With the rampant adoption of smartphones and growth in mobile Internet, communications service providers have access to unprecedented amounts of data, including customer profiles, device data, network data, customer usage patterns, location data, apps downloaded, clickstream data and so forth. CSPs are sitting on a goldmine of information and are in a great position to capitalize on these valuable data sets.
CSPs are increasingly adopting Apache Hadoop and big data analytics solutions to turn their data into valuable business insights. Operators believe big data will play a critical role in helping them meet business objectives, accelerate growth, and drive efficiencies and profitability across the entire telecom value chain. So how are CSPs utilizing big data? What are the most compelling use cases?
Although there is endless potential for big data within the realm of an operator’s business, most of the key use cases within telecom can be grouped under the following four buckets:
Customer experience management (Customer 360)
CSPs are starting to leverage Hadoop and big data analytics to stitch together a true 360-degree view of their customers and business across all products, systems, devices and diverse interaction channels. Based on these detailed customer profiles, telcos can perform targeted micro-segmentation of their consumer base to deliver personalized campaigns, improve customer experience and predict and prevent churn.
Big data and analytics solutions enable CSPs to:
–Deliver personalized offers and improve conversion rates. The right offers at the right time, in the right context to the right customer. Examples include personalized data top-up plans or up-sell recommendations based on data usage; device upgrade campaigns based on specific customer preferences; and discounts or tailored offers based on recent purchases, enquiries or calls into the support center.
–Drive down customer churn through predictive modeling. Telcos can use effective churn analytics to identify “at-risk” customers and proactively reach out to them with targeted retention programs.
–Deliver proactive care. Using big data, telcos are building intelligence and analytics tools to proactively identify issues and offer solutions before they impact the customer. Not only does this provide a compelling customer experience, but it also deflects and prevents calls to customer care centers, thereby lowering support costs.
Network optimization and planning
Network capacity is a highly valuable resource. Telcos are starting to leverage big data analytics to monitor and manage network capacity, build predictive capacity models and effectively plan for spikes or outages. Using big data analytic tools, CSPs can:
–Prioritize network expansion for new capacity rollout by visualizing and pinpointing highly congested areas where network usage is nearing its capacity threshold.
–Manage and improve user experience by building real-time capacity heat maps that alert teams of network congestion or potential outages. Service providers can now in real time model the potential impact in of a particular cell site going down based on the number of subscribers and capacity in adjacent sites.
–Plan preventive maintenance. Based on data collected in real time from cell towers, engineers can monitor any drop in service performance at a specific location and send in crews, if need be, for proactive resolution.
Operational analytics
Another key area of application for telcos is the use of big data to drive internal efficiencies, process improvements and cost savings around core telco operations. Operators are starting to adopt big data solutions powered by Hadoop for everything from plugging and minimizing revenue leakage, to tackling fraud, to managing network and cyber security and driving down order-to-activation lead times. Some prominent use cases include:
–Revenue leakage and assurance. Leveraging Hadoop and big data solutions enables operators to examine and plug dozens of actual or potential leakage points through the network and customer-facing systems, and to correct data before it reaches the billing system.
–Real-time fraud detection and management. Utilizing big data-enabled fraud detection and visualization tools, CSPs can detect and act on fraud in real time, helping them combat growing fraud issues such as roaming fraud, premium rate service fraud and subscription fraud.
–Cyber security and information management. Telcos are increasingly relying on Hadoop-based big data platforms to detect security incidents, mitigate risk and respond to breaches in real time. These solutions enable operators to collect and analyze large amounts of log data to detect anomalies that will in turn create an event for a security analyst.
Data monetization
Data monetization is increasingly starting to gain importance as a significant use case for service providers. Given all the data they have at their disposal, CSPs are starting to mine, model, aggregate and anonymize their data sets to create powerful statistics that can be of significant value to other businesses. Two of the most compelling use cases here include:
–Data analytics-as-a-service. Using big data solutions, CSPs can now combine key customer demographics and preferences along with location and social data to provide DAaaS to other key verticals including: retail, financial services, advertising, healthcare and the public sector. If executed right, with the appropriate governance controls and data access permissions in place, CSPs have a tremendous opportunity to monetize data and insights by making them relevant to other businesses and verticals without compromising subscriber privacy and rights.
–IoT and machine-to-machine analytics: Due to their inherent proximity to data generated, CSPs can play a dominant role across the “Internet of Things” value chain; from collecting the streaming data, to processing, storing, analyzing and serving intelligence back to end customers. With petabytes of data streaming in real time and in multiple formats from sensors across multiple geographies, CSPs are leveraging Hadoop as the ideal platform to collect, store, secure, manage and analyze these data sets in real time.
These are just some of the more prominent use cases that telcos are using big data to address, presenting tremendous opportunities to enhance customer experiences, build more efficient networks, drive down costs and open new revenue-generating engines.
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