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Microsoft updates Dynamics CRM with a new IoT twist

Microsoft updates Dynamics CRM with a new IoT twist

A Connected Field Service tool focuses on predictive maintenance

There's an update available for Microsoft's Dynamics CRM 2016, and it brings with it a brand-new tool to help companies tap the Internet of Things for their customer-service efforts.

Announced on Monday, the Spring 2016 Wave of Dynamics CRM adds Connected Field Service, a new tool companies can soon use to leverage the potential of predictive maintenance via IoT devices.

Available as a preview in June, Connected Field Service continuously monitors IoT-enabled devices for anomalies, generating alerts that trigger automated actions or service tickets and workflow according to service level agreements. Service technicians with the right skills and tools are then matched against the service requirement based on availability and proximity and routed to customer locations for preventive action.

"For many service-oriented businesses, this represents a truly revolutionary shift from more of a reactive break-fix posture to a model that is built on predictive service," explained Param Kahlon, general manager of program management for Dynamics CRM.

Also new in this Spring Wave are Web portals designed to help companies engage external communities with self-service profile-management capabilities, rich content publishing, configurable extensions, and secure access and permissions controls. A customer portal, for instance, helps customers solve issues on their own, freeing up service agents to focus on high-impact issues. Also among the preconfigured solutions are portals for employees, partners and communities.

A new feature called Learning Path, meanwhile, offers guided navigation capabilities designed to help new application users get up to speed quickly. With personalized, context-sensitive and scenario-based tasks and sidebars, the tool walks users through the steps needed to complete a task.

Released in late November, Dynamics CRM 2016 is most notable for putting machine learning to work for customer service. An adaptive learning feature, for instance, determines how a product, campaign or brand is perceived on social media. Automated social triage detects intention in social posts and automatically routes them as cases or leads into the customer relationship management system.

An online event on June 7 will go into further details about the features available in the Spring 2016 Wave.


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