Care-by-Design: Enhancing Customer Experience through Empathetic AI Chatbots
Kadhim Hayawi, Sakib Shahriar · 2024
The reliance on AI-driven customer service has improved efficiency but often lacks the empathy and personalization that foster deeper customer relationships. Traditional customer service models are limited by human agents' capacity to remember past interactions and adapt to individual customer needs in real-time. This paper introduces a Care-by-Design (CbD) framework that embeds empathy, contextual learning, and personalization into the training and deploying large language models (LLMs) for customer service. The proposed framework emphasizes building meaningful customer relationships by addressing emotional and contextual cues in customer interactions. To validate this approach, we conducted a case study comparing a baseline LLM with a CbD-enhanced version fine-tuned on an empathy-focused dataset. Our results demonstrated improved customer satisfaction, query understanding, and emotional responsiveness in the CbD model.