• April 19, 2019
  • By John Chmaj Senior Practice Director of Knowledge Management, Verint Global Consulting Services
  • Article

Contextual Knowledge: Your Key to Building Effective Knowledge Tools

Knowledge has been defined as “information provided in the context of a specific need.” As such, context is the driving force behind targeted, personalized answers that make knowledge delivery systems efficient and accurate.

Increasingly, knowledge users expect the context of who they are, what they are doing, and what they need to drive the information and actions presented to them. “Contextual knowledge” is critical for delivering KM value by facilitating faster, better answers and information, dynamically presented in the context of the user’s work. Let’s take a look at how contextual knowledge can turbocharge customer support and the overall customer experience.

Defining Context

In the realm of knowledge management, “context” refers to the properties of both the requestor and the information requested that frame and scope the knowledge need. Context can be any information property, fielded information, or text that can contribute in a meaningful, predictable way to help assess information requests. Context can include a variety of criteria:

♦ Identity: Who is asking?

♦ Issue: What they are asking about?

♦ Actions: What they are doing?

♦ Location: Where are they situated?

♦ Application: How they are interacting?

♦ Information Type: What types of information would serve them best?

Enabling Context

Context can help drive the best knowledge forward in several ways. Depending on the tools and working environment, context can arise from and be processed through:

♦ Customer account systems

♦ Actions and locations in digital workspaces (web, chat, email, intelligent virtual assistants, and social channels)

♦ IVRs or call management tools (including real-time speech analytics)

♦ Agent desktop metadata, forms, and workflow states

Context gathered from these environments can be linked to appropriate knowledge through metadata scoping, search string generation, direct content identification, natural language processing, and/or machine learning.

The output of context can influence what is delivered in different ways, depending on the capabilities of the KM system:

♦ Specific objects can be returned that directly match the context of the request.

♦ Groups of information that match the context can be presented in a results list.

♦ Some objects can be promoted or preferred in relation to others in a knowledge list.

♦ Activities can be triggered based on context, such as fetching additional context from other tools, initiating specific functions in a knowledge tool, or presenting requests for additional information to further refine the knowledge request.

Depending on the audience for the content, these enabling methods and their results can be broadly or narrowly focused. The key to enabling context effectively is to have a clear understanding of how each element of context can best scope information in the tools and knowledge base in play.

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