With the rapid development of mobile network, the use of mobile phones has become popular. People use mobile phones every day to surf the Internet, shop, socialize, work, etc. In the process of using mobile web services, users may be dissatisfied with the service perception, such as voice connectivity, Internet access, Slow Internet access and other common problems. If the customer is not satisfied with the communication service, the customer can usually complain about the quality of the communication service, so the frequency of the customer complaint has become an important evaluation index for the management of the operator. The quantity and frequency of customers ‘complaints about telecommunication service are increasing gradually, which brings challenges to the service quality and efficiency of telecommunication operators. This paper presents a methodology for customer complaints. The analysis system is based on the data of Horizontal pull- through, combined with big data analysis model, focus on the user’s response to the Internet slow, Internet access, voice access issues such as real-time positioning analysis, to provide customers with the first time solutions.

The feedback of service quality comes from customers is an important information for mobile operators, and the value of different user contacts varies greatly. This paper tries to integrate this contact information with telecom operator’s business and signaling data, and then realize the digital mapping from user experience to operation and network problems. Our aim is diagnose the root cause of the problem and then provide the systematic solution. This paper proposes a systematic and package solution for collaborative improvement of user experience and network quality, driven by user’s contact information with operators. Meanwhile, this paper also proposes three method to help telecom operators to repair user’s stickiness step by step, and improve the mobile network quality synchronously.

With the disappearance of the demographic dividend and the saturation of the public telecom market, telecom operators need new development strategies urgently. New services formed by the convergence of mobile network services and broadband network services (referred to as fixed-mobile convergence services) have become an important strategy. Through business innovation, telecom operators can bundle mobile services with broadband services, which can enhance user stickiness and increase business revenue. Based on the joint analysis of mobile network data and broadband network data, this paper proposes a rule-based and model-based integrated method for mining potential fixed-mobile convergence target users. After applying this method to the real market for single mobile contract user transferring to convergent contract, results show that the proposed method for exploiting potential target users can increase the conversion rate of convergence users.