Natural Language Front Door

One of the key benefits of an AI-powered virtual agent solution is the natural language processing to understand intent from an open-ended question. This offers a better CX than forcing callers to sit and listen to a long list of menu options or wait on hold for a live agent. A good example of this use case comes from one of the largest hospitality chains in Las Vegas, which had so many places to route calls that it simply was unfit for IVR. This meant that live agents had to route all calls, leaving customers on hold even for simple needs—not a great CX. Virtual agents have helped the company replace live agents answering the phone with an automated prompt that simply asks, “How can I help you today?” Depending on the property, the solution understands the intent for upwards of 10 to 15 different end points. With a 95 percent routing accuracy rate, the hospitality chain has significantly cut hold times and improved the CX.

Front-End Data Gathering and Authentication

Front-end data gathering is the process of automating the drudgery of account authentication, product registration, or other types of information collection so agents don’t have to do it. This step is pivotal in speeding up the call process for a faster CX, as virtual agents often authenticate customers in about half the time it takes live agents to do so.

One good example is in the medical space around patient authentication. HIPAA mandates that companies have to triangulate three of eight different data points in order to verify patient identity, which can account for a large portion of handle time on the phone. For a top regional supplier, this task was taking its live agents three minutes on average. It implemented virtual agents to handle authentication before passing calls to live agents and was able to offload all of that verification time to virtual agents at a fraction of the cost.

Front-end data gathering is also perfect for retail or insurance companies in the form of product registrations. By automating the process of gathering all of the customer demographic information, product information, and other data, call center agents can focus on high value situations that cannot yet be automated.

One of the biggest CX benefits for this use case, especially when bundled with a natural language front door, is that it minimizes “cold transfers,” which happen when a customer is transferred but the new agent who receives the call has no information about who it is or why they got the call. This severely limits how personalized the agent can make the greeting and conversation, forces customers to repeat information over and over, and ultimately frustrates everyone involved. By capturing this data in the automation—even if it is just a partial capture—and providing it to live agents as the customer is transferred, the customer is given the most streamlined and high-quality CX.

Routine Inbound Conversations

Scheduling an appointment or checking on the status of an order are examples of routine inbound conversations that can be handled by virtual agents. The classic example is in pizza ordering, as the world’s largest pizza chain transfers calls to virtual agents to handle certain orders. Over the cloud, the virtual agent is able to access customer data via caller ID and looks to see if the customer ordered within the last two months. If yes, the customer gets a personalized experience given the high probability that he or she wants to place the same order as last time.

Conversational Outbound

This is an untapped opportunity for many large companies because it often requires a lot of human effort. One of the top truck rental agencies used live agents for outbound reservation confirmations, which helped it with fleet management and reduced no-shows. But using live agents was a huge investment of time and money. By using cloud-based automation that is connected to their customer data, they can now “outsource” these calls and text messages to AI-powered virtual agents. While robocalls are another automation option, the difference between virtual agents and robocalls (or texts) is massive, as the virtual agent can handle multi-turn conversations like rescheduling the pickup, cancellations, location changes, and more. It also creates an even stronger CX.

Conclusion

Artificial Intelligence is no longer a fearsome black box that will render call center jobs obsolete, but rather the ‘new normal’ for how call centers must operate. In fact, the customer service organizations that will succeed over the next five to ten years are likely to be those that embrace AI-powered virtual agents and use them to enrich the Customer Experience far beyond what had ever been possible without them.