China Mobile Group Shanghai Co.,Ltd Customer Complaint Management Research And Application

The final analysis, the competition between enterprises is thecompetition for customer resources. China Mobile is the leadingfull-service competition, customers need to scale advantages translateinto customer relationship advantage is a continuous need to improvecustomer satisfaction. Customers of China Mobile Group Shanghai Co.,Ltd. rapid growth at the same time the amount of customer complaintsalso rapid growth, how can conduct in-depth analysis of the contents ofthe customer complaints quickly focus on key complaint and found thatthe products, services, short board and quickly implement optimization,enhance customer perception of mobile services, which to enhance thequality of mobile services, improve customer satisfaction, consolidatingmobile brand has important and far-reaching significance.Complaints management is an important part in the management ofservice quality, China Mobile Group Shanghai Co., Ltd. has accumulateda large amount of text data in the complaints management, on the onehand, these data implies a direct description of user demands, on the otherhand how fast to acquire knowledge from these data and be theapplication of a problem. Text mining as the composition of theknowledge mining from unstructured, heterogeneous text collectionfound effective, innovative, knowledge available, and can be understood,is a way to solve the above problems. But how effective application of thetheory and tools for text mining technology to meet the needs of the ofcomplaints text processing and analysis of the actual work becomes achallenge.The papers from the complaints system support, processmanagement, and the accumulation of knowledge in three areas of ChinaMobile Group Shanghai Co., Ltd. customer complaints management status, summed up the problems. To solve these problems, the studycarried out work in three areas: First, a text data mining theory andclassification method. The practical application of the Shanghai Mobiletext mining theory building principle and process of text mining model;second, study the basic principle of support vector machines and KNNtext classification algorithm. In practical applications, an improved fuzzyclassification algorithm based on the statistics to improve the algorithmprecision; third, the improved model algorithm applied in actual servicequality management process, elaborated on the application of the modelas well as physical and technical architecture of the platform.CCR model in support of the complaint management applications,effectively reducing the amount of customer complaints, improvecustomer satisfaction, lower labor cost savings and efficiency gains,better demonstration effect.