kayla
Kayla Matthews
March 24, 2017
AI
Customer engagement
Customer Experience
Omni-channel contact center
Telephony

Get Ready for Big Data and AI In the Call Center

Get Ready for Big Data and AI In the Call Center

Reaching out to a call center and getting a machine is common these days. It’s no secret that many people prefer to talk to an actual human, though. If you’re one of those folks who prefers to have a “real” conversation, you might be a little disconcerted to hear this next bit of news.

Artificial Intelligence, or AI, may soon enter the call center. We’re talking full-blown Siri- and Alexa-like AI that can respond to queries and carry out various actions.

AI bots will power up to 85% of customer service interactions by the year 2020, which will lead to people having more conversations with bots than with their spouses.

It’s easy to roll your eyes or think of the negative when you consider this scenario, but call centers may actually be a perfect place for modern AI. Let’s take a closer look at why that is.

Advantages of AI in the Call Center

Did you know 32% of business executives claim voice recognition — a form of AI — is the most-widely used technology in their business.

And there’s one thing that Artificial Intelligence — or a computer — can do much faster than humans, and that’s referencing and inputting data.

Today, big data and modern analytics allow us to collect loads of information about nearly everything going on in the world. Brands have habit, purchase and trend data from their customers. Customer service teams have data on common problems with products and past claims. Marketing professionals have an endless supply of data on consumer trends and preferences. The list goes on and on.

The social media platforms, web applications and websites we visit are always tracking what we’re doing, when and how. This information is being stored, analyzed and leveraged to make our experiences that much better.

When you call in with a problem or a query, AI can immediately access an endless trove of data to find your answer. A human must first tap into a computer system physically and enter search terms, and it’s likely they would even have to search through listings to find the information they need.

Simultaneously, that AI could also be recording or submitting information you have provided on a form to preserve the history of your experience. Again, humans would need to multi-task, which means typing, reading and talking all at once — ultimately making them slower.

In essence, AI has the potential to make call centers more accurate and efficient. But it’s important to recognize that they should be used as a side-by-side tool, and not one to completely replace human interaction. The latter could spell disaster.

Modern AI Still Isn’t Perfect

Chances are, you’ve had this next experience before. While on the line, a computer system tells you to enter a number or speak at a prompt to make a selection. You speak, but the computer doesn’t recognize your answer. You do it again, and again and again. You get the picture.

It happens with all technology. Computers and modern AI are not perfect and they have their flaws.

Eighty percent of IT service projects fail — including those that involve implementing AI and big data processes. That’s exactly why the technology should be used to augment the customer experience — not replace true interactions with other humans entirely.

For example, at any time, you should be able to bypass the AI system and get a real customer service representative on the line. Some people just prefer to have that human interaction instead.

A survey from Software Advice revealed that casual engagement is preferred by 49% of Midwestern callers, while 36% of Northeastern callers prefer formality. Truly casual interaction is more of a human trait, so what this tells us is that some people would prefer to talk to another human, while others would have no problem talking to a more formal AI.

Also, there should be a failsafe that allows the AI to identify or recognize when a conversation or interaction isn’t going well. If you have to repeat yourself several times, it gets frustrating and you’re more likely to hang up. The AI should know when it’s best to just transfer you to an actual rep.

But again, therein lies the beauty of AI. It can be programmed and maintained to make these decisions and actions, carrying out things much faster than any human ever could. Over time, the data collected from past conversations would allow the system to become even more advanced and accurate.

In other words, it will improve as time goes on — and that’s important to understand. Artificial Intelligence is poised to replace 16% of American jobs by the end of this decade. It’s getting bigger and better every day.

What Are Some Ways Big Data and AI May Be Used?

There are some specific use-cases for big data and AI in the call center, but it’s important to make the distinction here and now that the possibilities are nearly endless.

  • Customer Insight: Big data systems and AI, in particular, can be used to collect, organize, archive and access information on customers past and present. This means a rep would need access to previous interactions or conversations, support requests, emails and calls, employee notes, quick solutions and more. Analytical systems would allow agents to quickly access this information, relay it back as necessary and take action.
  • Employee Training: Before throwing an agent or rep out to the wolves, they will need live training. Call centers are usually fast-paced, intense and stressful. Employees need to get used to this kind of environment and truly understand how to interact with and handle various customers. AI could help provide the necessary training and allow teams to see where they need to focus their training efforts.
  • Customer Feedback: AI or computer systems can actually be given the necessary information to glean a person’s attitude and emotions. For example, an AI system could have the tools to recognize anger or frustration. In turn, this would allow call centers to collect a different kind of customer feedback.
  • Data Analysis: Data analysis involves putting collected data to use, which means having analysts and experts look it over and figure out ways it can better be utilized. The problem with this is we’re collecting so much data today that analyst teams may not even be able to sort through everything on their own. An AI could effectively help them do this much faster by organizing data sets and recognizing various patterns.

There are many more ways — which we won’t discuss here —this technology could be leveraged in a call center. Point being, don’t look at this small list as comprehensive.