AI Gives Contact Center Knowledge Management a Boost

Most contact center leaders understand the potential and promise of knowledge management (KM) and self-service. Few, however, have experienced a successful or optimal KM project. But a new generation of KM is here—riding on the backs of breakthroughs in artificial intelligence (AI), automation, big data, and analytics.

Knowledge is at the core of everything a contact center does; connecting questions to answers is the primary function across all channels of the contact center. Successful KM affects nearly every metric, including handle times, call transfers, attrition rates, costs, first call resolution, and customer satisfaction. When done properly, contact center managers can use these metrics to create a positive impact. But to understand how to apply these metrics properly, we first need to look why so many KM and self-service initiatives fail.

Three Factors of KM Project Failures

The heavy maintenance and upkeep associated with traditional knowledge initiatives make it difficult to keep information accurate, up to date and trusted. Knowledge management is only a part-time initiative; admins put out fires and handle higher-priority issues throughout the day. Therefore, KM usually takes a back seat and begins to grow stale over time—affecting the ability of agents and customers to trust the knowledge base.

Findability has always been a crux of KM and self-service. And having multiple systems with old interfaces that aren’t designed to optimize search only compounds the problem. These scenarios can be even worse in environments with an outsourcer who acts as a Tier 1 provider. Frontline agents drive up costs by transferring calls to in-house resources when they can’t locate information—and that further degrades the customer experience.

Finally, a lack of metrics and ROI makes it difficult to oversee KM and prove its value over time. In the past, KM has been a black box of activity, making it difficult for admins to know exactly what to optimize and demonstrate its impact to management.

These challenges have long been a cause of frustration and anxiety across the contact center. Fortunately, major technology breakthroughs made over the last two to three years have addressed the traditional challenges of knowledge management.

Technology Trends for a Successful Knowledge Management Initiative

Four major trends help contact center managers create successful KM initiatives: the maturation of the cloud, the next generation of big data and analytics, advancements in AI, and new capabilities that automate knowledge discovery to drive changes that improve customer experience in completely new ways.

Technology is replacing knowledge tasks that required massive human effort. The chart below depicts how the burden on people to manage knowledge is shifting to automated, intelligent technology.

 

The current disruption to the knowledge management space transfers several human-driven tasks and opens the black box of KM activity to technology that provides transparency. It also significantly reduces administrative overhead and exponentially increases the effectiveness of a small number of people to improve the flow of knowledge in the customer experience department.

There are three major underpinnings for this change.

• Analytics provides insights into user behavior, content patterns and system performance that was previously unavailable.
• Automation takes the burden off administrators to keep content up-to-date, trusted and accurate.
• AI turns a previously flat, unintelligent system into a dynamic, constantly improving knowledge engine.

Traditional knowledge management is becoming obsolete—the age of knowledge intelligence is here. Managers and executives must rethink their knowledge strategies and consider integrating these breakthrough technologies into their planning. The next generation of KM can:

• Reduce handle time by 25% or more with AI-driven findability
• Save admins over 500 hours a year through automation
• Help the entire contact center gain insights into customer and agent behavior

Through the Genesys AppFoundry, you can leverage AI-based knowledge management solutions like Shelf to automate maintenance, gain deep insights into user behavior and improve content findability. Sign up for this short on-demand webinar today and visit Shelf.io on the AppFoundry Marketplace.