Visual Analytics of Spotify Music Data for Listener Behavior Insights - Madek Jeani Purnama; Cokorda Pramartha; Christina Ayu Maha Dewi (Yayasan Sinergi Widya Nusantara (Sidyanusa), 2025)
This study applies a visual analytics approach to explore Spotify music streaming data and uncover listener behavior patterns, genre preferences, and temporal listening trends. The dataset, obtained from the Maven Analytics Spotify Streaming History Data Playground, comprises 149,860 records with attributes such as track name, artist, duration, platform, and playback reason. Using Pentaho Data Integration (PDI), the data was cleaned, transformed, and enriched with a genre feature generated through ChatGPT-based classification of artist information. The processed dataset was then visualized in Tableau, producing interactive dashboards that revealed that The Beatles and The Killers were the most played artists, with Rock as the most dominant genre. Listening activity peaked during late-night hours, and Android was identified as the most-used platform. These results demonstrate how integrating ETL and visualization tools can convert raw streaming data into actionable insights for user engagement, personalized recommendations, and strategic music marketing.