Application of Neural Networks to Recognize Satisfied Customers for Car after Sales Services Marketing

Abstract

The purpose of the research was the development of a neural networks model to recognize satisfied customers for car maintenance service marketing. Data set was built up from survey of ten car maintenance service provider in Iran. Multi-layer perceptron (MLP) neural networks with hyperbolic tangent function trained by feed forward training algorithm were utilized to build the recognition model. The result reveals that the recognition accuracy of the test on the model is greater than that expected by chance. Meanwhile, a set of contribution weights representing the general importance of each independent variable was produced and their marketing implications were illustrated. This research confirms that the neural network model is useful in recognizing existing patterns of customer’s data. The advantages of using the model are highlighted and marketing implications are demonstrated. Authors believe that the model is useful and suitable as an analyzing tool for car maintenance service on market strategy planning.