SERIES: Music, Technology and the Future of the Industry

S4-S6 / Adult

60–90 minutes

Spotify Wrapped and Music Data: Create a Music Data Storyboard

Spotify Wrapped turns ordinary listening logs into one of the world’s most recognisable personal data stories. You will create a Wrapped-style storyboard while asking what the numbers really show — and what they do not. By the end of this challenge you will: Distinguish measured data from inference Find patterns in listening data Analyse […]

Spotify Wrapped and Music Data: Create a Music Data Storyboard

Your Mission

What does your music data say — and what does it not say?

Build a Wrapped-style music data story and investigate why a platform recap can feel like a story about identity.

The Shape of This Challenge

Discover

✏️ ️ Notice & question

Explore

️ Investigate & test

Create

✏️ Make & communicate

Reflect

️ Think & apply

Discover

Build the concepts and questions you need before researching.

Step 1

What Can Listening Data Actually Measure?

✏️ Metric sort · 8–10 mins

We are learning to distinguish measured listening behaviour from unsupported personal inference.

Listening data can show plays, repeats and timing. It cannot automatically explain personality, mood or identity.

Your Task

List eight possible listening metrics.
Sort them into directly measured and inferred/needs caution.
Write one sensitive conclusion you should not infer from music data alone.

I can separate measured behaviour from interpretation.

→ This sets the ethical boundary for your data story.

Critical ThinkingData LiteracyDigital Citizenship

Step 2

Find the Story in the Numbers

️ Data hunt · 10–12 mins

We are learning to identify patterns, comparisons and changes in a small listening dataset.

A data story is stronger than a list of rankings when it reveals a pattern.

Your Task

Use a fictional, anonymised or teacher-provided dataset.
Calculate or identify at least five metrics.
Find one change, contrast or surprising pattern.
Write three possible headlines and choose the most accurate.

I can identify a defensible story from listening data.

→ This becomes the narrative spine.

Critical ThinkingData LiteracyCommunication

Explore

Use evidence, comparison and testing to move beyond assumptions.

Step 3

How Does Wrapped Turn Data Into Identity?

Choose your route · 12–15 mins

We are learning to analyse how a data product turns behaviour into a shareable story.

Selection, sequencing, labels, comparison and visual hierarchy make data feel personal.

Your Task

Complete one research route.
Identify at least four storytelling/design techniques.
Separate factual metrics from interpretive labels.
Explain why the product is marketing as well as analytics.

⚡ Quick Track

Analyse a public Wrapped example or official explanation. Identify sequence, hierarchy, comparison and sharing prompts.

Dig Deeper

Compare Wrapped with another annual recap/data-story product. Analyse how each creates emotion, identity and sharing.

I can analyse how a platform transforms user data into an identity-shaped media product.

→ This gives your storyboard a critical design lens.

ResearchCritical ThinkingMedia Literacy

Step 4

What Does the Data Leave Out?

️ Missing-data audit · 10–12 mins

We are learning to identify limitations and missing context in a personal data story.

Data may miss offline listening, shared accounts, background play, changing tastes or why a track was played.

Your Task

List at least five limitations.
Choose the one that most affects your chosen story.
Rewrite your headline so it does not overclaim.
Add one transparency note.

I can communicate data patterns with appropriate limitations.

→ This makes the final storyboard credible.

Critical ThinkingData LiteracyEthical Reasoning

Create & Share

Turn the strongest evidence into a professional output and reflect on what it means.

Step 5

Create a Music Data Storyboard

✏️ Analyse · Create · 25–35 mins

We are learning to turn listening data into a clear, engaging and honest story.

Make the difference between data and interpretation visible.

Your Task

Use at least five metrics.
Build around one clear pattern or change.
Include at least one comparison or relationship.
Add one ‘what this cannot tell us’ note.
Choose one output below.

Wrapped-Style Data Story

6 slides · maximum 25 words per slide

⏱ 30–35 mins

Create a sequence of data cards that builds to one clear listening story.

Music Data Storyboard

1 page · 5–7 panels + 120–160 words

⏱ 25–30 mins

Map the story, metrics, insight and limitation on one page.

My Year in Music Data

90 seconds final runtime

⏱ 30–35 mins

Narrate a music-data story using a fictional or anonymised dataset.

I can create an engaging music data story without unsupported personal claims.

→ This is your finished mission output.

Critical ThinkingCommunicationDigital Citizenship

Step 6

Reflect, Apply, Look Forward

️ Think or discuss · 5–8 mins

We are learning to reflect on how personalisation can shape identity and platform loyalty.

Next you will move from algorithms analysing music to AI systems generating it.

Your Task

Answer the prompts.
Name one insight genuinely supported by the data.
Write one question about who should control music-related personal data.

Reflect

Which metric told the strongest story and which was mostly decoration?

Apply

How can a yearly recap strengthen platform loyalty?

Look Forward

What could go wrong if entertainment data were used to infer sensitive traits?

I can explain how data storytelling can be persuasive without being the whole truth about a person.

→ You are ready to investigate AI music.

ReflectionCritical ThinkingDigital Citizenship

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TOOLKIT

Choose Your Tools

Use current, credible music-industry sources where possible. Record dates and distinguish platform/company claims from independent evidence.

Data

Use fictional, anonymised or teacher-provided listening data.

Analyse

Look for patterns without inferring sensitive traits.

Create

Use a storyboard, slides or narrated explainer.

Educator / Parent Notes

Age, Stage and Prior Learning: S4–S6 / Adult.

Before You Start: Do not require learners to share personal listening histories.

How to Open This: Ask: “Why does a list of songs feel meaningful when a platform turns it into a story about you?”

Scheduling: 35–45 mins for Steps 1–4; 25–35 mins for Step 5.

If a Pupil Gets Stuck: Provide a small 20–30 row fictional dataset and five ready-made metrics.

For Fast Finishers: Compare two narratives built from the same data.

Marking Guidance: Look for accurate data use, fact/inference distinction, narrative hierarchy and transparent limitations.

Spotify Wrapped and Music Data: Create a Music Data Storyboard

Spotify Wrapped and Music Data: Create a Music Data Storyboard

Discover

What Can Listening Data Actually Measure?

Find the Story in the Numbers

Explore

How Does Wrapped Turn Data Into Identity?

What Does the Data Leave Out?

Create & Share

Create a Music Data Storyboard

Reflect, Apply, Look Forward

Show What You Have Learned

Data

Analyse

Create

Show What You Have Learned

Data

Analyse

Create

TOOLKIT

Data

Analyse

Create

Educator / Parent Notes

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