Exploring Personality-Aware Interactions in Salesperson Dialogue Agents
It addresses the problem of personalizing dialogue agents for sales interactions with diverse users, offering incremental insights and tools for broader applications.
This study investigated how user personas based on the Myers-Briggs Type Indicator (MBTI) affect the interaction quality and performance of sales-oriented dialogue agents, revealing significant patterns in dynamics, task completion rates, and naturalness.
The integration of dialogue agents into the sales domain requires a deep understanding of how these systems interact with users possessing diverse personas. This study explores the influence of user personas, defined using the Myers-Briggs Type Indicator (MBTI), on the interaction quality and performance of sales-oriented dialogue agents. Through large-scale testing and analysis, we assess the pre-trained agent's effectiveness, adaptability, and personalization capabilities across a wide range of MBTI-defined user types. Our findings reveal significant patterns in interaction dynamics, task completion rates, and dialogue naturalness, underscoring the future potential for dialogue agents to refine their strategies to better align with varying personality traits. This work not only provides actionable insights for building more adaptive and user-centric conversational systems in the sales domain but also contributes broadly to the field by releasing persona-defined user simulators. These simulators, unconstrained by domain, offer valuable tools for future research and demonstrate the potential for scaling personalized dialogue systems across diverse applications.