Telecommunications Industry Data Analysis Services (RPM)
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Data Analysis Services2015-09-10 09:55:19
Shanghai Tianyuan Project data analyst firm, specializes in compiling various kinds of project reports and providing analytical industry data services for enterprises. Contact Tel: 13917778657
1. Network management and optimization.
(1) Optimization of infrastructure construction. such as the use of data analysis to achieve base station and hotspot location and resource allocation. It is possible to design 4G base stations and WLAN hotspots for high-flow regions of 2G and 3G by analyzing the distribution of the traffic in the time period and the location characteristics of the users in the word order and signaling. At the same time, the evaluation model can be used to evaluate the efficiency and cost of the existing base station, and the problem of resource waste is found. If some areas in order to complete the base station construction indicators to build the base station in the interpersonal rare places.
(2) Network operation management and optimization. At the level of network operation, data Analysis network traffic, flow direction change trend, timely adjustment of resource allocation, but also can analyze the network log, the whole network optimization, and continuously improve network quality and network utilization.
Data analysis technology is used to collect and process network signaling data, monitor network status, identify value cell and business hotspot, and more accurately guide network optimization to realize network, application and user's intelligent finger matching. Due to the different user groups, the contribution of different communities to operators is also different. Operators can be a multi-dimensional data analysis of the community data, through the Community VIP user distribution, income distribution, and the relevant distribution model to get the value of different communities, and network quality analysis combined, the two superimposed together, it is possible to find a high value of a community, but the network coverage needs to be further improved, In order to improve the investment efficiency, the priority of network optimization is set first.
2. Market and precision marketing.
(1) Customer portrait. The company can be based on customer terminal information, location information, call behavior, mobile Internet behavior trajectory and other rich data, for each customer to play demographic characteristics, consumption behavior, Internet behavior and interest hobby tag, and with the help of data mining technology (such as classification, clustering, RFM, etc.) for customer clustering, Improve the customer's 360-degree portrait to help operators gain insight into customer behavior preferences and demand characteristics.
(2) Relationship chain research. Through analyzing the customer address Book, call behavior, network social bank and customer data, and so on to carry out the communication circle analysis. In particular, the use of a variety of contact records to form social networks to enrich the user's insight, and further use of the method of graph mining to discover a variety of circles, identify key people in the circle, as well as identifying the family and business customers, or analysis of social circles to find marketing opportunities. If in a homogeneous circle of behavior, if the majority of the circle for high-traffic users, and found in this circle of users of the network, we can speculate that the user is also a high-traffic situation, you can through marketing activities to the network of high-traffic users to guide their own networks, the promotion of 4G packages, improve marketing conversion rate. In short, we can use social circles to improve marketing efficiency, improve services, and lower costs to expand the impact of products.
(3) Precision marketing and real-time marketing. In the customer image based on the customer's deep understanding of the characteristics of the establishment of customer and business, tariff package, terminal type, in the use of network precision matching, and in the push channel, push time, push way to meet customer needs, achieve precision marketing. If we can use big data to analyze the user's terminal preferences and consumption capacity, predict the user's change time, especially the contract machine expiry time, and capture the user's recent feature events, so as to predict the real needs of the user purchase terminal, through SMS, call center, Business Hall and other channels to push the relevant marketing information to the user's hands.
(4) Personalized recommendation. Using customer portrait information, customer terminal information, customer behavior preferences, operators can provide customers with customized services, optimize products, traffic plans and pricing mechanisms to achieve personalized marketing and services to enhance customer experience and perception, or to implement personalized recommendations in the marketplace, personalized recommendations on the e-commerce platform, Recommend friends who are interested in social networks.
3. Customer relationship Management.
(1) Customer Service Center optimization. Customer Service Center is the operator and customer contact more frequent channel, so customer service Center has a large number of customer call behavior and demand data. We can use big Data technology can deeply analyze customer service hotline incoming customer behavior characteristics, select path, waiting time, and related to customer history contact information, customer package consumption, customer demographics, client-type data, establish customer Service Hotline Intelligent path model, predict the next customer incoming demand, The risk of complaint and the corresponding path and node, so as to shorten the customer service processing time, identify the risk of complaints, help improve customer satisfaction; In addition, through the semantic analysis, the customer service hotline to classify the problem, identify hot issues and customer sentiment, for the occurrence of large and serious problems, To timely alert the relevant departments to optimize.
