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Visualizing Data —
Music, Culture & Streaming

What does the music you listen to say about who you are? An information design project examining how age, ethnicity, and streaming habits shape music preferences across the US; three datasets, three hypotheses, one visual narrative.

Information Design Project (Solo)
Designer & Data Analyst
3 x 2018 US datasets via Statista
Data Analysis · Dashboard Design · Visual Storytelling
2023
Visualizing Data cover
Project cover — The Interplay of Music Preferences, Streaming Platforms, Ethnicity, and Age

The Premise

Music is personal but it's also deeply cultural. The genres we gravitate toward, the platforms we stream on, and the artists we consider "representative" of a culture are all shaped by demographic factors we often don't consciously notice.

This project asked: can data reveal the cultural dynamics at play in how Americans consume music? Using three 2018 datasets from Statista, I set out to find patterns, test hypotheses, and ultimately tell one cohesive visual story.

Narrative slide — Music
The narrative frame — music as a mirror of cultural landscape and consumption habits

Three Hypotheses

Hypothesis 1 — Exploratory
Hypothesis 1 — Exploratory: genre variation across age and ethnicity
Hypothesis 2 — Explanatory
Hypothesis 2 — Explanatory: demographic influence on streaming platform choice
Hypothesis 3 — Predictive
Hypothesis 3 — Predictive: ethnicity and perception of what "represents" modern America
Hypothesis 01 — Exploratory

There is a noticeable variation in favourite music genres across different age groups and ethnicities.

Hypothesis 02 — Explanatory

Demographic factors like age influence how music is consumed and which streaming platforms people choose.

Hypothesis 03 — Predictive

The perception of which music genres "represent modern America" varies significantly across ethnic groups and cultural identity shapes what people see as mainstream.

The Three Datasets

Dataset 1 — genre by age
Dataset 1 — favourite music genres broken down by age group
Dataset 2 — streaming platforms
Dataset 2 — monthly active users across streaming platforms (Spotify, Apple Music, Pandora, etc.)
Dataset 3 — genre by ethnicity
Dataset 3 — genre preferences and cultural representation across racial and ethnic groups

Process Work

This project didn't start with music. I began with a completely different topic, but after reviewing available datasets I found the volume of information overwhelming and couldn't find data that genuinely engaged me. I stepped back, did a proper brainstorming session, and settled on music, which stayed aligned with the theme of content consumption while being a topic I actually wanted to spend time with.

That pivot taught me something important about data visualisation projects: you have to care about the subject. The design decisions, what to highlight, what comparison to lead with, what the emotional arc of the dashboard should be, all of those require genuine curiosity about the material. If you're just executing a brief, those decisions feel arbitrary. When you're invested, they feel inevitable.

Dashboard — final output
Final dashboard — three datasets unified into one visual narrative

Key Findings

Finding 01

Pop dominates among younger age groups; Classic Rock indexes much higher among 45+ listeners, confirming strong generational genre clustering.

Finding 02

Younger listeners skew heavily toward Spotify and Apple Music; older demographics lean toward Pandora Radio; platform choice tracks closely with age.

Finding 03

Hip Hop/Rap is considered representative of modern America by a significantly higher proportion of Black respondents than any other ethnic group.

Finding 04

Country music is seen as "representative of modern America" primarily by white respondents, revealing how cultural identity shapes perception of the mainstream.

Reflection

Data visualisation expanded my toolkit as a designer in ways I didn't expect. The core challenge isn't choosing chart types, it's deciding what story you want to tell and what comparisons you want the viewer to make. Every design decision in a dashboard is an argument about what matters.

I also became more aware of how data about people carries cultural weight. The findings here aren't neutral statistics. They reflect real patterns of identity, belonging, and representation. How you visualise that, and what you choose to foreground, has consequences. That responsibility is something I take seriously as a designer.

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