Call Center Modernization with AI

Picture this: A traveler sets off on a camping trip. She decides to extend her RV rental halfway through her trip, so she calls customer service for assistance, but finds herself waiting minutes, then what feels like hours. When she finally does get a hold of somebody, her call is redirected. More waiting follows. Suddenly her new plan doesn’t seem worth the aggravation. Now, imagine the same scenario from the agent’s perspective, dealing with a dissatisfied customer, scrambling for information that takes time to collect. Instances like these are far too common—the debacle ends up being costly for the company, and frustrating for both customer and agent.

Conversational AI solutions for customer service have come a long way, helping organizations meet customer expectations while reducing containment rates, complexity, and costs. It starts with bringing AI into the mix and ends with more cost-efficient operations and more satisfied customers.

So how can conversational AI help fulfill customer expectations in today’s ever-demanding landscape?

When you deploy conversational AI in your call center, you get:

1. Increased customer and agent satisfaction. Think of the example above—long wait times and unanswered questions can only lead to frustrated customers and agents and slower businesses. With leading natural language understanding (NLU) and automation leading to faster resolution, everybody wins.
2. Improved call resolution rates. AI and machine learning enable more self-service answers and actions and help route customers who need live agent support to the right place – continuously analyzing customer interactions to improve response. Agents benefit from this assistance too; empowering them to perform at their best when call traffic is high. Ultimately, improved resolution rates mean better customer experiences and improved brand reputation.
3. Reduced operational costs. With the capabilities of AI-powered virtual agents, you can contain up to 70% of calls without any human interaction and save an estimated USD 5.50 per contained call. This is money saved for your business, and time saved for your customers.

Not all AI platforms are built the same

On the lowest rung of the AI ladder, you have rules-based bots with limited response function. For example, you want to know if your telecom provider offers an unlimited data plan, so you call customer service and are given a set of basic questions following strict if-then scenarios—“…say yes if you want to review service plans; say yes if you want unlimited data.”

Climb up one rung, and there’s level two AI with machine learning and intent detection. You accidentally type “speal to an agenr”— but the virtual assistant understands your intention and responds properly: “I will connect you with an agent who can assist you.”

Why add complexity when you can simplify with AI? 

According to a Gartner® report, in 2031, conversational AI chatbots and virtual assistants will handle 30% of interactions that would have otherwise been handled by a human agent, up from 2% in 2022.¹ To remain among the leaders, modern contact centers will need to keep up with AI innovations. Of course, like Watson, leading businesses are constantly learning, analyzing, and striving to become better.