Know Your Sound
Drop your CSV files here
or click to browse — you can select multiple files
Step 1 — Export your CSV from Spotify
Exportify exportify.net
Watsonbox github.io/exportify
Export your Liked Songs — make sure to include audio features (Danceability, Energy, Valence…)
Your
Musical
DNA
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LIKED SONGS
Overview
Key Insights
Personal Music Profile
Your Listener Archetype
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Your Music DNA
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Top 5 musical keys · % of your library
Taste Fingerprint
Key numbers that define your music personality
Listening Eras
Which Decades Shaped Your Taste?
Taste Over Time
Audio Feature Evolution (by month you saved songs)
How your taste in sound has changed over time — smoothed 3-month rolling average
Mood Shift Over Time
Average happiness (valence) of songs you saved each month
Energy Shift Over Time
Average energy of songs you saved each month
Artist Discovery Timeline
When you first saved a song by each artist — your top 20 discoveries
# Artist First Saved Songs Avg Popularity Avg Energy Avg Valence
Popularity Taste Over Time
Are you discovering more underground or mainstream music lately?
■ Avg Popularity ■ Mainstream (>70) ■ Underground (<40)
Artists & Tracks
Top Artists
Most Popular Tracks
Extremes & Outliers
Artist Deep Dive
Top 10 Artist Profiles
Audio fingerprint of your most-saved artists
Audio Features
Average Profile
Feature Radar
Mood Analysis
Energy vs. Valence (Mood Map)
Each dot = one song
SadHappy
Valence Distribution
Danceability Distribution
Rhythm & Key
Tempo Distribution (BPM)
Keys Used
Major vs Minor
Major Minor
Acoustic & Instrumental
Acousticness Spectrum
Instrumentalness Spectrum
Live & Spoken
Liveness Score
Speechiness Score
Loudness
Loudness Distribution (dBFS)
Deep Audio Analysis
Feature Variance (How Diverse Your Sound Is)
High variance = eclectic taste, Low = consistent sound
Audio Feature Heatmap
Energy vs Danceability across your library
Low DanceHigh Dance
Time Signature Breakdown
Popularity Tiers
BPM Sweet Spots
Your top tempo ranges
Mood Intelligence
Mood Quadrant Breakdown
Energy × Valence → your emotional listening zones
Energy Tier Breakdown
How your library splits across energy levels
Valence Tiers
Genres
Genre Distribution
Genre Cloud
Labels & Content
Top Record Labels
Explicit Content
Popularity Distribution
Library Diversity
Artist Concentration
How spread out are your listens across artists?
Songs per Artist Distribution
When You Save Songs
Songs Added Over Time
Release Years
Songs by Release Year
Song Duration
Duration Distribution
Feature Correlations
Listening Habits
Day-of-Week Saves
Month-of-Year Saves
Saving Streaks
Release Patterns
Songs by Release Month (across all years)
Which month produces the most music you like?
Newness vs Nostalgia
Gap between release date and when you saved it
Collection Analytics
Save Rate Over Time
Songs saved per week, rolling
Cumulative Library Growth
Library Stats at a Glance
Full Statistical Summary
Descriptive Statistics (Mean · Median · Std Dev · Min · Max · P25 · P75)
FeatureMeanMedianStd DevMinP25P75MaxDistribution
Feature Correlation Matrix
⬡ Pearson Correlation Between All Audio Features
Green = positive correlation · Red = negative · Darker = stronger
Pairwise Feature Scatter
Key Feature Pairs — Each Dot is a Song
Save-Time Heatmap
🗓 Day × Hour Heatmap — When Do You Save Music?
Based on "Added At" timestamps — brighter = more saves
Fewer saves More saves
Genre Audio Fingerprints
How Do Your Top Genres Actually Sound?
Average audio features per genre — Energy · Valence · Dance · Acoustic
Popularity Deep Dive
Popularity vs Release Year
Do older songs stay popular in your library?
Mainstream vs Niche Score
Your library's underground / mainstream breakdown at a glance
Tempo Intelligence
🥁 BPM Zone Analysis
Named tempo zones — how your library splits across musical speeds
⚡ BPM vs Energy Correlation
Is faster always more energetic in your library?
Artist Intelligence
📊 Artist Depth Score
Artists ranked by how deep you go (songs + diversity score)
🎯 Artist Popularity Spread
Range of popularity among your top artists
Library Health Report
🏥 What Makes Your Library Unique — A Full Diagnostic
Decade Comparison
🎵 How Each Decade Sounds in Your Library
Average audio features split by the decade a song was released
📈 Popularity by Decade
Are old songs more or less popular in your library?
Duration Intelligence
⏱ Song Length Buckets
📏 Duration vs Energy
Do longer songs tend to be more mellow?
🎬 Total Runtime Facts
Advanced Listener Insights
All Listener Archetypes
Which one sounds like you?
Select a track
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