What You Don't Know Will Cost You: Analytics Enrichment to Manage and Grow Revenue
The revival of mediation in an analytics world
Mediation in telecom has traditionally been restricted to the collection and distribution of data from and about the network to support billing and assurance. However, the management of all the events related to a customer – not just billing transactions – is critical to fully understanding customer behavior and better managing both the customer experience and the revenue impact. As customers demand immediate access to an infinite number of applications using a wide variety of devices and access methods, the need for real-time and sophisticated Event Management has grown. Event management is more than the collection and processing of xDR’s. Event management addresses the gamut of customer-related events. By supplementing event management capabilities with predictive analytics, operators are empowered to better understand the impact of customer behavior on revenue, reduce revenue leakage, prevent fraud, and offer products targeted to specific customer needs.The biggest challenge is data volume. Millions, even billions, of events are collected every day from network probes and management systems. Add to that the specific nature of individual customer behaviors in near real time and you have a daunting task that can only be accomplished using sophisticated analytics and automation. Predictive modeling that incorporates multidimensional, nonlinear analysis and millions of values from dozens of sources delivers customer insight and revenue-management benefits beyond what is possible given the reality of existing stand-alone systems and data.
Revenue assurance and fraud are also major concerns for network operators and connected service providers. The application of sophisticated analytics at the resource layer correlates data from multiple sources inside and outside a company's business to rapidly detect and mitigate fraudulent activity. A supercharged mediation engine that's combined with sophisticated customer analytics and is capable of real-time, large-scale data collection, correlation, processing, and distribution is necessary in order to understand the nature of fraud and revenue leakage so that thee problems can be prevented.
In addition to recovering lost revenue and reducing risk, there is growing demand from marketing and product-development groups to define, promote and sell products that individual customers actually want. Using analytics enrichment, CSPs can offer more relevant products by understanding who the most likely customers are for each product and which ones are most suitable for them. Without offending or upsetting those customers, each touchpoint becomes a sales opportunity based on predictive intelligence rather than human assumptions.
The ability to manage the breadth of customer events and data, apply sophisticated analytics and deliver actionable results in near real time helps operators recover lost revenue, understand the impact of customer behaviors on revenue generation and identify opportunities to increase sales and customer satisfaction.
Comptel’s predictive and automated analytics solves the problems of Big Data with powerful, machine-learning capabilities that ensure that automated actions are taken at the right time for the right audience with the right context. In this way CSPs can leverage Big Data analytics to customize their marketing campaigns to each individual customer’s preferences and unique needs. More importantly, the insights that are delivered are helpful to a company's overall business strategy, making it easier to integrate analytics into operations and customer-loyalty and marketing programs.
