Social Media Analytic and Big Data Technology to Support Business Decision Making by an E-Commerce Company in Sustainability Fashion: A Content Analysis Study Lucya Erlinda Sonia
Faculty of Business and Economics Universitas Surabaya
Abstract
Objectives: This study aims to analyse how the use of big data from social media through content analysis methods can improve the performance of Echo Thread, an e-commerce company engaged in sustainability fashion.
Methods: The research method used in this study is a qualitative content analysis of text data and social media analysis from Echo Thread, as well as website related to the company^s activities in the period 2022 - 2024. The data collected was analysed to identify Echo Thread^s needs in relation to market trends, consumer sentiment, and customer preferences regarding sustainability products and practices.
Results: The results show that the utilisation of social media analytic and big data are able to provide valuable insights into the needs and expectations of consumers towards Echo Thread in the performance of improving sustainability fashion. This enables the company to optimise marketing, product development, and communication strategies.
Conclusion and Suggestion: The conclusion of this study is that the implementation of social media analytic and big data can effectively contribute significantly to improving the performance of Echo Thread as an e-commerce company in the sustainability fashion sector. Suggestions for future research are to expand the scope of data and analysis methods, as well as to test the impact of the implementation of big data insights on the company^s financial performance metrics directly.
Keywords: analytic on social media, big data, decision making, sustainability fashion
Topic: Accounting and management information system
