Call and contact centers are in a good place when it comes to the transformative power of automation. While technology can do some amazing things, there are many tasks that robots won't be able to handle for quite some time. Enter artificial intelligence (AI) and machine learning, two advancements already making significant headway in contact centers. When the AI contact center is used to make jobs easier for employees, and life easier for customers, it becomes a perfect example of a technology that brings immediate benefit.
AI and Machine Learning: A Short Comparison
Of course, it may be difficult to understand what AI can do for a modernized contact center without a frame of reference. Perhaps surprisingly, the tools modern contact centers use are quite similar to the devices and technologies you depend on in day-to-day life. Do you ask your smartphone what the weather's going to be like tomorrow? When you do, AI fields your question and returns the results. Do you click the "did you mean ..." link when you misspelled something in a search? Machine learning helped the engine figure out what you really meant when you made the typo.
Let's consider how those two technologies work. In the "voice assistant" example, AI runs your question through a collection of real-time and stored data to determine precisely how cold it is in your neighborhood. Meanwhile, the "misspelled search" knows you meant "American Banks" when you typed "American Bonks" because it has noted how others corrected themselves after the same mistake.
AI and machine learning share the same elevator pitch: They parse volumes of data much larger than any single person or team could in the same amount of time, using recurrent trends to grow smarter and better at their jobs while they're at it. For businesses that store troves of data and field hundreds or thousands of concurrent calls, the AI contact center holds huge potential.
In many ways, we're already realizing AI's potential. While the next wave of advancement will undoubtedly bring amazing things to contact centers, the tools companies deploy today show a high degree of utility and sophistication.
Reducing Wait Times in the AI Contact Center
Machine learning and AI are perfect for addressing the mother of all metrics in the average contact center: decreasing hold, wait, and overall call times. These advanced contact centers will accomplish these goals in one of two ways:
- Providing information or assistance related to the customer's call
In this instance, an AI center would anticipate the reason for a call or discover it after a brief conversation. When a customer's internet goes down, an interactive voice response system will recognize that they're in an outage area and tell them when to expect repairs. Or, an online chatbot would determine that a customer needs help resetting their password. In both instances, technologies carry out these very tasks thousands of times a day in countless different contexts — a sign of the versatility and utility they offer.
- Pre-screening to shorten contact with human assets
Let's say a customer needs help getting a refund on a recent purchase. The company's bot, realizing the task is beyond its capacity, can still help shorten the call. It collects the customer's name, determines refund eligibility based on predefined qualifiers (such as the amount of time the customer used the purchase prior to requesting the refund), and then transfers them to the appropriate department. It then shares the data it collected with the representative, so they won't have to start from scratch, further saving the customer time.
The Handoff: When Humans are Needed
There are some tasks — such as the refund request mentioned above — that AI isn't quite ready for yet. This is where a human agent should step in. For contact centers, figuring out when this should occur and imparting their AI with that intuition is paramount.
Thanks to natural language processing and rules-based systems, AI can look for certain words to determine exactly what kind of help is needed. While AI is very good at answering simple questions and carrying out programmed tasks, its ability to resolve problems decreases as complexity increases. For example, the AI that helps you determine the average cost of hotels when traveling is likely powerless to resolve a billing issue.
Since the particulars of service vary between organizations, machine learning tools may also be applied to help the AI contact center improve. By observing a center's interactions, monitoring where calls go when the transfer occurs, and considering the relationship between first-call resolution and total call time, an AI may pick up on some important facts: Where to route a call the next time an interaction with similar language occurs, or which details about the call to include when it directs the caller to a human agent.
In many ways, we're already realizing AI's potential. While the next wave of advancement will undoubtedly bring amazing capabilities to contact centers, the tools companies deploy today show a high degree of utility and sophistication — and give contact center stakeholders everywhere an intriguing new path to improved KPIs.
Ready to make your business run smoother and you keep your customers engaged? Learn how Vonage can help infuse your contact center with powerful, customized AI tools.