Enhancing conversational agents for successful operation: A multi-perspective evaluation approach for continuous improvement
Tom Lewandowski, Emir Kučević, Stephan Leible, Mathis Poser, Tilo Böhmann
Abstract
Abstract Contemporary organizations increasingly adopt conversational agents (CAs) as intelligent and natural language-based solutions for providing services and information. CAs offer new forms of personalization, speed, (cost-)effectiveness, and automation. However, despite their hype in research and practice, many organizations still fail to seize CAs’ potential because they lack knowledge of how to evaluate and improve the quality of CAs to sustain them in organizational operations. We aim to fill this knowledge gap by conducting a design science research project in which we aggregate insights from the literature and practice to derive an applicable set of quality criteria for CAs. Our article contributes to CA research and guides practitioners by providing a blueprint to structure the evaluation of CAs and to discover areas for systematic improvement.