In this episode of the Deep Learning with Poly AI podcast, host Damien Smith interviews Stephen Fine, a Senior Business Value Analyst, on the evolution of measuring success in contact centers. They discuss the transition from traditional operational efficiency metrics like average handle time to a more customer-centric approach facilitated by conversational AI and automation.

The conversation covers the importance of first contact resolution, the role of sentiment analysis in measuring customer satisfaction (CSAT), and the potential of automation to handle repetitive tasks, thereby allowing agents to focus on more complex issues. They emphasize a holistic view that combines operational efficiencies with a greater focus on the quality of customer interactions, suggesting a future where contact center success is more aligned with overall customer experience than reducing resources.