ResearchChatAI: An Open Source, Easy to Use Platform for Customizable Conversational AI Experiments
(A2026-134049)

AUTHORS

Marc Becker, Maastricht University; David de Jong, Vrije Universiteit Amsterdam; Roman Briker, Maastricht University; Jonas Heller, Maastricht University; Dominik Mahr, Maastricht University; Dhruv Grewal, Babson College

ABSTRACT

Conversational AI agents, systems that hold intelligent conversations with humans, are reshaping how organizations engage customers, from sales to service. Marketing scholars are beginning to study how these agents influence customer journeys and brand outcomes, yet most research relies on scenario-based methods with limited ecological validity. New no-code platforms let researchers design and deploy agents without technical skills, enabling studies using real-time interactions. These agents can represent customers, employees, or others; display traits and behaviors; and be used in lab, field, and experimental designs. Across three studies (N = 789), we show that interacting with such agents shapes perceptions, attitudes, and incentivized behavior. We introduce ResearchChatAI, an open-source tool, to illustrate study design and deployment, discuss methodological trade-offs, and show how such tools support more valid, realistic, and scalable marketing research on and with AI.