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Service Complaint Data Mining Based On A Mobile Corporation Channel Analysis And Promotion Strategy

Posted on:2015-03-20Degree:MasterType:Thesis
Country:ChinaCandidate:B YouFull Text:PDF
GTID:2309330473952806Subject:Business administration
Abstract/Summary:PDF Full Text Request
The industry structure of the mobile communication has been continuously optimizing with its steadily developing. For the ChinaMobile in 2G era, today’s China Mobile has been different. Because of the operators’ 3G licenses start at the same time, the traditional strong China Mobile has no longer dominated in the aspect of acquire new users.The all-round business operatingmakes the new mobile’s business to face the heated competition. The speed of users growth is beginning to slow down due to the size of the market is close to saturated. In such a background, the urgent affairs of the development of communication enterprises are to improve their ability to acquire and retain users. And this makes the contest among the communication enterprises turn toserviceorientation from product orientation. Service has become the key to seize users. But how can it struggle for competitor’s customers at the same time of remaining their own users’ loyalty? In general, customers usually contact with the enterprise through business channels. So the main source of customer satisfaction is their perception in the process of dealing with the business through business channels. So the competition of telecommunication enterprise has already become channel competition from the network technology competition and price competition. And the marketing channel which is as an important link between sales and customer service has become the focus of the core competitiveness of communication enterprises. Law of time to explore the analysis of the distribution of the user to the user complaints, classify, and summarize the cause of complaints, and summarizes the cause of the problem. To targeted formulate corresponding strategies to improve channel satisfaction, reduce customer churn. The purpose of this article is to study the consumers’ channel satisfaction of A Mobile Company. It needs to analyze the SMS evaluation data in a period time, to discuss and analyses the rule of time of the user complaints, to classify and summary the cause of complaints and summarizes the cause of the problems. It can targeted formulate corresponding strategies to improve channel satisfaction and reduce customer loss.The article chooses the uses of A Mobile Company as the research object, based on marketing channel management, service marketing and data mining theory, applies data mining technology to analyze the users’ complaint data, finds out the factors affect on the channels’ service quality satisfaction and proposes the corresponding strategy. This article’s conclusions are as follows. The self-management channel has the most of complaints. The main problems of channels include the quality problems of network and business, false propaganda and information security. On this basis, this paper puts forward the service satisfaction promotion strategy of A mobile company channel should give priority with interpersonal interaction, entity channel, product promotion and channel development and so on. In the aspect of interpersonal interaction, it has to strengthen personnel training, to pay attention to the interactive construction of electronic channels, to actively follow up with the customers, to fulfill the duty to inform to the customer. In terms of physical environment, it has to ensure the good environment, to maintain the customer order and offer warm service to customers and so on. For the product promotion, it has to build a service guidance, complete the pre-assessment, keep maintenance of base station equipments and guarantee the propaganda to be according to the facts. For the direction of channel development, it should focus on the electronic channel. Finally this article come to the conclusion and points out the problems existing in the research.
Keywords/Search Tags:ChinaMobile, marketing channels, services marketing, data mining
PDF Full Text Request
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