A Study On Application Of PPN In The Prospect Customers Data Mining

Customers are the direct source of a firm’s profit and to obtain new customers continuously is the key of business success. It costs much if a firm sends a mail to every prospect customer in direct mail promotion. It is necessary to find the most possible customer to response to the new product to lift the customer response rate. Enterprise customers face the explosive growth of data, how will the introduction of data mining in customer relationship management is the key to improve the efficiency of decision-making.Probabilistic neural networks (PNN) model is a kind of artificial neural networks,which is simple in structure, easy for training and wide used. Practically the linear algorithm can be used to complete the work that was done by the non-linear algorithm while the high accuracy of the non-linear algorithm can be kept, especially in classification. Mining the prospect customers is a problem of classification eventually,which needs to divide customers as response ones and non-response ones. This paper uses probabilistic neural networks to deal with the data about customers, training the network to get a prediction model of prospect customers,which divides customers as response ones and non-response ones. Firms can use this model to improve the effect of promotion, and to lift the return of investment (ROI). The implementation on real example shows that probabilistic neural network in prediction of prospect customers is better than traditional methods (e.g. linear regression), and is better than BP neural networks.