Until recently, Verizon primarily relied on customer feedback to understand when the speed and quality of its service was falling short of expectations.
In recent years, however, following a large investment in analytics and AI-driven technology such as machine learning – in part subsumed through the company’s 2017 acquisition of Yahoo! and it’s research units – a different approach is bringing impressive results.
Now it’s predictive analytics algorithms monitor 3GB of data every second streaming from millions of network interfaces – from customers’ routers to an array of sensors gathering temperature and weather data, and software which “listens in” on operational data, such as billing records.
Verizon’s director of network performance and analytics, Matt Tegerdine, told me that in 2017 this analytics infrastructure allowed them to predict 200 “customer impacting” events before they happened and take steps to prevent them occurring.
Source: Bernard Marr | Forbes