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Here's Why Every Contact Center Should Be Investing In Artificial Intelligence

It's a customer experience fact: everyone who calls customer service wants to talk to a human being. They mash 0 to avoid self-service. They tweet at the company when they're on hold. They try to contact someone, anyone who can answer their question.

And that just causes more problems because most of the problems people call customer service about can be solved by self-service.

According to a 2013 study of a financial contact center, 70 percent of calls could easily be taken care of online or by using a contact center's self-service options: checking balances, for example, or asking about bank branch hours. Twenty percent of the calls were related to card maintenance. Just 10 percent of the calls were nuanced and complex enough to warrant attention from a human representative.

But everyone wants to talk to a human, right?

Those 70 percent of mundane calls take their toll. More calls mean that at certain times of day — lunch hour for example — staffing managers must make sure there are enough representatives ready and waiting for high call volume spikes.

More calls also means that more customers are sitting on hold during their lunch hour, angrily posting to social media about hold times (which doesn't look great for a company.)


Why are these customers upset? Because they just want to talk to a human.

According to the 2017 Microsoft State of Global Customer Service report, more than a third of U.S. respondents said that automated telephone systems and an inability to reach a live human is the most frustrating aspect of customer experience. Even people who work in customer service and understand the need for self-service mash 0 to get to a representative. In a talk about BI in call centers, Dileep Srinivasan, then Venture Leader at Cognizant, admitted that he does it too.

This seems like a Catch-22 for businesses, who can provide easy access to FAQs and self-service options that would answer 70 percent of simple inquiries...if customers would only use them. But they call in and press 0, because they want to speak to a human.

And that has its own problems, because in many cases, the staff at contact centers are getting angry callers with mundane issues who are eating up their time by complaining about being on hold, and that influences the agents and on the centers' bottom lines. The customer service industry struggles with agent turnover and the stress of dealing with lots of angry callers can impact the way agents answer the phone; they can be perceived as rude, for example.

So, yes, callers want to talk to a human. But what if the answer to the problem isn't human at all?

Enter the Robots

Artificial intelligence (AI) has been entering customer experience slowly. Chatbots are probably the most visible AI in customer service; they appear in the corner of the screen on organizations' sites to direct customers to the page that will best answer their questions — or to be ignored.

However, AI can be used several ways to support call centers and improve customer experience

  • to predict problems before they happen
  • to make suggestions to agents as they are speaking to customers
  • as potential agents themselves
  • as behind-the-scenes support

Let's look at each of those use-cases in more depth.

AI as a Crystal Ball

Calling AI a "crystal ball" is perhaps unfair, the predictions made by AI aren't magic. They're the product of algorithms that take in an immense amount of raw data from, for example, the phone systems, the CRM, product listings and customers' online behavior, and use that information to make targeted predictions that will help a contact center better respond to customer needs.

Think of the staffing manager at a contact center. That person must predict call volume to ensure that there are enough agents on duty at the right time, so that there isn't a skeleton staff trying to juggle a high volume of calls, or too many agents being paid to sit idle during low call volume times.

invest-in-aiPhoto by Diana Varisova [CC BY-SA3.0] via Wikimedia Commons

To do this, the staffing manager uses historical data about call volume, often using BI to find out the times, days and months call volume has been highest, weighing that data against flukes — times when call volume might have spiked due to a company mistake, for example — and then scheduling workers based on that data.

Even with BI support, that can be a tricky job. Staff may not want to work at certain times, or the BI application may only pull data from one system.

An AI integration can pull data from several systems, predict the call volume down to the minute, and assign the correct number of agents to work and at what time. As a bonus, AI is also immune to wheedling from workers who want different hours.

AI can also predict the sorts of problems customers will call about. By using the information in a contact center's CRM — what a client bought, when, and why — AI can tell if that product is likely to need service. If the product has sensors, AI may be able to sense a problem before the customer even detects it. In both cases, customer service can then reach out to the customer with a solution before the customer even picks up the phone to call in.

So, it's not magic, but to the customer who can't start a lawn mower because there's not enough gas in it, a helpful text from customer service saying, "we noticed you're trying to start your mower. Put some gas in and see if that helps" might feel like magic, for example.

