Call centers have long been front and center in providing customer service and support — in fact, IBIS World estimates that there are 36,787 customer care centers employing 305,000 individuals in the United States.
Despite the widespread proliferation of call centers, there is no denying that not all centers operate at the same level of efficiency. This can have a direct impact on the customer experience and influence the public’s perception of the business. However, the introduction of AI is having a noteworthy impact in this space as well.
As Han Butler, president and co-founder of ROI CX Solutions, a company that provides call center and help desk services, explains, AI offers several simple yet meaningful ways to improve call center efficiency.
1. AI-Powered Predictive Call Routing
“One of the best ways AI can help call centers is through predictive call routing,” Butler explains. “This builds off interactive voice response (IVR) systems but goes further by using AI to analyze call history, sentiment and preferences to match customers with the best agent.”
Instead of navigating long menus, AI can recognize repeat callers, predict their needs, and route them efficiently. Furthermore, AI considers agent expertise, past resolution success, and real-time traffic to optimize response times. By reducing transfers and wait times, AI-driven routing enhances both efficiency and customer satisfaction, creating a more seamless support experience.
2. Offer AI-Enhanced Knowledge Bases
AI-powered knowledge bases significantly improve call center efficiency by providing agents with instant access to accurate and up-to-date information. “AI allows call centers to build knowledge bases trained on company-specific data, including products, services, policies and procedures,” Butler explains.
These customized language models generate quick, reliable responses, helping agents find answers faster and resolve issues correctly on the first attempt. By reducing search time and improving accuracy, AI-enhanced knowledge bases streamline support, boost agent productivity, and enhance the overall customer experience.
3. Provide Real-Time Coaching to Support Agents
The potential for natural language processing (NLP) to provide real-time assistance during a call gives Butler even more reason to be enthusiastic regarding AI’s potential in the call center space.
“NLP tools have the ability to act as a type of copilot for the call center agent as they listen to the conversation,” Butler explains. “The NLP can detect changes in the caller’s tone and sentiment or identify key words and phrases. It can then deliver these insights to the call center agent in real time, helping the agent adjust how they address the customer. Picking up on these cues an agent might miss on their own helps the agent deliver the right kind of support for each specific situation.”
4. Use Chatbots for Simple Inquiries
Unsurprisingly, the increasingly prevalent presence of chatbots also plays a role in improving call center efficiency, in large part by taking care of simple inquiries in place of human agents. Unlike traditional chat systems that rely on scripted responses, modern AI chatbots leverage advanced natural language processing (NLP) to understand customer questions, provide precise answers, and adapt to different conversational contexts. Chatbots are capable of answering roughly 80% of routine questions.
When a request requires deeper expertise, AI chatbots intelligently detect when to escalate the conversation, seamlessly transferring customers to a human agent without unnecessary delays or frustrating dead ends. By taking over routine inquiries, chatbots ensure that call center agents’ time is reserved for the customers who need a deeper and more personalized level of support.
5. Measure Key Analytics
Call centers rely on a wide range of analytics, but actually understanding and making use of this data is often easier said than done. Butler sees AI as a solution for gaining more actionable insights out of what might otherwise be an overwhelming level of data.
“AI analytics can help call centers measure a wide range of metrics, such as call times and first call resolutions for both individual agents and the call center as a whole,” he says.
“More importantly, AI can flag and highlight information that has the biggest impact on the call center’s KPIs, including issues that might otherwise get overlooked. This can help guide agent training or other efforts that a call center might need to implement to improve its efficiency and customer service scores.”
6. Develop a Proactive Approach
As an extension of AI’s ability to measure key call center analytics, AI’s potential to dig deeper into call center trends can lead to organization-wide benefits. By using AI to categorize calls based on sentiment analysis or keywords, call center agents can more easily identify recurring issues and their surrounding context.
With these insights, call centers can become more proactive in addressing customer service problems and even communicate information to the larger organization to help resolve major problems.
Improved Efficiency, While Keeping the Human Element
As Butler’s insights reveal, the use of AI in the call center space isn’t designed to replace human support staff, especially since research shows most people would rather talk to a real call center agent.
Instead, proper implementation of AI can improve the efficiency and skill level of call center staff, helping them focus on higher-level activities and work in a way that will better resolve the needs of those who call. With the strategic implementation of AI, call centers can deliver a better experience for callers and agents alike.
