Exploring emotional engagement in AI-driven retail chatbots: balancing emotional value and communication efficiency to enhance customer satisfaction

This paper investigates the interplay between emotional engagement and communication efficiency in AI-powered chatbots within the retail sector. Using a 2×2 factorial design, the research explores variations in emotional engagement (high vs. low) and communication efficiency (high vs. low), measuring their effects on customer satisfaction, trust, and repeat purchase intention. Insights are drawn from cross-cultural comparisons between China and the UK, highlighting the role of culturally adaptive chatbot strategies. Key findings indicate that chatbots employing empathetic language and rapid responses can improve customer retention rates by up to 35%. The paper also addresses scalability challenges for small and medium enterprises (SMEs) and proposes cost-effective solutions to leverage emotional AI. Ethical considerations, including data privacy and the authenticity of simulated <br/>empathy, are critically discussed. This study contributes actionable insights for retailers and academics seeking to optimize customer engagement via AI-driven technologies.