Zendesk, Inc introduced Zendesk Guide, a smart knowledge base solution that captures the collective knowledge of an organization and combines it with machine learning (ML) technology to deliver a better customer experience. Guide empowers customer service agents to resolve inquiries with contextual insights and gives customers ML-powered self-service customer support. The result for both agents and customers is faster support resolution and outcomes from anywhere.
“Customers like the convenience of self-service and automation, but they still want answers tailored to their unique situation,” said Adrian McDermott, president of products at Zendesk. “Zendesk Guide meets this need by helping companies deliver knowledge to customers and employees with personalization through machine learning technology and context based on the customer’s journey.”
Through the use of a combination of the Zendesk API, Web Widget, and Mobile SDK as Zendesk Embeddables, Guide allows companies to deliver in-context support anywhere – apps and websites – meeting customers where they already are. And for customers who would prefer self-service, Guide makes self-service quick and convenient.
Zendesk Guide introduces two new capabilities to deliver faster resolution and better customer service: the Knowledge Capture app and Answer Bot. The Knowledge Capture app converts customer interactions into an opportunity for agents to capture and share information that enriches the knowledge base. Answer Bot utilizes information from the knowledge base, combined with advanced machine learning technology, to automate responses to customer inquiries for better service outcomes.
There are multiple challenges customer service agents face. For example, wasting time repeating themselves, providing the wrong answer to customers’ inquiries due to out-of-date knowledge articles, and losing product and client know-how every time a peer leaves the team. With the Knowledge Capture app, agents can share their collective knowledge with their customers and peers more effectively, reducing the errors caused by outdated information and improving the quality of the self-service content over time.
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