3 Real-World Examples Of Contact Center AI
The customer experience can make or break your business. A positive experience will go a long way toward keeping customers satisfied and loyal. A poor experience, however, can damage your brand beyond repair. (Unsatisfied customers will share their opinions with anyone who will listen!)
When a customer reaches out to your organization they expect to be treated as a priority, not a hassle. They are looking to you for answers, not “the runaround.” Customers want to be heard … and understood. This requires not only gathering plenty of good data but being able to make sense of all that data in a way that lets you quickly and accurately act upon it. That’s the power of AI. A true conversational AI application can provide personalized interactions that give the customer the answers they need in just a few questions—while improving CSAT, increasing revenue, and lowering your service costs.
Creating Smarter Customer Contact Experiences
At its core, artificial intelligence is about understanding data. In the early days of IVR, this was done the hard way by writing business rules that tried to cover the content. The problem, of course, was that no set of rules can anticipate all the words a customer might use when they need help. The customer was interacting with the voice on the other end of the line, but they weren’t having a conversation.
Today’s approach combines natural language processing rules with the pattern recognition of machine learning. This creates a powerful toolset that helps to deliver smarter, more satisfying customer experiences in the contact center.
An AI interface can interpret multiple pieces of data from a caller’s phrase or sentence, whether spoken or written. The result is faster, easier, more accurate self-service—in short, more satisfied customers.
With natural language, you don’t have to fit a certain menu structure. You aren’t limited by the number of options you can have on a menu. You can simply ask the caller how you can help them.
“Rather than forcing a customer to understand my system, what if I could build a system that understands my caller’s needs? — Kevin Maas, Director, Strategic Consulting Waterfield Technologies
Three Examples Of Real-World Results
AI technology helps create smarter customer contact experiences. Here are three examples of how our clients transformed their contact centers resulting in higher containment rates, improved accuracy, and better experiences for their callers.
Online retailer doubles containment rate:
An online retailer was struggling with high seasonal call volumes during the busy back-to-school season and the holidays. Their touchtone-based IVR and agents couldn’t keep up with the overwhelming call volume and the existing solution only had about a 15% containment rate.
The Waterfield team implemented a modernized, voice-first natural language application in English and Spanish. The platform was complete and online in about five and a half months – a surprisingly short time compared to the up-to-two years traditionally needed for a natural language voice project.
As a result, the retailer’s call containment immediately doubled. They also reported a 51% containment rate for chat interactions, which they hadn’t been able to offer with their old system. Peak stability, self-service, and CSAT rates all went up, while agent transfers and operational costs went down.
AI improves recognition, accuracy, containment stats over time:
We helped a national emergency roadside assistance provider update their legacy speech application to a new system using AI. The AI made dramatic improvements in recognition immediately, with the metrics settling around the new, higher level.
For the client, the most surprising results came a few months after the upgrade. Accuracy and containment scores improved, despite no additional changes. The AI was self-teaching—able to learn as it acquired more examples of customer speech.
AI lightens the load for a local government:
Municipalities are also benefiting from the power of AI. Waterfield Technologies recently deployed an AI system to transform a city government’s 311 call service. A traditional IVR structure would have handled only a small fraction of the wide range of callers’ inquiries, however, the new AI platform has an open-ended greeting with the ability to handle spoken-word requests, recognizing over 80 issue types. The AI is then able to create the report ticket directly in the system without involving any employees, freeing the burden on the staff.
The Parks and Recreation Department was the first to roll out the system and the Waterfield team is currently expanding the platform to the city’s other departments.