Spotify Music Analytics This interactive Power BI report, made with use of Claude design and inspired by works of PauloGrijo Gusbavia nayarahellen , and MariusHelle explores features of a large catalogue of Spotify tracks and what separates the songs people love from the ones they skip. Instead of a single dashboard, it's built as a guided experience across several connected pages, combining exploratory analysis and storytelling. What's inside:Overview — a landing page that surfaces the headline findings up front, with quick-read summary cards so you can see the main takeaways before diving deeper.Evolution of Sound — a chapter-based walkthrough of how the sound of popular music has shifted over the decades, with a narrative rail and supporting charts for each theme.Popularity Question — the analytical core: a "fingerprint" radar comparing the average popular track against the average unpopular one, a simple model view showing which features carry the most predictive weight, per-feature scatter plots, and breakdowns by genre and era.Listening Room — a fully filterable track explorer. Filter by genre, release year and audio-feature ranges.Make your own Hit! — an interactive tool where you set several feature levels to generate your own track. Note: for public demo purposes the tracks have been pre-generated using the Suno API.Key takeaways:Sound alone doesn't make a hit: a track's audio features explain only ~3% of its popularity — the rest is fame, marketing, playlists and timing.Music has drifted moodier and more produced. Over 60 years songs got less acoustic, more danceable, louder, shorter, and measurably less cheerful.Hits and flops sound almost the same. The audio "fingerprints" of popular and unpopular tracks nearly overlap.Data sources:- https://www.kaggle.com/datasets/jashanjeetsinghhh/songs-dataset- https://www.kaggle.com/datasets/salvatorerastelli/spotify-and-youtube Contact: Robert van de Vorst - https://www.linkedin.com/in/robertvandevorst/ eyJrIjoiZTI3NzNhNTgtMjBkMS00NTU2LThjN2EtZDM0NDAwYWNhZTQ2IiwidCI6Ijg5NzU5Zjk5LWQxNzEtNDZjMC04YzZjLWY3ZWNhYTJlOGI2ZSIsImMiOjh9

Robert_1985

Advocate I

1 month ago

Spotify analytics

Spotify Music Analytics

This interactive Power BI report, made with use of Claude design and inspired by works of PauloGrijo Gusbavia nayarahellen , and MariusHelle explores features of a large catalogue of Spotify tracks and what separates the songs people love from the ones they skip. Instead of a single dashboard, it's built as a guided experience across several connected pages, combining exploratory analysis and storytelling.

What's inside:

Overview — a landing page that surfaces the headline findings up front, with quick-read summary cards so you can see the main takeaways before diving deeper.
Evolution of Sound — a chapter-based walkthrough of how the sound of popular music has shifted over the decades, with a narrative rail and supporting charts for each theme.
Popularity Question — the analytical core: a "fingerprint" radar comparing the average popular track against the average unpopular one, a simple model view showing which features carry the most predictive weight, per-feature scatter plots, and breakdowns by genre and era.
Listening Room — a fully filterable track explorer. Filter by genre, release year and audio-feature ranges.
Make your own Hit! — an interactive tool where you set several feature levels to generate your own track. Note: for public demo purposes the tracks have been pre-generated using the Suno API.

Key takeaways:

Sound alone doesn't make a hit: a track's audio features explain only ~3% of its popularity — the rest is fame, marketing, playlists and timing.
Music has drifted moodier and more produced. Over 60 years songs got less acoustic, more danceable, louder, shorter, and measurably less cheerful.
Hits and flops sound almost the same. The audio "fingerprints" of popular and unpopular tracks nearly overlap.

Data sources:
- https://www.kaggle.com/datasets/jashanjeetsinghhh/songs-dataset

- https://www.kaggle.com/datasets/salvatorerastelli/spotify-and-youtube

Contact: Robert van de Vorst - https://www.linkedin.com/in/robertvandevorst/

eyJrIjoiZTI3NzNhNTgtMjBkMS00NTU2LThjN2EtZDM0NDAwYWNhZTQ2IiwidCI6Ijg5NzU5Zjk5LWQxNzEtNDZjMC04YzZjLWY3ZWNhYTJlOGI2ZSIsImMiOjh9

Entertainment