Telecom Analytics – a smart way to ensure customer loyalty and benefit from new types of revenue
Data analysis in the past was manageable. Originally operators were not taking in as much information and analytics in real-time were not necessarily required. Analytics and big data are far more difficult today, with the availability of everything at any moment on personal devices. Operators need to be responsive in seconds - even proactively.
Analytics are a major differentiator allowing operators to leverage knowledge from data and enhance their already tight margins. Operators need to see the big picture - to stay on top of trends. If something is an anomaly, fine. But, if it has never happened before, they need to keep track of it. Ultimately the operator needs a single picture of the subscriber, fixed and mobile.
As part of Telecom Analytics, Nokia's Cognitive Analytics suite brings to operators intelligent and self learning software that continuously optimizes towards its goals with machine- & deep-learning. Providing a 360 degree view of customers and networks across the customer life cycle journey, this Cognitive Analytics can be used as standalone software or can be combined with other products to enable closed-loop actions and automation of real-time decisions.
Cognitive Analytics includes customer, marketing and crowd insight, mobile, fixed and IP networks, autonomous care and security as part of the comprehensive offering. Included in Telecom Analytics is also a variety of Data Monetization and Predictive Service offerings as well as our Analytics Office.
Telecom analytics focuses on customers, networks, data monetization and predictive services
The Cognitive Analytics suite covers a wide array of analytics to use standalone or to combine with other products to enhance their actions and automation.
Cognitive Analytics for Customer Insight increases customer satisfaction to gain and maintain a loyal subscriber base.
Cognitive Analytics for Mobile Networks enables deep subscriber and network insight and real-time network action and optimization. The key products are Traffica, Wireless Network Guardian and Network Performance Optimizer.
Cognitive Analytics for Security infuses Nokia’s NetGuard security solution with advanced analytics capabilities to help services providers secure and protect physical, virtual, and hybrid mobile networks.
Cognitive Analytics for IP Networks provides real-time, multi-dimensional insight by combining and correlating data from cloud applications and services to see their exact impact across the network allowing operators to pinpoint and resolve service issues in moments.
Cognitive Analytics for Fixed Networks allows service providers to troubleshoot issues with digital subscriber line (DSL), copper and fiber network access.
Cognitive Analytics for Autonomous Care uses interactive bots and machine learning to proactively fix problems and resolve customer issues without the need for any interaction between the customer and the help desk.
Data monetization represents a significant new opportunity to compensate for flattening and lost revenues. The key solutions are Cognitive Analytics for Crowd Insight, Ad Analytics, and Big Data Consulting.
Predictive Services Suite includes Preventive Complaint Analysis and Predictive Care solutions, which are services based on a machine learning concept to detect network elements' behavior anomalies for predicting and resolving issues before they impact customers. These are all hosted on our AVA services platform.
Analytics Office services suite provides deep domain expertise to help service providers improve customer experience, data monetization, service operation centers, data science and network automation.
Explore our Telecom Analytics products and services
Big Data ConsultancyHelps operators maximize the value of their big data platforms and deliver measurable outcomes by benefitting from accumulated expertise from large big data and Customer Experience Management projects
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#bigdata from @nokianetworks
With analytics, CSPs can improve their businesses by focusing on customers, networks and data monetization. They can raise network operational efficiency; accurately predict and correct potential network performance issues before they affect customers; increase the effectiveness of their marketing campaigns; improve the efficiency of their customer care functions; create new revenue opportunities from other industries; and much more.