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Analysis And Strategy Of Loss Of Customers In Deyang Mobile

Posted on:2016-01-14Degree:MasterType:Thesis
Country:ChinaCandidate:Q XiaoFull Text:PDF
GTID:2309330482974676Subject:Business administration
Abstract/Summary:PDF Full Text Request
Customers are the lifeblood of the enterprise survival and development, in the fierce competition in the communications industry, customer stability and how to keep the customer is particularly important. 2G era, the size of the industry users directly determines the size of the communications enterprise income share and the market share. In recent years, with the development of 3G, 4G mobile business, the release of fixed network business license, and the rapid development of the Internet business, the three operators completely broke the monopoly of the various fields, and which form the competition pattern of three whole business operations, and also make the original single voice service competition into comprehensive business competition, such as voice, data traffic, information services and the internet business, but in a word, the customer is still the core competitiveness of the comprehensive competition.Deyang mobile communication company as one of the prefecture-level branch for China Mobile Group Co., Ltd. Sichuan Branch, at the beginning of the 20 th century which had created a proud achievement in revenue and customer scale than the rest 19 prefecture-level branch except for Chengdu, but in an increasingly changing market environment, the customer high-speed development period is over, constantly faced with new challenges. Customer scale barely moved, monthly customer new and loss were little changed. In the stock of the customer to maintain cost is far lower than the cost of new customers, how to seize the new, at the same time do a good job in the stock of customer maintain and sustain, to avoid the loss of the stock of customer is an urgent problem to be solved in Deyang mobile.This paper reviews the scale development of Deyang mobile customers, the average annual growth rate of 2012-2014 is only-0.55%, far lower than the average growth rate 16.2% of 2008-2011, while at the same time Deyang Telecom’s customer growth rate of 16.15% and Deyang Unicom growth rate of 2.4%, which shows that the loss of Deyang mobile customers is serious, at present for Deyang Mobile to reduce customer churn which is an urgent need to solve.This paper applies the relevant knowledge of MBA we have learned, together with the research team in the company, through the analysis and study of 34192 customer questionnaire, puts forward the six key factors influencing the loss of Deyang mobile customer, focus on the investigation of 4899 in the customer analysis and research on its social attributes, age, network age and consumption structure dimensions, analysis of these key factors behind the five management issues.This paper uses knowledge learning through MBA, Work with the company’s research team, Data mining through CRM system, Focus on the high-end customers in Deyang before the loss of consumption and business characteristics of the screening and selection of variables(such as network age, age, consumption, traffic, traffic, etc.), Build decision tree early warning model, Using the verified model to potential customers in the network customer mining, And take outbound questionnaire on customer churn intention, on the one hand, the model test, on the other hand analysis and research of customer loss reasons, put forward five key factors affecting Deyang mobile customer churn.Finally, the use of marketing management strategy, customer service management and other related knowledge, combined with the "customer loss", "potential loss of customer retention measures" and other issues, put forward the response of the marketing, service and management recommendations and measures. In this paper, the research on the loss of customers in Deyang, not only has the theory and the application value of Deyang, but also has important reference value and application value for other companies.
Keywords/Search Tags:Customer churn, Decision tree model, Loss reason analysis
PDF Full Text Request
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