The difficulties imposed by the pandemic have led to a serious rethinking in the traditionally call center-based customer service economy.
Traditional IVR (Interactive Voice Response) systems in contact centers become expensive and outdated to maintain as they are not compatible with newer system migrations, such as a shift to cloud.
Operational costs can go up, while archaic IVR struggles to keep up and wait times become longer, dragging customer satisfaction levels down at the same time.
But a cloud-based, conversational AI platform today is capable of leveraging advances in AI, machine learning, voice recognition, and natural language processing (NLP) to more accurately comprehend the customer’s queries and to respond in a more natural way.
The AI and machine learning capabilities will even learn from earlier errors, improving its responses for the next interaction.
Conversational service automation, or CSA, is a combination of overlapping categories such as data analytics, conversational analytics, IVR systems, voice bots, security, robotic process automation (RPA) and customer feedback history, working together in real-time.
This solution optimizes and drives both automated human to machine interactions as well as direct conversations between contact center agents and customers.
Additionally, cheap and reliable high-speed networks have made it possible to offload processing to the cloud, enabling rapid “understanding” of peoples’ intents.