The Effect of AI Powered Sentiment Analysis on Consumer Complaint Resolution in Ecommerce: A Comparative Study of Human Vs AI Meditation Support

Abstract

Artificial intelligence's (AI) quick development has revolutionized e-commerce and improved customer service effectiveness. With an emphasis on resolution speed, emotional understanding, customer happiness, and cost-efficiency, this study compares the effectiveness of traditional human mediation with AI-powered sentiment analysis in handling customer complaints. Quantitative data from online surveys was analyzed using a mixed-methods approach and statistical tools such as the Mann-Whitney U Test, ANOVA, and Chi-Square Test. This investigation provided valuable insights into the advantages and disadvantages of both approaches. The literature review emphasizes the importance of human mediators, the development of technology for emotion analysis, and theoretical frameworks such as the Emotional Contagion Theory and the Acceptance Model of technologies. The results show that AI is highly effective and scalable, and it drastically cuts down on the amount of time needed to process complaints (Iqbal et al., 2023). The significance of human mediators in compassionate consumer encounters is highlighted by their remarkable ability to manage intricate emotional nuances (Banga and Peddireddy, 2023). This study proposes a hybrid AI-human mediation framework that strikes a compromise between emotional intelligence and technology efficacy in order to optimize complaint settlement processes (Sai Mounika Inavolu, 2024). Furthermore, discussed are ethical issues like data security and AI transparency. By providing practical guidance for integrating AI and human approaches in e-commerce, the study broadens the body of existing literature and opens the door for further investigation into collaborative mediation models. By boosting operational efficiency and preserving client trust, these models support service delivery and client pleasure.