AI as a Coach

Contact center agents often receive thorough training when they're onboarded, but even the best trained representative can start to slip when they’ve been answering calls for a few hours during a high-volume time.

They might, for example, forget they’re on the phone with a customer when looking up information in the CRM and go silent, causing the already-frustrated caller to wonder if the agent is there. Or — if the organization is trying to move their contact center towards being a profit center — an agent might forget to mention a product that customer might be interested in, based on what they've bought before.

AI can listen in on those phone calls and make suggestions while the call is in progress. IBM's Watson is already being used for this purpose. According to an article in Fortune, a bank in Brazil with 50 different products uses Watson to advise contact center agents about the bank's offerings, so bank representatives aren't tasked with remembering the details of 50 financial products.

Humana, a health insurance company, is using a different approach when it comes to AI and customer experience: they use Cogito, an AI tool that analyzes conversations to monitor phone calls. Cogito listens to representatives and offers suggestions while the conversations are happening in real time. For example, the agent who is quiet for too long while looking up information might be prompted by the AI to check in with the customer and let them know they are still with them on the line to avoid dead silence.

Humana's call center pilot in 2016 yielded promising results: customers whose calls were answered by agents using AI were 28 percent more likely to recommend Humana and problem resolution improved by 6 percent. Additionally, average call and wait times decreased. Turns out, when customers feel they're being taken care of, they ask fewer follow up questions, complain less and likely won’t ask to speak with a manager or escalate their situation.

AI as a Customer Service Representative of the Future

AI has been making some calls lately.

Google demoed its computer-generated voice assistant, Duplex, at the company's I/O conference in May. That demo featured Duplex making dinner reservations and haircuts (complete with crutch words such as "uhs" and "ums" that punctuate an actual human sentence), but Duplex can take calls as well as make them.

Earlier this month, The Information reported that a major, unidentified insurance company was looking into using Duplex in its contact centers. The company was considering using AI to handle the 70 percent of repetitive, easily answered calls, while the 10 percent of calls that require a human are sent to live agents. That project has slowed down because of ethical worries — critics are asking if callers should have the right to know that they are speaking to a computer.

AI as Back Office Support

That sort of ethics concern may quash that project, because callers want to speak to humans. But even if robots don't become representatives, they can still help agents be better at their jobs and can do a good job of routing that 10 percent of complex queries to a live human while handling simpler concerns.

AI can, for example, listen to a customer's complaints, use a combination of language recognition and CRM information to determine how urgent the matter is and if the query requires a live agent, and route the caller to the appropriate resource.

This sort of solution helps callers without the callers even knowing an AI method was involved and cuts down on transfers from the IVR to the contact center.

What Sort of AI Will Work for You?

AI can help call centers improve their practices and cut down on costs, but the technology is so new, choosing an AI approach may seem intimidating.

In some cases, it may mean a custom integration that involves Business Process Management (BPM) tool, or an existing system. To understand what AI will work best for you, you should always work with a company who puts your needs ahead of selling a specific product or service.

Omni, for example, is a K2 partner — which helps us design BPM solutions for our clients with contact centers — but we are also platform agnostic, meaning we work with you to solve your challenges using the tools your solution requires and the platforms you've already invested in.

Our first step is to develop a thorough understanding of our clients' businesses and challenges. Only when our consultants understand your needs do we introduce the technologies that help you.

AI is Here

The robots aren't coming — they're here. If you don't work with them in some capacity, you could get left behind. But if you do, no matter the use case that applies to you, you're likely to improve customer experience, reduce call volume, and make your representatives better at their jobs.

Ready to bring AI into your contact center? Work with us.


Twitter Image credit: https://twitter.com/CLinscott/status/1016495215023218688

Juan Godina

About Author Juan Godina

Juan is a former customer solutions manager with Omni. He joined the company to promote the firm’s advanced technical capabilities. His knowledge of the complexities and regulations that are involved in data privacy and security requirements, customer sensitivity, privacy laws including HIPAA & HIPAA HiTech, is what gave him valuable insight into how emerging technologies, such as blockchain can be applied. He holds a bachelor's degree in Business Administration and Finance from the University of Phoenix and volunteers in several organizations around the state.


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