Fertitta Entertainment
Several years ago, struggling to handle call volumes due to understaffing resulting from COVID, we were faced with a few options. Add an IVR and try to divert callers, making it harder to get to an agent. Or, add a customer-led conversational AI voice assistant that would answer the call immediately and help callers resolve their concerns and make reservations.
Over the past few years, I have made these observations in comparing the roadblocks of a traditional IVR to our new conversational assistant and how it became a pathway to help our callers and drive more revenue while reducing costs.
In the ever-evolving landscape of customer service, the way companies interact with their customers can make or break their reputation. Traditional Interactive Voice Response (IVR) systems have long been criticized for their tendency to act as roadblocks, frustrating callers with confusing menus and limited options. However, the emergence of Conversational AI assistants presents a paradigm shift, transforming customer interactions into seamless pathways towards issue resolution.
The IVR Roadblock:
IVR systems have been a staple of customer service for decades, designed to automate call routing and reduce the burden on human agents. However, they often fall short in delivering satisfactory customer experience. Callers are greeted with a series of robotic prompts, forcing them to navigate through a maze of menu options, often leading to dead ends or irrelevant departments. Frustration mounts as customers struggle to articulate their issue within the confines of pre-determined choices, leading to longer call times and decreased satisfaction.
The Conversational AI Pathway:
Conversational AI assistants represent a departure from the rigid structure of IVR systems, offering a more intuitive and natural way for customers to interact with businesses. Powered by advanced natural language processing (NLP) and machine learning algorithms, these virtual assistants can understand and respond to a wide range of inquiries, regardless of how they are phrased. By leveraging contextual understanding and personalized data, Conversational AI assistants guide callers along a pathway tailored to their needs, swiftly addressing their concerns and providing relevant solutions.
Key Differences:
- Flexibility: IVR systems offer limited flexibility, constraining callers within predefined menu options. Conversational AI assistants, on the other hand, adapt to the unique needs and preferences of each caller, offering a more dynamic and personalized experience.
- Engagement: IVR systems often leave callers feeling disconnected and frustrated due to their impersonal nature. Conversational AI assistants engage callers in natural, human-like conversations, fostering a sense of empathy and understanding.
- Resolution Time: IVR systems can prolong resolution times as callers struggle to navigate through menus or wait for human assistance. Conversational AI assistants streamline the process by quickly identifying and addressing customer inquiries, leading to faster issue resolution and higher satisfaction rates.
The Path Forward:
As businesses strive to enhance their customer service offerings, transitioning from IVR roadblocks to Conversational AI pathways represents a significant opportunity for improvement. By embracing the capabilities of Conversational AI technology, companies can elevate customer experience, drive operational efficiency, and build stronger relationships with their clientele. As customer expectations continue to evolve, the path forward is clear: it’s time to break down barriers and pave the way for seamless, conversational interactions.
With over 35 years of experience, Brian Jeppesen is a seasoned leader in contact center operations and two-time Frost & Sullivan award winner. He specializes in deploying Conversational AI to enhance customer experience and reduce costs, has led teams of up to 2,500 agents across global brands including Landry’s and Golden Nugget and serves on the Board of Directors for the Contact Center AI Association.
