Research On Accurate Mining Of House Purchasing Customers For Online Community

With the rapid development of Internet technology,a lot of changes have taken place in people’s lives,especially the social and consumption patterns are gradually changing from the traditional living social circle and offline physical consumption to online social and online consumption.Real estate marketing mode has also been a great impact,buyers are no longer satisfied with the traditional marketing mode of information indoctrination,passively accept this way of marketing.And most of the real estate enterprises still use the subjective judgment method of marketing personnel to mine and classify customers at this stage.This kind of judgment method based on experience is relatively poor in reproducibility and accuracy,and can not accurately mine and locate target customers from the existing complex network data.The demand of house buyers also tends to be diversified and personalized.They can obtain information beyond their own cognition through the online community,such as communicating with other house buyers or professionals through the online social platform,which leads to the diversification and complexity of the factors influencing the decision-making of house buyers.Therefore,it is necessary to conduct in-depth research on the online community behavior of real estate customers,build a model suitable for real estate enterprises’ online community precision marketing and buyer mining model,which can be used for real estate enterprises to accurately locate target customers and implement personalized precision marketing means.Based on the research status and achievements of online community marketing,real estate precision marketing and customer segmentation at home and abroad,this paper designs a real estate precision marketing model for online community based on the concept of data mining.Through the analysis of the trajectory and characteristics of online community behavior of house buyers,this paper analyzes the mining ideas and channels of online community behavior of house buyers.On this basis,using artificial neural network algorithm and funnel model,this paper constructs the accurate mining index system and model of buyers facing the network community.This model can be used for real estate enterprises to divide the buyers according to their purchase intention and purchase demand.The higher the willingness level of the buyers,the greater the possibility of purchase.The more matching the purchase demand level with the project development planning,the greater the possibility of purchase.In this study,the real estate development and sales project sample data is used to complete the training and testing of the model.In this process,the network structure and related parameters of the artificial neural network are determined,and the trained model is applied to the subsequent mining guidance experiment.Finally,this study designs the experiment of accurate mining and guidance for online community.The experimental process and results show that: first,based on the artificial neural network technology,the accurate mining model of home buyers for network community can accurately screen customers’ purchase intention and demand,which greatly improves the efficiency and accuracy of marketers’ subjective judgment of home buyers;Secondly,the screening index system of buyers’ willingness and demand grade constructed in this study is effective,which can deeply tap customers’ willingness and demand for house purchase,improve the efficiency of precision marketing,and enhance the marketing level of real estate enterprises;Thirdly,the model selection level is not unique,and the willingness and demand level of buyers will flow with the marketing guidance.According to the characteristics of positive or negative flow,corresponding marketing strategies can be formulated to improve the marketing efficiency;Fourth,the results of model home buyers mining combined with online community precision marketing model can effectively match the needs of home buyers,improve the purchase intention of target customers,promote the purchase transaction,shorten the marketing cycle and reduce the marketing cost.