Optimizing Content Strategy for Spotify Philippines: A BI Study of OPM and Global Streaming Trends

Spotify has become the most used streaming music service. This study explores the listening behavior of Filipino listeners on Spotify, where the contrast between foreign music and Original Pilipino Music (OPM) is emphasized. The focus of this study is to identify the most important music preference and streaming popularity factors. This was done by performing an analysis on the top 25 most streamed songs within a period of four weeks, where computer programs like Microsoft Excel and Weka were used. Three machine learning algorithms, namely M5P regression, clustering, and linear regression, were used to identify user pattern behavior. The findings showed that OPM songs typically have higher average streams and a longer chart presence, and that success is strongly predicted by prior chart performance and consistency. Filipino listeners exhibit a strong preference for familiar and locally produced music, indicating the cultural significance of OPM. The findings suggest that optimizing content strategy and recommendation algorithms based on historical streaming data can help improve user engagement and the presence of local artists on Spotify Philippines. The results provide concrete suggestions for increasing user satisfaction, marketing efficiency, and personalizing the platform.