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Contact Centers Offer a Glimpse into the Future of AI—if You Know Where to Look

No matter the industry or customer base, businesses have had to adapt to a sharp rise in digital interactions over the past year. With customer activity and expectations changing rapidly and less predictable than ever, many enterprises have turned to AI to help manage swings in customer demand and crunch large amounts of data and draw actionable insights from it

Nowhere is this more evident than in customer service and contact center teams, where agents are on the front lines of using practical applications for AI every day. Contact centers are quickly becoming both a proving ground for AI-based tools and a way to introduce their benefits to customers through fulfilling interactions. Taking a look at the different use cases of AI in the contact center can offer valuable insights beyond customer service, insights that any organization can use to boost flexibility and efficiency.

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How Contact Centers Became the Perfect Setting For Future of AI

Contact centers have always been treasure troves of data. And during the pandemic, the volume of customer service interactions has climbed to levels 40 percent higher than predicted.

At the same time, pressure has been mounting for faster and more personalized service.  According to a Salesforce survey, 83 percent of customers expect to engage with someone immediately when contacting a company. What’s more, our CX Benchmark for Customer Experience revealed that 96 percent of consumers expect companies to make it easy to switch channels without the need to repeat information about their case.

With resources stretched thin, call volumes up, and teams dealing with more uncertainty than ever before, contact centers looked for tools to help lighten the load. The unprecedented challenges these teams faced—and the need to act quickly—led them to explore AI-based technologies that go well beyond the self-service chatbots that are top of mind. The benefits these technologies bring proved to be both powerful and practical.

Tangible AI capabilities, like natural language processing (NLP), natural language understanding (NLU), and Machine Learning (ML) proved the perfect fit for contact centers’ needs, helping them to draw insights from conversations, sentiment, and customer history. Cloud platforms made gathering these insights possible at scale, providing increased flexibility to manage spikes in demand.

By combining the flexibility and scalability of the cloud with the deep, rapid insights of NLP, NLU, and ML tools to provide more effective self-service and better prepared agents, contact centers have been able to  tackle the spikes and swings of customer inquiries during the pandemic. For customers, that’s meant experiences that feel more personalized. For employees, that’s meant interactions, cases and customer relationships that are easier to manage and learn from. 

A Closer Look at Technologies that Have Proven Effective

So, what specific, practical tactics have contact centers been using to achieve these results? Here’s a breakdown of approaches that have proven the most effective:

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Agent coaching tools delivered in real time

The success of most customer interactions still comes down to agents. Knowing this, contact center decision-makers have been introducing real-time guidance tools to better contextualize and improve interactions. Cutting-edge technology now provides real-time soft-skill coaching tips to agents when the AI detects customer emotions like sentiment or frustration trending in the wrong direction. When combined with AI-powered knowledge bases, service agents can now receive guidance on the next-best behavior, answer, or action for each customer.  This means that customer service experts can improve interactions as they’re happening, rather than after the fact. 

Finding the right algorithms for accurate forecasting

Many contact centers have introduced workforce management tools with AI capabilities to capture and analyze large amounts of historical data and then recommend the most appropriate forecasting algorithm to use for their specific scenarios and business needs. This has resulted in increasingly accurate forecasts that have helped contact centers adapt to rapidly changing business environments. 

Making self-service CX feel more natural

Self-service solutions infused with AI, including virtual agents and conversational IVRs and virtual agents, have become go-to tools during the pandemic. Many customers prefer self-service options, but they want a level of effortlessness that not all chatbots and similar tools provide. Self-service solutions with the right AI capabilities allow users to solve their problems using their own words.

Customer-centric guides for routing interactions

Contact centers have found that AI-powered automatic contact distributors (ACDs) are powerful assets that make it possible to personalize interactions. ACDs can examine customers’ personalities and preferences and match them with the agents they’re most likely to get along with or feel more connected to. This offers a subtle way to achieve that “X factor” present in the best customer interactions. 

Changing Hearts, Minds and Business Priorities

In many ways, the success contact centers have been experiencing is a major proof of concept for AI in the realm of CX. The tactics outlined above are only the beginning. The underlying NLP, NLU, and ML technology powering AI solutions already in use in contact centers can be adapted to develop various other tools, for both broad and industry-specific use. These solutions are also highly iterative and can be trained and improved over time to enable even more natural and efficient experiences. They free up resources not only for IT, but also across the organization, which business leaders can invest in other strategic areas.

All this adds up to a strong business case for practical AI, but NLP, NLU, and ML tools in the contact center have created another major benefit: further normalizing the use of AI for customers in situations that can otherwise feel either banal or stressful. As customers interact with brands using AI effectively, they can see firsthand the benefits those tools can bring, associating them with more personalized, natural, and satisfying experiences.  

Other teams in a variety of industries can learn from contact centers, taking the strategies and technologies that work best for them. With contact centers’ recent success as a roadmap, these forward-looking organizations will magnify AI’s positive impact on the customer experience.

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