolutionary algorithm like genetic can be used to find feature of customers who will buy products more. This method evaluated by Portuguese Bank Tele Marketing dataset. Results show it simply can find the best customers in this case study. It´s highly recommended to companies use this method to reduce their marketing costs and have better performance.
Keywords :
"Decision support systems","Companies","Neural networks","Evolutionary computation","Genetic algorithms","Economics"
Conference_Titel :
Knowledge-Based Engineering and Innovation (KBEI), 2015 2nd International Conference on
DOI :
10.1109/KBEI.2015.7436136