Webinars
Designing Better AI Chatbots: A Rapid Prototyping Playbook for Marketers
As generative AI chatbots scale across customer service and marketing, teams must make frequent design decisions about tone, escalation, and behavior, often under tight timelines and with limited ability to test changes safely in live environments.
This session introduces a rapid prototyping approach that helps organizations evaluate and improve customer-facing chatbots before changes go live. Using Home Depot’s Magic Apron chatbot as an example, we show why common shortcuts such as reviewing transcripts or hypothetical scenarios can be misleading, and how guided, live research conversations provide clearer direction.
You will learn how to:
- Make confident chatbot design decisions faster, without relying solely on slow or risky in-market experiments
- Avoid misleading signals
- Operationalize rapid prototyping to determine what to change, what to scale, and when deeper testing is needed
speaker
Aaron M. Garvey researches consumer behavior as an Associate Professor of Marketing in the Haslam College of Business at the University of Tennessee. Dr. Garvey's research into human-AI interactions, branded product consumption, and consumer decision-making has been published in academic journals including the Journal of Marketing, the Journal of Consumer Research, the Journal of Marketing Research, and the Journal of the Academy of Marketing Science. His research has been featured in numerous popular press outlets, including NPR Morning Edition, Harvard Business Review, The Today Show, The Wall Street Journal, and The Economist. Dr. Garvey serves as Associate Editor for the Journal of Marketing, the Journal of Marketing Research, and the Journal of Business Research, and on the Editorial Review Boards for the Journal of Consumer Research and Journal of Public Policy & Marketing. Prior to entering academia, Dr. Garvey spent six years in product marketing and management in the Fortune 500. His current research examines human interactions with generative AI agents, including new methodologies enabled through incorporating generative AI agents into the research process.