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We’ve all had our experiences with call center agents who can’t answer questions or get us to the right person for the right answer. This makes it all the more important for technologies like voice-based data analytics and artificial intelligence (AI) to bring relief to call centers and those who are calling those centers.

“The general challenge that the call center industry faces is that call center agents lack data access at the right time and the right place,” said Jafar Adibi, head of AI at Talkdesk, a provider of cloud-based software for call centers.

Equally important is understanding the context of the dialogue that you’re having with a customer. What is the customer’s history of dealing with the company? In addition to what the customer is saying, what tones of voice can be detected that might indicate whether the customer is frustrated?

SEE: 60 ways to get the most value from your big data initiatives (free PDF) (TechRepublic)

“Call center agents are the heart of the call center,” said Adibi. “If you can’t help them enhance their knowledge bases, or assist them during their interactions with customers, it becomes difficult to improve call center performance.”

Here are some ways that AI and voice-based data analytics can enhance call center agents’ performance.

Providing the best call center agent for each customer

The goal is to make each call center agent your “best” agent, but every agent isn’t going to be an expert on every call.

“What AI can do is understand which agent is best suited for which type of call and automatically route the call to that agent,” said Adibi. This makes it less likely a customer will be transferred to a chain of different agents, which means there’s less opportunity for frustration, and the customer ideally gets his or her question answered promptly.

Understanding the customer’s emotions

AI as a big data analyzer can look at voice-based data as it comes in from the caller and determine emotional content in the person’s voice, such as a heightened sense of frustration, anger, or even satisfaction. These signals can be fed to the call center agent in real time, as well as logged for call center managers so they can assess customer sentiment.

Training call center agents

Voice-based data from call center agents can be assessed for training and coaching purposes. For example, a call center supervisor can listen to voice-based data and determine if an agent is talking too fast or unclearly. The supervisor can coach the agent on how to hone their skills, which will ultimately improve call center performance.

Smart dialing software

If call center agents are marketing or soliciting business, smart dialer software can determine the best times of day to reach a customer.

Understanding what customers want in real time

“If you have a call center with 50 or fewer call center agents, you probably don’t need AI software, but if your call center contains 50 or up to thousands of call center agents, you want to understand what your customers want, and AI can help,” said Adibi. “By using a call center AI software, you can look at 16 months worth of data to see what the most common call-in topics were and why customers are calling. This helps you to better prepare your agents for the calls that they are most likely to receive.”

The most exciting thing about call center big data analytics and AI is that it can operate in real time–this gives call center agents and their managers up-to-the-minute data when they need it.

“The past few years have seen dramatic improvements in computer processing and memory and also the ability to manage vast troves of big data,” said Adibi. “If LinkedIn, Facebook and Google can manage billions of members and transactions in real time, a call center certainly can manage a subset of that data to improve call center performance and also the satisfaction levels of those who are calling.”