What if callers could simply say what they want and get relevant answers to their questions instantly? Instead of pressing a series of numbers hoping to get routed to the right department, what if callers could state in their own words the problems they are having, or the tasks they want to complete? When voice AI becomes more of the standard, organizations may finally start to realize the promise of automated call centers.
Currently, in industries like banking and financial services, callers must address one request at a time and often with different agents in different departments. In the future, advanced technologies such as Speech-to-Meaning™ will allow customers to ask once for everything they need. Requests like, “I’d like to reset my password and transfer funds” could be understood and resolved in one phone call.
Just as companies don’t have the resources to train all call center agents to handle every call, it doesn’t make sense to design an individual domain for every type of request in each call center. As use cases are documented through the system’s data collection capabilities, the knowledge graphs for these voice assistants will grow over time allowing one AI assistant to handle multiple common requests so human agents can focus on the more complex requests.
The evolution of the call center has involved the amalgamation of technologies and human interaction. However, the solutions currently available aren’t solving the growing complexities of running a contact center. While the human element will always be part of these customer service operations, the challenges of training and monitoring individual interactions continues to be a drain on the system. Plus, attrition still continues to be a huge problem.
In an effort to formalize and standardize conversations, contact centers currently provide scripts for agents to follow. These scripts are limited in scope as individual requests may not fall strictly within the guidelines suggested. Often, callers are transferred from one call center team to another in an effort to provide solutions to complex issues. In these cases, the voice assistant can become a silent advisor to the human agent, replacing static call scripts and offering unique solutions based on a large database of information.
Instead of putting the caller on hold, or waiting for a supervisor to join the call, customer service agents will have the benefit of data collected over time from calls to all the contact centers in the company. Quick answers and suggestions for next steps will be at the agent’s fingertips—empowering them to handle more calls quickly and efficiently and creating brand affinity through customer satisfaction.
Reducing the burden of common queries and routine transactions
People in urgent need of support—such as an insurance customer involved in a car accident or a banking customer reporting credit card fraud—are often put on hold. A voice assistant can step in to solve call log jams especially with addressing the most commonly asked questions.
First, by categorizing the call, urgent calls can be prioritized and routed immediately to an available agent. In addition, the voice assistant can respond to the routine “noise calls” and make suggestions for other sources of information. Voice assistants can take the load off the agent by helping address common issues that require simple responses like sending password reset emails and pricing information. In addition, routine appointments, scheduling, and other simple tasks can be handled directly by the voice assistant.
Since a large majority of calls to contact centers are for routine matters, the voice assistant can also efficiently assist customers with requests like account statements, billing questions, automated payments etc. without the frustrations of choosing from complicated menu options, and long wait times.
Modernizing call center training and record keeping
“This call may be monitored or recorded for training purposes.” This effort requires both time and resources. Meaning that in addition to paying the contact center agent, there is a supervisor who is listening in to the call or reviewing transcripts after the fact to determine how well the call went and if the problem was solved for the customer. In addition, during each call and at the end, call center agents are filling out forms and recording information associated with the call in call logs—requiring more manual labor and input.
The machine learning capabilities of voice tech will improve call center responses over time and help companies recognize patterns in requests and problems with accounts. Calls will be automatically transcribed accurately and in real time, reducing the load on contact center agents. Constant training to review calls and improve responses will no longer be necessary as the voice AI tech will provide support to the agents during the course of each call.
