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An Analysis and Research of Growth Factors of Internet Celebrity Boba Milk Tea Stores using Machine Learning and Artificial Intelligence

Authors

Fuyi Xie1 and Zihao Luo2, 1University of California Irvine, USA, 2California State Polytechnic University, USA

Abstract

The boba milk tea industry has emerged as a dynamic and competitive sector within the broader landscape of the food and beverage industry [1]. Characterized by its unique combination of tea, milk, and chewy tapioca pearls, boba milk tea has garnered a dedicated following of enthusiasts. To secure and expand their presence in this market, boba milk tea stores aspire to achieve the status of internet celebrities, attracting a widespread and loyal customer base [2]. This research paper delves into the intricate realm of boba milk tea store growth factors using Machine Learning and Artificial Intelligence [3]. The study is motivated by the recognition that the industry's success depends on understanding and harnessing a diverse array of factors, including customer sentiment, store location attributes, and effective marketing strategies [4]. Our methodology entails data collection and preprocessing from a variety of sources, encompassing customer reviews, sales records, geospatial data, and marketing data [5]. Through rigorous feature engineering and the application of advanced Machine Learning algorithms, including sentiment analysis, geospatial analysis, and personalized marketing models, we aim to uncover the key determinants of boba milk tea store success. The results of our research offer actionable insights for both existing and aspiring boba milk tea store owners. Customer sentiment analysis reveals that customer reviews play a critical role in influencing store performance. Store location attributes, explored through geospatial analysis, indicate that proximity to target demographics, competitors, and high-traffic areas significantly impacts growth [6]. Furthermore, the effective deployment of personalized marketing strategies using Machine Learning techniques has been shown to enhance customer engagement and drive growth. While our research provides valuable insights, it is essential to acknowledge certain limitations, such as data availability and the complexity of Machine Learning models. However, we are confident that this research contributes to the broader understanding of growth factors in the boba milk tea industry and can inspire further studies and practical applications. As businesses in the boba milk tea industry navigate a landscape shaped by evolving consumer preferences, this research underscores the transformative potential of Machine Learning and Artificial Intelligence in achieving and maintaining internet celebrity status. Beyond its immediate application, the study provides a blueprint for leveraging technology, data, and industry expertise to thrive in the competitive landscape of modern retail. This paper invites stakeholders within the boba milk tea industry and the broader retail and food and beverage sectors to embrace the power of data-driven decision-making, facilitating sustainable growth and success in the ever-evolving marketplace.

Keywords

Flutter, Web Scraping, Firebase Storage, Boba Milk tea

Full Text  Volume 13, Number 22