Listening Intelligence,
visualized.

A music intelligence dashboard offering a deep-dive into listening patterns, taste evolution, and discovery habits — built from real listening data, designed with love, and rendered with D3.js.

Identity

Sonic Fingerprint

What you listen to may give subtle clues about who you are in a musical sense — the artists, genres, and audio features that define your musical identity.

Period
Total Hours

14

+18.5% vs last week

Unique Artists

131

+22.1% vs last week

Top Genre
Deep House

48%

+12.3% vs last week

Top Artists

These are the artists most in rotation for the selected time range above. There is a weekly, trimestral, yearly and all time ranges to pick from.

1Massive Attack

Massive Attack

Electronic

20

plays

1

hours

2Soul Wun

Soul Wun

Deep House

12

plays

1

hours

3Chaos in the CBD

Chaos in the CBD

Deep House

10

plays

1

hours

4Tâches

Tâches

Electronic

8

plays

1

hours

5Evren Furtuna

Evren Furtuna

Deep House

7

plays

0

hours

6Gab Rhome

Gab Rhome

Deep House

7

plays

0

hours

Genre Affinity

What are the degrees of attraction to certain musical styles? How broad and deep is your engagement with it is? How strongly you identify with the genre's sound, culture, and aesthetics?

48
32
18
14
10
8
6
Deep HouseElectronicAmbientTechnoJazzClassicalHouse
Deep HouseElectronicAmbientTechnoJazzClassicalHouse

Audio DNA

EnergyValenceDanceAcousticInstrumentalSpeechTempoLiveness

People high in openness often show strong affinity for complex or novel genres (classical, jazz, eclectic, “experimental” styles), and enjoy exploring new sounds rather than sticking only to familiar hits.

Strong affinity for energetic mainstream genres (chart pop, dance, contemporary rock) often correlates with extraversion and sociability, since this music fits social, party, and group settings.

Very narrow, rigid genre affinity can hint at lower openness and a preference for predictability and clear identity boundaries, whereas broad, flexible affinity suggests curiosity and cognitive flexibility.

People who use music heavily for emotion regulation often show high “musical affinity” in general, which is linked to stronger emotional sensitivity and engagement, regardless of which specific genres they love.

Habits

When and how do you listen?

Your listening rhythms — peak hours, daily patterns, and session behaviors that reveal how music fits into your life.

Daily Average

148min

+7.8% vs last year

Peak Hour

22:00

+0.0% vs last year

Avg Session

52min

+11.4% vs last year

Hourly Distribution

Average minutes listened by hour of day

20m40m60m
0:006:0012:0018:0023:00
Peak: 64m

Weekly Heatmap

Listening intensity across every hour of the week

12:00
MonTueWedThuFriSatSun

Change

How has your taste evolved?

A year of genre shifts, obsessions, and rediscoveries — the narrative arc of your listening journey.

ElectronicAmbientClassicalDeep HouseTechnoJazz

Listening Phases

This visualization provides insights into taste evolution over time, with recognizable prevalence of certain styles.

The Classical Immersion

Nicholas Britell scores and Händel defined the early months — deep listening to compositional structure and orchestral texture.

Main genre: Classical
JanMar

The Ambient Descent

Yagya and Giriu Dvasios pulled you into ambient and dub techno territory — long, immersive sessions with minimal variation.

Main genre: Ambient
AprJun

Deep House Summer

Geju, Chaos in the CBD, and Landhouse took over — warm, rhythmic grooves for late-night and weekend sessions.

Main genre: Deep House
JunAug

Electronic Exploration

Max Cooper and Eric Hilton led a broader electronic sweep — trip-hop, downtempo, and experimental textures.

Main genre: Electronic
AugOct

Jazz Interlude

Miles Davis and jazz fusion crept in — a reflective shift toward improvisational and acoustic forms.

Main genre: Jazz
OctNov

The Return to Form

Back to the core — Massive Attack, Skinshape, and downtempo electronica closed out the year.

Main genre: Electronic
NovDec

Discovery

How do you find new music?

The pathways from first listen to heavy rotation — which sources stick, and how quickly new artists earn their place.

New Artists

131

+14.3% vs last year

Discovery Rate

2.8week

+10.5% vs last year

Retention

18.7%

+6.2% vs last year

Discovery Flow

How new artists travel from discovery source to listening outcome.

Top Source

DiscoverWeekly

Responsible for the most artists entering rotation

Time to Rotation

14days

Average time from first listen to regular play

Weekly Rate

2.8artists/week

Average new artist discovery pace

Retention Rate

18.7%

Of discovered artists that make it to rotation

Architecture

How it works

The pipeline from raw listening data to interactive visualization — ingestion, enrichment, derived features, and rendering.

Ingest

Pull listening history from Spotify and Last.fm APIs — every play, timestamp, and context.

Spotify Web API, Last.fm API, OAuth 2.0

Enrich

Layer on audio features, artist metadata, genre classification, and release data.

Audio Features API, Last.fm Tags

Derive

Build sessions, detect phases, compute discovery timelines, and generate listening narratives.

Custom pipeline, D3 statistics

Visualize

Render interactive charts with D3.js inside a server-rendered Next.js application.

D3.js, React 19, Framer Motion

Deploy

Ship to deployment with edge-optimized static generation and on-demand revalidation.

Next.js 16, Edge Runtime

©2026 Music Intelligence Engine by FRND | Would you like to create yours? Get in touch.