Contact center AI and knowledge management combine to create an agile process focused on improving every customer engagement and every agent on the team.
The use of knowledge management in contact centers is known to increase customer service agent productivity, consistency in replies, the use of new information, and compliance with industry norms. This is far from a complete list of its advantages. Today's worldwide contact centers are considering new business models. Recent changes include the move to remote work, hyper-automation, and the fast adoption of platforms and applications that allow customers to "control their experience" via self-service.
Enterprises nowadays seem to be taking every conceivable measure to cut operational expenses while providing more and better consumer experiences. While doing more with less has benefits, it might backfire if not done appropriately. For example, sensitive and confidential client information must not be compromised in a compliance-driven business such as banking or insurance, and practical compliance monitoring and mitigation must be in place.
This is where AI-based solutions like knowledge management and contact center AI may help.
1. What is AI-based knowledge management?
2. The reliance of agents on knowledge management
3. The impact of digitalization on customer service
4. The Advantages of Knowledge Management
5. What is contact center AI?
6. How Does AI in Contact Centers Improve Knowledge Management?
7. Two-for-One: Contact Center AI and Knowledge Management
AI-based knowledge management employs machine learning, natural language processing, and semantic search to identify keywords linked to client issues and promptly provide relevant knowledge articles to support agents.
It decreases the work required to obtain information, reduces agent error at contact centers, and ensures that critical customer service KPIs are satisfied.
A contact center agent serves as the company's initial point of contact with its consumers. As a result, they become brand ambassadors for their respective companies, and consumers look up to the firm based on their interactions with the agents.
A contact center agent's primary tasks and duties include:
Customers are growing more tech-savvy as the global contact center solution ecosystem changes with time and technology. Auxiliaries are no longer optional as consumer demands rise. Customers now want better, quicker, and more intelligent responses. Thus, if businesses want to keep and grow their client base, they must prioritize the customer experience. It can be accomplished with the correct Knowledge Management Software, propelling a corporation to the top of the ladder.
Establishing a culture of structured knowledge base and information is vital from the start. If you haven't already done so, with agents working remotely, it should be your priority.
In today's environment, information overload is a huge concern, and difficulty discovering and acting on valuable information further adds to it. Enterprises should maintain a consistent repository for internal and external customers that can access at any point in the customer lifecycle. You don't have to generate information; in many circumstances, you can reuse it across channels while creating new versions to keep your contact center expertise up to date.
We've witnessed again and again how clients receive various replies from different workers and get locked in a never-ending cycle. We've seen CX executives get agitated by poor customer satisfaction (CSAT) and first call resolution (FCR) metrics, as well as the pressures of a high average handling time (AHT) and total OPEX expenditures.
Taking a step back and doing a root cause analysis (RCA), teams may find that the representative provided erroneous information to the consumer. Agents can't put consumers on hold, go down the contact center floor, and seek fast support from a supervisor or subject matter expert (SME) to answer complicated customer issues and increase the wait time for the customers.
Agents are the heart of a contact center, connecting with consumers regularly. Their views and opinions are constructive. Consider having an obsolete workflow or procedure in place even after rules have changed.
Agents can instantly spot concerns, and the knowledge base content may be amended swiftly. Simultaneously, teams may receive insights on top-ranking content and relevant articles throughout the contact center by analyzing which agents and groups interact with which assets. They may also find other channels to proactively educate clients on how to own their experience and prevent repeat calls, especially for less-complex concerns. It allows support professionals to spend more time on complicated inquiries and create stronger customer connections.
Organizations are turning to AI-enabled tools to manage better remote agent performance, customer experience, and operational efficiency. Speech analytics and contact center AI are examples of such technology. To revolutionize the customer support experience, contact center AI combines speech analytics and quality management in a single platform. It enables businesses to transcribe and analyze 100% of voice calls to ensure call quality and compliance.
Consequently, compliance monitoring, agent performance, and overall customer experience have all improved significantly.
