5 Ways AI Can Help Call Centres in Crisis

Jacada share five ways in which artificial intelligence (AI) can help support contact centres in the midst of the COVID-19 crisis.

It’s fair to say COVID-19 has changed the way businesses operate. Compare everyday life today with your daily concerns from a month ago. The difference is pretty stark.

Like everyone else, call centres have been reeling from the aftermath of the coronavirus. Paul Stockford, National Association of Call Centers Research Director, raised concerns about what he called a “pretty high” risk of exposure in those working environments.

It’s not difficult to see why experts like Stockford are so worried: contact centres manage a large workforce sitting in close quarters. Not to mention, agents often share their work surfaces with employees from different shifts.

Where does that leave companies? They want to meet customer expectations, follow public health guidelines, and protect their employees. Some businesses have embraced a remote workforce. Meanwhile, others have resorted to shutting down their call centres completely.

One avenue to explore is artificial intelligence. The latest AI-based call centre RPA tools support better customer experience from start to finish.

At the same time, they reduce the amount of work assigned to call centre agents. With cutting-edge AI solutions, customer service and support teams can do more with less.

Here are five ways artificial intelligence can become the hero during this recent pandemic.

No 1. Build Smarter Chatbots With Intent Recognition

Chatbots and virtual agents reduce the burden placed on call centre representatives. They answer basic questions and guide site visitors to extra support materials.

They’re also good at addressing simple problems and collecting information, but often, too simple. Most of us have tried to describe a problem to a chatbot only to get a response that didn’t come close to solving it.

What if chatbot software could understand exactly what you said? What if it could understand nuance? Then, chatbots might achieve some level of accuracy without redirecting to an agent.

If nothing else, they could gather more relevant details up front and share that information with a call centre employee.

Intent recognition is a component of AI that addresses this issue head-on. Using natural language processing (NLP) tools, virtual agents can analyse communications to determine what customers are trying to say. More importantly, NLP and AI platforms help chatbots recognize the user’s intent – that is, what they’re trying to do.

You can phrase a specific question in any number of different ways, but the intent will be the same every time. Let’s say you’re trying to check the status of an upcoming flight. You might say:

• Check flight status.
• What’s the status of my flight?
• Is my upcoming flight still scheduled?
• Has my flight been cancelled?
• Is my flight delayed?
• Did my flight get cancelled?

NLP and AI help virtual agents understand the shared intent behind all these prompts. Intelligent chatbots provide better customer experience without involving a call centre agent.

No. 2. Guide Conversations With Dialogue Management 

Part of what makes designing an effective chatbot so difficult is that the conversation could go in any number of directions. How do you plan for every prompt that a customer might give?

The longer a conversation goes on, the more likely a chatbot is to run into dialogue it doesn’t recognize or understand.

The answer is to guide the conversation in the right direction, so the user’s communications are more predictable. Dialogue management controls the back-and-forth between the virtual agent and the customer.

To be effective, this interaction must seem natural and organic. The customer should be unaware a chatbot is running an automated script or off dialogue tree if the chatbot is doing its job.

AI can improve dialogue management tasks so they give customers more relevant responses. It’s another way to get more use out of chatbots and reduce the burden placed on call centre agents.

No. 3. Understand How Your Customers Feel 

Call centres may be running with fewer agents for the time being, but they still need to maintain high customer satisfaction and service levels.

There are a lot of metrics companies use to measure agent performance – call time, ticket close rates, etc. – but they don’t always provide much insight into the customer experience.

To get a better insight into how customers feel, companies should turn to AI. It may sound counter-intuitive, but AI-based voice analysis tools can pick up on details that don’t show up in your usual call centre KPIs.

Sentiment analysis and emotional analysis technology assess chat logs, call recordings and other communications to determine how a customer’s attitude changed – or didn’t – during those interactions. Was an unhappy caller placated? Did the agent exacerbate the issue? Sentiment, tone and emotional analysis solutions can answer those kinds of questions.

Combine those approaches with text analytics, and you can gauge the customer experience without asking people to take part in surveys or provide feedback.

No. 4. Streamline Customer Support With RPA 

Have you tried calling an airline or health insurance support line recently? Call centres and contact centres across the world are inundated with requests from worried customers. The increased wait times create enormous customer friction.

Agents need to work through calls fast and still deliver best-in-class service. That’s not always easy with the different systems they need to shuffle between.

A simpler and more efficient way to manage call centre tasks is through robotic process automation (RPA). Customer service robots automate mundane, time-consuming tasks that may distract agents.

That way they can focus more time on the customer. The AI-enabled RPA bots work behind the scenes to gather information and process requests.

No. 5. Capture More Useful Information With Computer Vision 

An image can say more than words ever could. Take a car insurance claim, for example. It would be much more expedient to send a picture of a damaged car than to try and describe it in an email.

Over the years, AI technology has become good at analysing images. And computer vision is the next step in that evolution. This technology allows a customer to send images to a virtual agent from their smartphone.

Let’s say you have a defective or broken product. The AI software could identify the product model from the image and pull up warranty information, troubleshooting steps, or repair guides. It gives customers another avenue to address issues on their own if they choose. A call centre agent doesn’t even need to get involved.

AI is one of the most exciting fields of technology today. Call centres benefit from AI solutions as much as consumers, especially as this crisis continues.

Even though the world is changing all around us, AI customer service solutions are helping businesses adapt.

Author: Guest Author