Data Science Utilization in Consumer Trend Prediction: A Qualitative Study on an e-commerce Market Research Team in Indonesia

Abstract

In the era of digital transformation, the e-commerce industry in Indonesia faces great challenges in understanding and responding to changes in consumer behavior that are very dynamic. Data science is a strategic approach that can help companies analyze consumer data deeply and predict market trends accurately. This research aims to explore how market research teams in e-commerce companies utilize data science in the process of predicting consumer trends. A qualitative approach with a case study design was used in this research, involving in-depth interviews, questionnaires, and observations of market research teams from three major e-commerce companies in Indonesia, namely Tokopedia, Bukalapak, and Blibli. The results show that tools such as Python, Tableau, and BigQuery are widely used in the analytics process, from data cleansing to trend visualization. The research team has a good conceptual understanding of data science, although there are still gaps in coordination between divisions. The implementation of data science has proven to have a positive impact on the accuracy of marketing strategies and the efficiency of business decision-making. Obstacles faced include limited technical human resources and lack of standardized documentation. This research provides a practical contribution in developing a data-driven market research ecosystem in Indonesia's e-commerce industry and serves as a basis for further research with a broader scope