As artificial intelligence (AI) continues its meteoric rise, the role of knowledge management (KM) in contact centers is gaining prominence like never before. Knowledge and knowledge management platforms are key building blocks for AI systems and applications such as customer self-service, agent assistance, chatbots, virtual agents, and many more. AI, bots, and automation depend on having the correct knowledge to extract in context with task flows or queries, and that knowledge is stored in knowledge bases. Getting to that knowledge is the challenge.
Knowledge management platforms help businesses store, organize, access and share knowledge with agents to help them better serve customers. This knowledge can include product information, customer support best practices, and company policies.
More than just a static repository of information, a knowledge management platform is a system that captures, stores, organizes, and retrieves knowledge. “Knowledge” encompasses a wide range of content, such as articles, videos, FAQs, and more, sourced both internally and externally. These systems help to ensure consistency, with a “single source of truth” for information.
Knowledge management platforms typically include a knowledge base, which is a searchable repository of knowledge articles, FAQs, and other resources that agents can use to answer customer questions. The knowledge management platform also has reporting and analytics to help businesses track the usage of their knowledge management platform and measure its impact on customer satisfaction and agent productivity.
More recently, these platforms have added agent assist tools that provide agents with access to knowledge bases, customer profiles, and other information while they are on a call or chat; the knowledge management platforms have also added self-service portals where customers can access knowledge bases and other resources to resolve their own issues.
Knowledge management platforms can be used in a number of ways. For example, agents can use a knowledge base article to learn how to troubleshoot a common customer issue, or use an agent assist tool to provide answers to a customer inquiry while on a call.
Some key knowledge management features include efficient search capabilities, tools for content creation and updates, and analytics tools for tracking performance. By consolidating knowledge from various systems to make it easily accessible, KM systems reduce the time it takes agents to research information and respond to customer inquiries. Agents don’t need to navigate different databases for information; they can access knowledge directly from their desktop screens, helping to better assist customers.
Initially developed to support agents assisting customers, KM solutions are increasingly being used to assist customers directly, providing improved self service capabilities and eliminating or reducing the need to speak with an agent for assistance.
AI is playing an increasingly important role in knowledge management. AI-powered search engines can understand the meaning of customer questions and return the most relevant knowledge base articles or help agents find the information they need more quickly to provide customers with faster and more accurate answers. With generative AI, knowledge management systems can generate new knowledge base articles, FAQs, and other resources based on existing content, helping businesses keep their knowledge base up-to-date and to provide agents and customers with the information they need more quickly.
Leading KM vendors include Bloomfire, eGain, NICE, Puzzel, and Verint. These vendors offer KM solutions that seamlessly integrate with CCaaS offerings to create complete solutions. Recently, several vendors have leveraged generative AI capabilities, producing more conversational and understandable information to both agents and customers.
There’s no shortage of options for knowledge management offerings. Here are some of the leading vendors in the contact center space.
eGain just released AssistGPT, an integral part of the eGain Knowledge Hub that is powered by Generative AI to provide a zero-code solution for Knowledge Automation. It helps create knowledge content and process guidance, can generate responses for agents, among many other things, and comes with an out-of-the-box prompt library.
Einstein Service Replies are grounded in knowledge and conversation history, enabling personalized agent chat replies to be automatically generated, reducing the time to create knowledge and making it easier to keep articles up to date. Einstein will also be able to auto-generate knowledge articles for evaluation based on successful customer conversation transcripts (currently in pilot).
Most of the contact center/CCaaS vendors have integration partnerships with KM vendors. For example:
As many organizations prefer reducing the number of vendors used, the trend toward single suite solutions with increased functionality has led CCaaS providers to integrate KM capabilities into their portfolios. Several CCaaS vendors have introduced their own KM capabilities:
In the era of AI and digital transformation, knowledge management's role in contact centers has never been more critical. It empowers agents and improves agent effectiveness, while also enhancing customer self-service experiences. With the addition of generative AI and LLMs, knowledge management's potential will continue to gain strength.
This post is written on behalf of BCStrategies, an industry resource for enterprises, vendors, system integrators, and anyone interested in the growing business communications arena. A supplier of objective information on business communications, BCStrategies is supported by an alliance of leading communication industry advisors, analysts, and consultants who have worked in the various segments of the dynamic business communications market.
