Mobile networks are increasingly complex to manage. Over the past three years, outages have increased by 46% with little end in sight given traffic is forecasted to increase by over 700% within four years.
In the midst of this, mobile customers have higher expectations. Net promoter score (NPS), the key predictor of customer lifetime value and propensity to churn, is now 49% dependent on users' network experience. Beyond outages, frequent degradations that impact their ability to get things done are now responsible for 98% of customer dissatisfaction. Fixing the user experience is paramount in a time of single-digit margins, uncertain financial conditions and the race to build out 5G.
But user experience is largely invisible to operators. Existing monitoring systems that report aggregate KPIs over 5 to 15 minutes can't resolve the individual user experience, so impairments often go unnoticed. The call center is usually the first to know when there is a problem, but since subscribers are more likely to churn than call, it's often too little, too late.
In response, operators are now turning to machine learning-based analytics to enable them to quickly cut through seas of alarms to find fault origins and maintain user experience. This webinar will show early examples of the new visibility these techniques enable at three leading mobile operators in Europe, the Middle East and North America.
Specific topics to be addressed in this webinar include:
(Source for statistics: GSMA 2020, Heavy Reading, 2019-08 global MNO survey for EXFO)