Enhancing Customer Service with AI-powered Chatbots: A Comparative Study across E-commerce Platforms

Authors

  • Dina Kamelia Universitas 17 Agustus 1945 Surabaya
  • Endah Budiarti Universitas 17 Agustus 1945 Surabaya

Keywords:

Customer Service, AI-Powered Chatbots, Comparative Study

Abstract

The rapid development of artificial intelligence (AI) technologies has transformed the landscape of customer service, particularly through the implementation of AI-powered chatbots in e-commerce. This research aims to investigate the effectiveness of chatbot integration in enhancing customer service quality across various e-commerce platforms. Utilizing a comparative case study approach, the study analyzes chatbot performance on three major platforms—Tokopedia, Shopee, and Lazada—based on parameters such as response accuracy, resolution time, customer satisfaction, and user experience. Data were collected through user surveys (n=300), platform interaction logs, and in-depth interviews with customer service managers. The findings reveal that while all platforms benefit from AI chatbot deployment, differences exist in implementation quality, natural language processing (NLP) capabilities, and personalization levels. Shopee's chatbot demonstrates superior speed and contextual understanding, whereas Tokopedia's chatbot excels in multilingual support. Customer satisfaction is significantly influenced by the chatbot’s ability to provide accurate and empathetic responses. The study concludes that AI-powered chatbots, when optimized with robust training data and user-centric design, can significantly improve service efficiency and customer loyalty. This research provides practical insights for e-commerce businesses aiming to enhance digital customer engagement through AI technologies.

Published

2025-05-06

How to Cite

Kamelia, D. ., & Budiarti, E. . (2025). Enhancing Customer Service with AI-powered Chatbots: A Comparative Study across E-commerce Platforms. International Conference of Innovation and Community Engagement, 1(01). Retrieved from https://conference.untag-sby.ac.id/index.php/icoiace/article/view/5403

Issue

Section

Articles