Research On The Pricing Of Super-market’s Goods Based On Data Mining

With the continuous acceleration of globalization process, Domestic Industries are subjected to the significant worldwide competitive pressure. The supermarket industry as a representative retail industry, also be first to bear the brunt. Goods price is a most important management object for the supermarket, because it will impact consumer purchasing decisions, thus affecting the supermarket income. Accordingly, strengthen scientific management in supermarket goods pricing not only to the enterprise business income, but also have the important help to improve customer shopping experience, develop an appropriate price system and to maintain the order of the retail market.Regrettably, goods pricing involves many factors, and the existing pricing methods is difficult to meet the fast-growing market changes, So this study for supermarket goods pricing based on data mining is important in theoretical and practical.The purpose of this paper is to construct a pricing model which is used to support the managemental decision of supermarket. Based on the factor analysis in supermarket commodity prices, it establishs commodity price index system. And then,it construct the supermarket commodity pricing model based on BP neural network.In the data mining process,it extracts the supermarket commodity pricing rules from transaction database, realize the automatic, intelligent supermarket goods pricing in batch.First of all,it introduces the basic theory of data mining, based on analysis of commonly used methods in supermarket goods pricing, points out the feasibility of introducing data mining to supermarket goods pricing field,then states the BP neural network, genetic algorithm, weighted KNN algorithm in theory.Secondly, based on optimized BP neural network, it constructed the supermarket commodity pricing model. In the model construction process,it firstly elaborated the principle of supermarket goods pricing model and construction ideas, after analysising of cost factors, customer needs, competitive factors, other factors four supermarket commodity price factors, build commodity price index system; secondly, it optimize the BP neural network in the hidden layer nodes, the network weights and threshold, loss input index; and then; finally it constructs the pricing model of supermarket commodity based on optimized BP neural network.Finally,apply the construction of the supermarket commodity pricing model based on BP neural network in empirical, prices in a certain chains supermarket.the results show that the model and method is effective, and has good maneuverability, can provide effective support for the management of the supermarket in commodity price.