By Anindito De, Solutions Head, Information Management, Wipro Ltd

Telecom service providers across the globe are faced with challenging market conditions, coupled with declining revenue. High subscriber churn rates as a result of network congestion, increased competition from Over-The-Top (OTT) services, and a shift towards data-based voice communications are all playing a role in driving these challenges. Telecom providers must therefore focus on maximising revenue from existing customers while reducing customer churn, in order to remain competitive in this environment. The customer experience has become essential, and delivering proactive customer care, predicting early triggers of churn and preventing deteriorations in the service experience are critical. Achieving this requires intelligent network data analytics to provide timely insight and enable agile response times, preventing revenue and customer loss.

One of the issues facing telecom providers currently is that they remain unaware of negative customer experiences, which can cause customers to switch service providers, or changes in usage patterns that could indicate an opportunity for a service upgrade, until it is too late. Service providers only become aware of these issues if a customer reaches out to the contact centre, which is often not the case. In addition, there is often a delay between customers complaining or bringing an issue to light, and an appropriate response. There is also frequently a lag between altered usage patterns and optimised offers for a service upgrade. In other words, timely responses to events are not intelligent or subscriber-aware, while intelligent and subscriber-aware responses are not timely. This lack of insight and delayed response time typically translates directly into lost revenue.

Customer churn is a real challenge, as service providers lose not only the cost of acquiring the customer, but also the revenue for a year or more when a customer leaves the network. To remain viable, telecom service providers need to hold on to the customers they have and find better ways to increase their share of each customer’s wallet - they need to improve their ability to detect and convert revenue enhancement opportunities. The solution is a telecom data analytics system that can detect churn risk and revenue enhancement opportunities from live subscriber call behaviour and initiate dynamic real time responses. Through the use of near real-time integration and analysis of multiple data sources and predictive statistical models, telecom providers can expect to see a 12% to 25% reduction in churn and up to 40% increase in the average revenue per VIP user.

As a result, any response to these events is reactive, and the majority of service providers have had limited success in keeping pace with rapidly changing customer preferences and usage patterns. Usually, by the time they do react, the opportunity is lost.

Utilising event analytics, data collection, integration, analytics, and business rule-based, near real-time event processing, service providers can improve this process, reducing churn and boosting per subscriber revenue. Near real-time information is gathered from multiple sources through integration of network data, the detection of significant event patterns from live network data, and correlation of network events with contextual insight like customer preferences, usage history, call centre interactions and customer segments from business systems. Predictive analytics and complex event processing can then be utilised to quickly determine right action to mitigate the potential risk or convert the opportunity. This requires awareness of generic, local, and customer-specific data points, the application of predictive statistical models, and complex event processing to identify the next best action. In addition, it required the flexibility to change threshold parameters easily to run marketing campaigns based on dynamic feedback from different market segments.

A study conducted by Wipro of operators that have applied similar methods to those described above highlights a number of benefits achieved, including revenue growth through cross-sell and up-sell opportunities. In addition, these service providers experienced enhanced customer satisfaction, reduced customer churn, and improved campaign management utilising event-based marketing techniques and customised campaigns.

Advanced network analytics can help service providers to not only differentiate themselves from the competition, but also reduce churn. It also delivers predictive and proactive visibility of the subscriber service experience, a network-centric and device-centric view, and application usage and its related service experience. This in turn empowers service providers to transform their customer service, enabling smart customer and network care that delivers an improved customer experience and therefore improved revenue and more satisfied, more profitable customers.