Application of neural networks to recognize profitable customers for dental services marketing-a case of dental clinics in Taiwan

The purpose of the research was the development of a neural networks model to recognize profitable customers for dental services marketing. Data set was built up from proprietary customer databases and survey of seven dental clinics in Taiwan. Multi-layer feed-forward neural networks with sigmoid function trained by back-propagation 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 customers’ 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 dental marketers on market strategy planning.