Building Customer Service Virtual Agents Faster and Smarter by Analyzing Human-to-human Interactions with ML
Innovative companies are modernizing their contact centers by adopting AI-powered virtual agents to improve customer satisfaction by providing helpful service 24/7, globally. But for brands building a virtual agent, the critical questions are: What are the best use cases for the virtual agent? What questions do customers ask and how do they phrase them (including follow-ups)? How to ensure virtual agents responds helpfully? What is the optimal time to do a hand-off to a live agent? Particularly for companies with large customer service operations, answering the questions above manually is slow, based on guesswork, and creates gaps that put customer satisfaction at risk. In this session, attendees will learn how machine learning techniques can unlock actionable insights from human-to-human interactions in contact center chat and call logs -- making development much faster, and virtual agents much smarter.
Ofer Ronen is the general manager of Chatbase, a conversational analytics service brought to you by Area 120 (a products incubator operated by Google). Previously, he was CEO of Pulse.io, an app performance monitoring service (acquired by Google), and CEO of ad network Sendori (acquired by IAC). Ofer is a startup mentor at Stanford and an angel investor in Lyft, Palantir, and Klout. He holds an MS in artificial intelligence from Michigan and an MBA from Cornell.