Developing a Business Intelligence for Leaftea Milktea Bar Integrated with DialoGPT-powered Chatbots - Mangahas, Jasmine Villalobos; Ngo, Gerard Nathaniel C. (International Journal of Computing Sciences Research, 2024)
Purpose – This project aims to digitally transform Leaftea Milktea Bar by developing an advanced AI-driven business intelligence system integrated with Dialogpt-powered chatbots. The goal is to significantly enhance customer engagement, streamline and automate operational processes, and elevate service efficiency to unprecedented levels. The system will be developed using Python, HTML, CSS, JavaScript, and MySQL. Proposed Method – The study uses a hybrid approach, combining quantitative analytics and qualitative evaluations. Customer surveys will measure satisfaction and engagement before and after chatbot implementation, while staff interviews will assess operational impacts. The Dialogpt will be seamlessly integrated into LeafTea’s infrastructure. Advanced statistical tools and thematic analysis will be employed to derive insights. This research aims to provide actionable recommendations for leveraging AI technologies to optimize business operations in the food and beverage industry. Conclusion – Implementing DialoGPT-powered chatbots for business intelligence significantly boosts customer engagement and operational efficiency. By leveraging data analytics and AI-driven interactions, this solution enhances personalization and provides real-time insights, transforming the food and beverage industry. It enables businesses like LeafTea MilkTea Bar to serve customers better and streamline operations, promoting sustainable growth. Initial Results – Initial prototype designs demonstrate some of the system’s functionality. First is the dashboard which shows the summarization of the branches' flow and growth. Second is the chatbot designed to assist users specifically for order taking. Lastly, the inventory shows the available stocks. Also, the orders that have been placed in the chatbot will be automatically deducted from the warehouse inventory. Recommendation – This study recommends adopting the proposed system in merchandising and manufacturing businesses to optimize stock levels, facilitate real-time updates, and ensure scalability to meet evolving business demands.  Practical Implications – The system's benefits extend beyond businesses, encompassing students, prospective researchers, and developers.