Machine Learning in FMCG - How Social Listening, Big Data, and AI Apply in the Business Decision Process

Yau, P. C. (2022) Machine Learning in FMCG - How Social Listening, Big Data, and AI Apply in the Business Decision Process. In: 7th International Conference on Human Interaction and Emerging Technologies: Artificial Intelligence and Future Applications (IHIET-AI 2022), 21-23 Apr 2022, ISBN 9781792389894 (doi: 10.54941/ahfe100921)

Abstract

Without a machine, human beings cannot process the massive data volume produced by us nowadays for business analysis purposes. Being part of the critical decision-making process in the commercial sector, the usage and role of Big Data, especially those collected from social listening are getting important: how a company listen to the true voices from a group of genuine customers and avoid those misleading, fake comments generated by the robot, to enhance the efficiency on measuring competitor's performance towards their marketing return compared to the investment (MROI), is critical and more challenging. In this paper, we will discuss various analytical methodologies from the angles of business and technological viewpoint: what decision-makers want from social media, what kind of information are they looking into, how visualisation provides instant insights and what kind of system design provides enough interaction to the decision-maker. We will investigate the real-world challenges and difficulties: how the data inconsistency affects the computational analysis, what kind of obstacles was facing in the existing product design in the market. Finally, we will conclude the used machine learning techniques that can address the mentioned business problems, including the successful rate, accuracy and various efficiency level in the studied samples.

• Item Type: Conference Proceedings
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Yau, Dr Peter C Y
• Authors: Yau, P. C.
• College/School: College of Science and Engineering > School of Computing Science
• Journal Name: AHFE International
• ISSN: 2771-0718
• ISBN: 9781792389894