Nokia unveils machine learning-powered customer experience solutions

Staff writer
Telco Analytics Asia

Nokia has powered major updates to its Motive Customer eXperience Solutions (CXS) software portfolio, promising communications service providers with advanced machine learning capabilities to reduce costs and improve customer experiences.

Nokia Motive Service Management Platform (SMP) 7.0 and Motive Care Analytics (CAL) 2.0 use machine-learning algorithms developed by Nokia Bell labs — advanced capabilities that give computers the ability to learn without being explicitly programmed.

With support for machine learning in its CXS portfolio, Nokia aims to set a new standard for proactive care in the industry, dramatically improving the detection, troubleshooting and resolution of subscriber issues.

Nokia Motive SMP 7.0 features Dynamic Intelligent Workflows, a new self-optimizing system that determines the ideal sequence of tasks that deliver the highest probability of resolving billing, subscription and network service issues in the shortest amount of time.

By analyzing data from previous workflow executions, the network, customer premises equipment, and trouble tickets, this capability enables service providers to quickly find the optimal remediation to issues when subscribers contact help desk agents or use self-care.

Nokia Motive CAL 2.0 is the first solution of its kind that automatically correlates customer help desk calls and self-care actions with network, service and third-party application topologies to identify call anomalies, such as unusual patterns in help desk calls that indicate the location of customer-impacting network and service issues.

Together, Motive SMP 7.0 and Motive CAL 2.0 help service providers lower costs by reducing average help desk handling times 5% to15% and eliminating inappropriate truck rolls (dispatching a service technician to a customer location) related to network outages by as much as 90%.

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