Developing a Business Intelligence for Leaftea Milktea Bar Integrated with DialoGPT-powered Chatbots

Jasmine Villalobos Mangahas; Gerard Nathaniel C. Ngo

Jasmine Villalobos Mangahas School of Graduate Studies, AMA Computer University, Philippines
Gerard Nathaniel C. Ngo School of Graduate Studies, AMA Computer University, Philippines

Abstract

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.

Author Biographies

Jasmine Villalobos Mangahas, School of Graduate Studies, AMA Computer University, Philippines

Jasmine V. Mangahas is a Master of Information Technology candidate at the School of Graduate Studies, AMA Computer University. She earned her Bachelor of Science in Information Technology from New Era University in 2019. Jasmine currently excels as a Senior Production Support Specialist at Collabera, where she leads peer reviews, enhances scripts, and provides hands-on client support, demonstrating her expertise in managing complex technical issues and optimizing production processes.

Gerard Nathaniel C. Ngo, School of Graduate Studies, AMA Computer University, Philippines

Dr. Gerard Nathaniel C. Ngo is a distinguished freelancer developer and a research adviser in the Information Technology Department of the Graduate School at AMA Education System, Philippines. His dual role allows him to apply cutting-edge development skills while guiding research projects, reflecting his commitment to advancing technology and supporting academic growth in the field of Information Technology.