Solutions use Nokia Bell Labs advanced machine learning algorithms to deliver new levels of proactive care and represent significant first steps in bringing autonomous capabilities to the customer care process.
Reduces help desk calls due to outages by 85 percent, shortens average call handling times by 5 to 15 percent, and eliminates inappropriate truck rolls by up to 90 percent.
Updates to Nokia Motive Customer eXperience Solutions (CXS) portfolio include: Nokia Motive Service Management Platform (SMP) 7.0 and Motive Care Analytics (CAL) 2.0.
17 November 2016
Espoo, Finland - Nokia today announced major updates to its Motive Customer eXperience Solutions (CXS) software portfolio, providing 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. Once anomalies are identified, Motive CAL initiates actions through Motive SMP to resolve service disruptions and other issues before they become widespread problems, triggering call deflection to IVR systems and OSS alarm correlation for rapid fault localization and identification.
Together, Motive SMP 7.0 and Motive CAL 2.0 help service providers lower costs by reducing average help desk handling times 5 to 15 percent and eliminating inappropriate truck rolls (dispatching a service technician to a customer location) related to network outages by as much as 90 percent. They also enable service providers to improve customer satisfaction and reduce churn by eliminating 85 percent of outage-related help desk calls.
Bhaskar Gorti, president of Applications & Analytics at Nokia, said: Service disruptions are often hard to identify because they happen in the access network, on customer equipment or on customers devices. 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. 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.
Sheryl Kingstone, research director, Business Applications at 451 Research, said: Reducing the complexity around customer care, providing a personalized experience and introducing self-service are key to maximizing customer satisfaction and improving Net Promoter Scores. By embedding machine learning into customer care offerings, operators can provide relevant and engaging customer journeys across new channels of interactions, which are integral to success in todays digital world.
Nokia Motive SMP and Motive CAL build upon Nokias leading customer care solutions, including Motive Home and Access Analytics, which enables operators to identify and resolve issues proactively before they affect the customer experience. Powered by Nokia Bell Labs machine learning algorithms, the new Motive SMP and Motive CAL solutions represent the first steps in Nokias effort to bring autonomous support into the digital care process.
Nokia Motive SMP 7.0
Nokia Motive SMP is a customer experience platform for home, mobile and enterprise devices and services, enabling service providers to adopt care processes that deliver the highest possible customer satisfaction at the lowest possible cost. Motive SMP provides a foundation for deploying service management as part of an agile omni-channel customer experience strategy.
Key features of Motive SMP 7.0 include:
Dynamic Intelligent Workflows that drive actions with highest predicted resolution for a customer at the time they call or use self-help
Omni-channel service modeling and management of business logic that render unified and relevant content to different audiences and a consistent user interface across channels and devices
Drag-and-drop interface that makes it easy to build and deploy advanced workflows
Robust integration framework that enables: New data source adapters for underlying systems to gather the information required by models; end-to-end service management across operations support/business support systems; and prescriptive workflow actions
Motive SMP delivers the continuous improvement and agile introduction of new business and technical processes, enabling customers to avoid lengthy IT cycles in implementing new capabilities. Runtime updating of business logic reduces the time required to introduce new logic into the network. Dynamic Intelligent Workflows streamlines this process
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Solutions use Nokia Bell Labs advanced machine learning algorithms to deliver new levels of proactive care and represent significant first steps in bringing autonomous capabilities to the customer care process.
