A Chatbot Integration in E-Commerce Customer Relationship Management: Insights from the Literature Platforms - Chhayna Cheng (Jurnal Inovasi Bisnis dan Kewirausahaan, 2026)
While the body of literature on AI tools continues to grow, research on chatbot integration to support customer relationship management on e-commerce platforms remains limited. This study aims to address this gap by providing an in-depth analysis of chatbot features within a unified framework. This review employs a literature review approach, inclusion criteria, and document analysis as its review methods. The review synthesizes literature from various sources, primarily scholarly works published between 2020 and 2025, including 75 articles. Drawing on secondary data, it indicates that chatbots trace their origins to ELIZA in the 1960s and categorizes them into three main types: AI-based chatbots, rule-based chatbots, and voice-activated chatbots. Chatbots play a crucial role in digital marketing strategies by managing customer expectations, increasing satisfaction, and fostering long-term relationships with platforms such as Amazon, Shopify, Alibaba, and other e-commerce sites. Additionally, they are effective tools for enhancing CRM in e-commerce, including quick responses, personalized interactions, automated replies, and 24/7 customer support. These functions improve information quality, customer satisfaction, retention, and loyalty across various e-commerce settings. Ultimately, this review proposes directions for future research to further explore chatbot integration in supporting customer relationship management across different industries and environments.