Conversational Commerce and Relationship Quality: Examining Trust, Social Presence, Personalization, and Response Competence in Digital Customer Interactions

Maya Lestari

Conversational Commerce and Relationship Quality: Examining Trust, Social Presence, Personalization, and Response Competence in Digital Customer Interactions

Author(s)	Dr. Maya Lestari
Country	United States
Abstract	Conversational commerce is transforming digital customer interactions by allowing consumers to search for products, request recommendations, resolve service questions, compare alternatives, and initiate purchases through chat-based interfaces. Although conversational agents can improve accessibility and response speed, their long-term commercial value may depend less on transactional efficiency than on their ability to support high-quality customer relationships. This study develops a simulation-based framework examining the relationship between conversational commerce and customer relationship quality through response competence, personalization, social presence, trust, satisfaction, and perceived conversational intrusiveness. A synthetic dataset representing 400 hypothetical digital consumers was constructed across four conversational-commerce conditions: low conversational quality, moderate conversational quality, high conversational quality, and high conversational quality combined with responsible personalization. Mean simulated relationship-quality scores increased from 3.12 in the low-quality condition to 4.18 under moderate quality, 5.21 under high quality, and 5.87 when high conversational quality was combined with personalization. A multivariable model identified trust as the strongest positive predictor of relationship quality, followed by satisfaction, perceived response competence, social presence, and personalization. Perceived conversational intrusiveness showed a negative association. The findings suggest that conversational commerce creates stronger relational value when automated interactions are accurate, contextually relevant, responsive, transparent, and sufficiently human-centered without misrepresenting machine communication as human communication. The paper contributes an integrated relationship-quality perspective to conversational-commerce research and argues that organizations should evaluate conversational systems not only through conversion and response-time indicators but also through trust, satisfaction, continuity intention, perceived competence, and relational confidence. Because all observations are simulated, the numerical findings are intended as theoretically grounded methodological illustrations requiring subsequent validation through real consumer experiments, transactional data, or longitudinal customer studies.
Keywords	conversational commerce; relationship quality; chatbots; customer trust; personalization; social presence; customer satisfaction; digital commerce
Field	Engineering
Published In	Volume 6, Issue 1, January-February 2025
Published On	2025-02-20

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American Journal of Advanced Multidisciplinary Innovation and Research

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Conversational Commerce and Relationship Quality: Examining Trust, Social Presence, Personalization, and Response Competence in Digital Customer Interactions

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