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Making AI Work in the Contact Center

Making AI Work in the Contact Center

/ Technology, Artificial Intelligence
Making AI Work in the Contact Center

When deployed to address targeted opportunities, AI adds significant value to CX outcomes and operational performance.

In the late 2000s, right around when videosharing platforms were really coming into their own, there was a curious trend among marketing executives. “Viral videos” captured the zeitgeist, and every brand decided they needed to have one—even if they didn’t fully understand what made a clip “go viral” or how to be strategic with its use. They simply needed to have one and the rest would figure itself out. The same trend is often true for innovative and game-changing technology solutions. Take artificial intelligence (AI), for example. PwC estimates that AI will contribute $15.7 trillion to the global economy by 2030, and every industry—including contact centers—is rushing to adopt their own AI strategy.

But investing in AI without an outcome-oriented plan in place can have significant consequences for your business. Today in the contact center, AI is most commonly leveraged in the form of chatbots to ease inbound volume of simple inquires, so agents can focus on more complex, higher value customer engagements. For customers, however, AI is not yet living up to its (expected) potential. The second annual NICE inContact Customer Experience (CX) Transformation Benchmark report found that a majority (79%) of consumers said that chatbots and virtual assistants need to get smarter before they are willing to use them regularly.

That said, AI innovations, when deployed to address targeted opportunities, have the potential to add significant value to customer experience outcomes and contact center operational performance. Here are the top ways AI can impact and improve your contact center:

Matching the Right Agent to the Right Customer

Contact center leaders are beginning to recognize that chatbots are just the tip of the AI iceberg. In fact, according to Forrester, 64% of companies plan to increase their AI investment in the contact center in the next 12 months (Forrester Consulting, “Building An Artificial Intelligence Infused Contact Center”, a commissioned study conducted by Forrester Consulting on behalf of NICE, March 2019).

One of the biggest positive impacts AI can have on the center is through intelligent routing. With Predictive Behavioral Routing, AI can be used to quickly route customers to the best agent match based on customer profile and business goal. Each previous interaction informs a unique customer profile that accounts for communication style, preferences, personality and behavior characteristics. Predictive Behavioral Routing is optimized to specific businesses goals and metrics. Specific measures such as Average Handle Time, Customer Effort, Customer Satisfaction, Net Promoter Score®, First Contact Resolution, Sales Effectiveness, and Customer Retention can all be accounted for when determining where a customer should be routed to ensure the desired outcome, and ensure that inquiries are properly prioritized. For example, by analyzing incoming emails by subject matter, intelligent routing can reduce the response times of high-impact requests by directing to the appropriate agent.

Enhancing Agent Performance

Despite what some might fear, AI is not here to replace agents—it’s here to make them more effective and focus on them on the most interesting and complex issues. Our study found that 90% of consumers prefer to talk with a live agent rather than a chatbot or virtual assistant. During interactions between agents and customers, AI can serve as a powerful co-pilot, offering suggested responses, prompts and contextual information.

On a larger scale, by analyzing a massive volume of conversations, AI is able to analyze customer behaviors and trends. For example, are agents handling numerous, repetitive issues on a specific product or update? Having this information quickly enables proactive response to alleviate customer frustration and help brands get to the root cause of issues impacting customers.

There’s also the training element. The same natural language processing that helps customers get to the right agent can be leveraged for quality monitoring and coaching. Gleaning agent performance insights allows contact center supervisors and leaders to deliver timely, objective and personalized feedback, while automating notoriously complex scheduling and staff forecasting functions. Customers benefit by having a more informed agent, and agents benefit by having the right insight to improve their skills and effectiveness

Focusing Chatbots For Success

As mentioned, many first-generation chatbots are underperforming relative to consumer expectations—for now. This is often because bots, as they exist today, are being asked to do too much at too broad a scope. In fact, chatbots excel when their function is narrow. The issue is due to the fact that they cannot intuit complex or implied information from customers the way people can. They may need to ask numerous questions and are a bit more roundabout to get to the same place, which is frustrating to customers.

Think about chatbots like you would IVR. If you add 25 new options to an IVR menu, it confuses the customer; if you ask AI to do 25 different things, it will confuse the bot. But, IVR that is focused and optimized on quick-hit structured responses delivers speedy, convenient customer experiences—same thing with a bot. In reality, chatbots need to be able to rapidly source information and elevate conversations across channels and to human agents when necessary.

A Bright Future Ahead

Successful artificial intelligence in the contact center is not going to be a single intelligent algorithm that does it all. Rather, AI will be a large collection of highly optimized intelligent applications that each do their part across the spectrum by pulling from the same pool of data. That’s why it’s important to begin with an open cloud customer experience platform that’s agile and allows for seamless integration of customizable AI applications, developed just for your business needs. Building a successful AI strategy doesn’t start with going out and “buying AI,” it requires a purposeful focus, end-to-end in the contact center, to truly live up to the hype.



Chris Bauserman

Chris Bauserman

Chris Bauserman is Vice President at NICE CXone. He has successfully driven technology strategy and go-to-market (GTM) growth initiatives for software startups and large enterprises over the past 20 years, focusing on solutions that help organizations improve the customer experience.
Twitter: @chrismikeb

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