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Algorithms developed by Bell Labs claim to cut outage-related help desk calls by 85%.
Nokia on Thursday updated its customer experience solutions (CXS) portfolio to make use of machine learning algorithms developed by its Bell Labs arm.
The Finnish vendor claims that its new Motive Service Management Platform (SMP) and Motive Care Analytics (CAL) can reduce call-handling times by 5%-15%, and reduce unnecessary truck rolls to network outages by as much as 90%. They can also cut outage-related help desk call by 85%, Nokia said.
"Traditional customer care may only address a small part of a larger problem and the time-consuming, step-by-step troubleshooting process can lead to customer frustration and the risk of lost business," said Bhaskar Gorti, president of applications and analytics at Nokia, in a statement.
Nokia said its updated Motive SMP can determine the sequence of tasks that offer the highest probability of resolving billing, subscription and network service issues in the shortest amount of time. By analysing data from previous workflow executions, the network, customer premises equipment (CPE), and trouble tickets, it can enable telcos to quickly fix problems when customers contact the help desk.
Meanwhile, its new Motive CAL identifies potential network and service issues by automatically correlating customer help desk calls and self-care actions with network, services, and third-party application topologies.
Together, Motive CAL and SMP are able to resolve service disruptions before they become widespread problems, Nokia claimed.
"By providing the earliest possible detection of network issues and streamlining help desk and self-care interactions, these new Nokia solutions reduce IT and care costs, and result in happier, more loyal customers," Gorti said.
