• October 30, 2018
  • By John Chmaj Senior Practice Director of Knowledge Management, Verint Global Consulting Services
  • Article

Finding the Knowledge “Sweet Spot” for Self-Service

Self-service is one of the most powerful applications of knowledge management. Customers can get answers quickly, and organizations can maintain customer satisfaction while spending pennies on the dollar over assisted support options.

To get the most out of self-service, your organization needs to provide the best knowledge for each support tool, while preserving the accuracy and efficiency of managing “one source of the truth.” This requires a clear definition of the customer expectations and best knowledge interactions within each knowledge delivery tool.

Self-service can encompass a wide variety of knowledge delivery environments, as shown in this graphic.

The Customer Self-Service Spectrum

Each support channel has a “sweet spot” where customer needs, knowledge, and channel interactions meet. It’s critical to define what knowledge to deliver, and how to get the most out of each environment. These definitions drive knowledge management actions to help ensure consistent, reliable outcomes for each interaction. Here are some considerations for the top self-service channels:

IVA, Automated Chat, Assisted Chat

Usage scenarios include conversational, contextual “chats” processed by AI, with robotic technology (or humans) to respond to natural language questions and provide interactive sessions. As questions are asked, the system processes and responds to the evolving context of the question or topic and can ask clarifying questions, provide examples and responses, and hone in on the best answer. This enables the system to deliver concise information that directly answers a question, data that supports a structured inquiry (e.g., schedules), or lists of relevant knowledge results.

Sweet spot: Driving knowledge that fits the scope of each type of interaction from direct, short answers, to database-driven results, to simple knowledge articles.

Web Knowledge Base

Usage scenarios include natural language or keyword queries, browsing targeted topics, or reviewing results generated from pre-set context. The search engine derives the best results and the system has the capability to filter in more advanced ways if a topic needs to be explored in greater detail. This channel enables users to hone in on knowledge items, including filters, suggested queries, landing pages, links, and content types. Articles and content with support focus can leverage good knowledge structures and inter-relationships to enable accurate navigation to potential answers.

Sweet spot: Defining consistent, task-focused content structures, accurate and intuitive tagging, and customer-focused language for ease of use.

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