Contact center AI provides firms with detailed analytics on key contact center KPIs such as AHT, supervisor escalations, and sentiment. They may share these insights across businesses, business lines, and even down to individual agents to know what's going on with every call. It answers issues such as, "Are agents adopting new messaging?"
Operations and Customer Experience Leaders evaluate 100% of voice conversations to get insights and, as a result, promote efficiency across the business.
Supervisors and Trainers increasingly use relevant and engaging coaching programs to transform their agents into top achievers, particularly in Learning and Development.
Quality Analysts use speech analytics and quality management technologies to monitor CSAT and compliance interactions and impact agent coaching. Agents are given feedback that is transparent, data-driven, and objective.
As we've all heard, this call will be recorded for training and monitoring reasons. However, how many of these calls are answered by qualified analysts? Typically, it is about 1-2% or less. Complexity emerges in the feedback loop as quality analysts and supervisors handle different platforms and spreadsheets to analyze calls, rate interactions, and adjust agent behavior.
This is where contact center AI comes into play. When AI is used to expose the most significant exchanges and areas of interest in conversations, the team can assess more calls at a greater level of quality. Supervisors, in turn, may teach with the why and offer the context and data agents need to modify essential behaviors.
Contact center AI can take the uncertainty out of your quality management process, from utilizing suitable openers to checking that staff follows standard operating procedures on audio conversations.
Contact center AI teams, for example, can instantly recognize dead air, which may signal a lack of agent confidence or training. It can also detect hold time violations, harmful or good attitudes, supervisor escalation, etc. By highlighting polarity in conversations, agents may get personalized instruction and be better prepared to manage difficult circumstances.
Contact center executives are eager for information to drive improvements and quantify tactics that may use. With contact center AI, these executives can search for keywords and essential interactions across every conversation to uncover emerging common themes and obtain insight into what may generate them.
Teams may work on context and data-backed conclusions rather than preconceptions. As a result, they may more effectively teach agents how to identify and fulfill unmet requirements, such as requests for future goods and services or new places for the company to operate in.
By combining contact center AI with knowledge base management, an agile workflow is specifically tailored to optimize every customer encounter and every agent on the team.
Consider the following real-world example:
Assume you've received a call from a dissatisfied client over an inaccurate credit card transaction. Contact center AI records what the client says and decides if the call is wrong. At the same time, Knowledge Management may generate a decision tree on the best course of action to follow to resolve this client’s issue. As the agent gives the necessary information, the client starts to feel better but then raises a question to which the agent is unsure how to react. Contact center AI detects hesitation and recognizes Dead Air. Finally, the agent can summon their supervisor and rectify the issue. They may also submit feedback to their Knowledge Management System if a resource needs to be updated.
Operator Response: Simultaneously, the contact center operator may notice using contact center AI that this difficulty on calls concerning improper credit card charges is increasing bad attitude and Dead Air. They may implement new protocols with context.
Supervisor Action: Supervisors may use an agent leaderboard to determine which agents are experiencing extended durations of Dead Air and train them on various strategies to attempt with clients when they don't know the solution right away.
That is how future contact centers will work, increasingly in real-time, as they supplement agents on live conversations with the right resources and at the right moment, which are surfaced based on speech recognition. Then, agents can listen, and companies can continue to invest in training and to strengthen their frontline brand advocates, who are often the only individuals who truly humanize and assist clients in developing an emotional bond with their brand.
Knowledge base management offers hundreds of additional benefits that directly influence the experiences of your workers and consumers.
The ultimate goal of a knowledge base management system in a contact center is to establish order and simplicity for agents by integrating all required information into one area. It is a crucial component of both the agent and consumer experiences. So, conduct your homework and choose the best system for your company.
You may utilize C-Zentrix to automate maintenance, obtain deep insights into user activity, and increase content findability using knowledge management platforms like CZ Guide.
Author Bio: Akshay