Automated Call Routing Versus Live Support – Improving Caller Experience is as Easy as Using Your Voice
In this omni-channel world, the phone continues to be consumers’ preferred means of contacting enterprises. In healthcare, every patient journey involves making many calls, from scheduling appointments to getting test results to paying bills. Creating frictionless caller navigation has a profoundly positive impact on patient satisfaction with their overall healthcare consumer experience.
One specific painpoint is the traditional IVR (sometimes called a phone tree). This outdated solution forces callers to follow a set script that lacks the natural flow of an everyday conversation. The series of hurtles – for example, “Press 1 for…”, “Listen closely because options have changed” – makes the process frustrating. See this article for more on the issue of outdated contact center technology.
Conversational AI technology offers a modernized, straightforward user interface that transforms IVRs from dissatisfying hurdles to friction-free enablers. These self-service solutions, when set up properly, managed well, and consistently tuned, are the optimal way to improve experiences for healthcare consumers who opt for the phone.
Parlance modern interactive voice response (IVRs) and intelligent virtual assistants (IVAs) open up conversations that are directed by the caller so patients and caregivers effectively navigate self-service by using their own voices. By mimicking the dialogues and call flows of live call center agents and operators, we create natural interactions that connect healthcare consumers with the correct resources easily and quickly. When callers self-serve, support staff face less workload. Voice-enabled speech technology handles routine tasks such as managing appointments, answering FAQs, routing callers to the correct person or department, etc. This gives agents increased time and energy to assist patients and caregivers who need the complex or emotional support that only humans can provide.
By Sheila Kelly
