Exploring Personality-Aware Interactions in Salesperson Dialogue Agents
Sijia Cheng, Wen-Yu Chang, Yun-Nung Chen
TL;DR
This work addresses how user personality, as defined by MBTI, influences the effectiveness of sales-oriented dialogue agents. It introduces MBTI-defined persona simulators and a role-playing framework to test a pretrained SalesAgent across diverse, trait-driven user profiles. Key findings show significant differences in task success, interaction length, and dialogue quality across MBTI dimensions, underscoring the value of personality-aware adaptation in conversational sales systems. The study provides actionable guidance for designing personalized dialogue strategies and releases a flexible, domain-agnostic set of persona simulators to enable future cross-domain research.
Abstract
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.