(2) Customer care and customer life cycle management. Customer lifecycle management includes five phases of new customer acquisition, customer growth, customer maturity, customer decline, and customer departure. During the customer acquisition phase, we can excavate and discover potential higher customers through algorithms, cross-sell through algorithms such as association rules during the customer's growth stage, and increase the customer's per capita consumption; At the customer's maturity, customer clustering (RFM, clustering, etc.) can be done through the big data method, At the same time, for different customer loyalty programs, in the customer decline period, need to carry out the loss of early warning, early detection of high-risk customers, and the corresponding customer care; At the customer departure stage, we can go through big data mining to return customers with high potential. Domestic and foreign operators in the customer life cycle management application of more cases. SK Telecom's new company, SK Planet, specializes in dealing with big data-related businesses by analyzing user behavior, introducing user-interested businesses to prevent user churn before they make a decision to leave, and t-mobile integrated data to analyze the causes of customer churn, Halve the wastage rate within a quarter.
4. Enterprise Operation Management.
(1) Business Operation monitoring points can be based on big data analysis from the network, business, user and business volume, business quality, terminal and other dimensions for operators to monitor the pipeline and customer operations. Build a flexible and customizable indicator module, build QOE/KQI/KPI and other index system, and the intelligent Monitoring system, from macroscopic to microscopic to quickly and accurately control the operation and the cause of the movement.
(2) Business analysis and market monitoring. We can analyze the business and market operation status through data analysis, mainly divided into business daily, weekly, monthly, quarterly and thematic analysis. In the past, these reports were written by analysts. In the big Data age, these business reports and feature analysis reports can be automated to generate Web pages or app forms to be completed by machines. Data sources are business and user data within the enterprise, as well as external social network data, technology, and market data collected through big data means. Analysts turn to report product managers, develop reporting frameworks, analysis, and statistical dimensions, leaving the rest of the work to the machine to complete.
5. Commercialization of data.
(1) Provide marketing insight and accurate advertising to the external market. Marketing Insight: American telecom operator Verizon set up the Precision Marketing department precision Marketing Division. The department provides accurate marketing insights (Precision market Insights) to provide business data Analysis Services. In the United States, baseball and basketball games are the most favorite marketing occasions, before the Super Bowl and NBA games, Verizon for the audience of the source of accurate data analysis, the team to understand the audience of the sponsor's preferences, etc. American telecom operator Sprint uses big data to provide consumer and market insights to industry customers, including demographic characteristics, behavioral characteristics, and seasonal analysis.
Precision AD Delivery: Verizon's Precision Marketing department provides accurate AD delivery services based on marketing insights, and the alert business, where users are close to the merchant, is likely to receive a large discount e-coupon from the merchant.
(2) based on big data monitoring and decision support services.
Passenger flow and site selection: In October 2012, Telefónica established the Dynamic Insight Division dynamicinsights to carry out big data business, providing customers with data analysis packaging services. The department partnered with GfK, the Market Research institute, to launch the first product name Smart Steps in the UK and Brazil. The smart footprint is based on fully anonymous and aggregated mobile network data, helping retailers to analyze customer sources and the flow of shops, booths, and consumer characteristics and consumption capabilities, and to provide insight into the customer flow analysis and retail store location services.
Utility Services: French Telecom, France's largest operator, and its communications solutions Department, Orange Business Services, has undertaken the construction of IT systems for many of France's public service projects, such as a French highway data monitoring project that generates millions of records per day, The analysis of these records can provide accurate and timely information for vehicles traveling on the highway, effectively improve the road patency rate of telecommunications customer complaints when the psychological analysis: from the consumer temperament analysis, can be divided into four categories of consumer temperament: choleric type, multi-blood quality, mucus type and melancholy quality.
After research, most of the repeated complaints of telecom customers belong to Choleric type and multi-blood quality customers, these two types of temperament of the customer higher nervous activity type is excited and lively type, their high emotional excitement, poor inhibition, special
Easily impulsive, therefore, they have three kinds of psychology in the complaint: The psychology of venting, the psychology of respect, the psychological remedy.
Telecommunications Industry Data Analysis Services (RPM)
