Research Of Customer Consumption Behavior For Auto After-sales Service Industry Based On Data-mining

It is a big challenge for enterprises to offer service with high quality and efficiency in this high developing society.With the developing of computer technology,the enterprise can get a good help from the information,but with the increasing of the data,how to get the valuable knowledge from thousands of information to support the enterprise is becoming harder,because many data was recorded routinely,and people can not realize the useful information and knowledge beyond them,even to get something useful to help them understand customers better and then to get more benefit with limited cost.At the same time,the suppliers of service can not supply different kinds of service for different kinds of customers but to treat them without any difference or just distinguish them simply.As a result,the companies miss potential valuable customers or have no idea about the decrease of benefit from important customers.The research goal of this thesis is to introduct highintelligence tool data-mining to CRM and to establish convenient and useful customer analysis system.So the companies can ananlyse and mine the charactors of customers and make customized policies.The paper proposed the appliance of data-mining in CRM.When using to segments the groups of customers,the data of customer consumption action can help companies decide how to distribute their limited resources to the customers according to the customers' levels and then design and implement different customer retention strategies.The purpose is to retain the most valued customers and translate potential current low-value customers into high-value ones in the future.It is also aimed to encourage non-value customers of all times to contact and have business with the companies' competitors.Through those strategies companies can realize the maximization of their total profits.The technique of data-mining can help the companies realize the purpose scientifically.And with the establishment of the system for customer segmentation and charactor analysis,the technique of data-mining can be used more widly.The paper first employed the theory of marketing,set up the RFM model of consumption for customers of auto after sales services companies, obtained the weight of each index through the method of analytic hierarchy process so as to obtain the basic data used in the clustering analysis and segmented the customers with improved ant colony clustering algorithm.Then with the classification algorithm CAMM,it analysed the charactors of each kind of customers so the companies can predict the types of customers when getting ontological information of them.Finally it designed and implemented the archetypal system of customer classification and character analysis.It is proved by case study that the model and methods advanced in the paper can effectively solve the problem of classification and character analysis of customers belonging to auto after sales services companies.