This project analyzes user listening behavior on Spotify using historical data across albums, artists, and tracks. It explores trends over time, peak listening hours, platform usage, and user engagement through dynamic and interactive Power BI dashboards.
- Understand how user engagement with tracks, albums, and artists has evolved over time.
- Compare latest year vs previous year growth metrics.
- Visualize listening patterns by hour and day using heatmaps.
- Identify top 5 albums, artists, and tracks based on play count.
- Highlight behavior like skips, shuffle mode, and platform preferences.
- Enable drill-through and export functionality in the data grid for deeper exploration.
- Total Albums, Artists, and Tracks played (2014–2024)
- Top 5 Albums / Artists / Tracks
- YoY comparison between the Latest Year and Previous Year
- Weekday vs Weekend listening patterns
- Listening Hours vs Days – Heatmap identifying peak times
- Avg Listening Time vs Track Frequency – Scatter plot segmentation
- Detailed data grid with track metadata, play duration, and album-level summaries
| Tool | Purpose |
|---|---|
| Power BI | Data visualization and dashboard |
| Excel | Data cleaning and preprocessing |
| DAX | Calculated columns and KPIs |
| Spotify Data | User listening logs and metadata |
| Field Name | Description |
|---|---|
track_name |
Name of the track |
artist_name |
Performing artist |
album_name |
Album where the track appears |
ts |
Timestamp of track end (UTC) |
platform |
Platform used (web, mobile, desktop) |
ms_played |
Duration played in milliseconds |
reason_start |
Why the track started playing |
reason_end |
Why it stopped (skipped, ended, logout, etc.) |
shuffle |
Shuffle mode enabled or not |
skipped |
If the track was skipped |
- Weekends and evenings are peak listening periods.
- Shuffle mode is used consistently on mobile devices.
- Top artists include The Beatles, The Killers, and John Mayer.
- High-frequency tracks don’t always have the longest listening time — indicating skip behavior.
Amrutha C
📧 amuthac1126@gmail.com
🔗 LinkedIn
🔗 GitHub