QuestionPunkQuestionPunk
Start free
All templates

Music Listening Habits & Streaming Experience Survey

Explores how people discover, choose, and experience music streaming services — covering platform choice, genre mix, discovery channels, and what drives satisfaction. An AI follow-up interview digs into a recent real discovery or switching moment to surface the 'why' behind the ratings. Built for music platforms, labels, and artist teams.

Use this templateBrowse more templates

Sample questions

A preview of what’s in the template. Every question is editable before you launch.

12 questions · ~7 min
Q01
Message

Hi! Thanks for taking a few minutes to talk about your music listening habits — how you find music, what services you use, and what matters most to you. This takes about 5 minutes and there are no wrong answers.

Q02
Multiple ChoiceRequired

Which music streaming service do you use most often?

  • (Replace with Streaming Service A)
  • (Replace with Streaming Service B)
  • (Replace with Streaming Service C)
  • Downloaded/owned music files
  • Radio (broadcast or online)
  • YouTube or video platforms
Q03
NumberRequired

In the last 7 days, on how many days did you listen to music for at least 10 minutes?

Q04
Multiple ChoiceRequired

In which situations do you typically listen to music? Select all that apply.

  • Commuting or traveling
  • Working or studying
  • Working out
  • Relaxing or unwinding
  • Socializing or at parties
  • Household chores
Q05
MatrixRequired

How much do you agree with each statement about the music service you use most?

4 rows × 5 columns
  • Its recommendations match my taste
  • It's easy to find new music I like
  • Sound quality meets my needs
  • It's worth what I pay (or the ads I tolerate)
Columns: Strongly disagree · Disagree · Neutral · Agree · Strongly agree
Q06
Best–Worst Trade-off (MaxDiff)Required

When choosing a music service, which of these matter most and least to you?

  • Price / subscription cost
  • Size of music library
  • Personalized recommendations
  • Sound quality
  • Offline listening
  • Ad-free experience
  • Social or sharing features
  • Podcast and other audio content
Pick best & worst per setBest:Matters mostWorst:Matters least
Q07
Point AllocationRequired

Thinking about your listening over the last month, how would you split 100 points across these genres based on how often you listened to each?

  • Pop
  • Hip-Hop / Rap
  • Rock
  • Electronic / Dance
  • R&B / Soul
  • Country / Folk
  • Other genres
Allocate 100 points
Q08
Ranking

Rank these ways of discovering new music from most to least important to you.

  1. Algorithm-generated recommendations
  2. Curated playlists
  3. Friends or word of mouth
  4. Social media
  5. Radio
  6. Live shows or festivals
Drag to rank
Q09
AI Interview

Reconstruct the most recent time this person discovered a new song or artist they actually liked: what channel surfaced it, what made it stick versus getting skipped, and whether it changed how they use their main service. If they rated recommendations or discovery low in the earlier ratings, probe specifically what frustrates them and what would need to change for them to trust recommendations more.

Q10
Rating ScaleRequired

Overall, how satisfied are you with your current music listening experience?

Range: 1 – 5
Min:Very dissatisfiedMax:Very satisfied
Q11
Multiple Choice

Which age range do you fall into?

  • Under 18
  • 18-24
  • 25-34
  • 35-44
  • 45-54
  • 55-64
  • 65+
  • Prefer not to say
Q12
Message

That's everything — thank you for sharing how you listen to music! Your answers will feed into a report on listener preferences and discovery habits.

What’s included

  • AI follow-ups

    Adaptive probes on open-ended answers that pull out detail a static form would miss.

  • Attention checks

    Built-in safeguards against rushed answers and low-quality respondents.

  • AI-drafted copy

    Wording, ordering, and branching written by the AI — tuned to your research goal.

  • Auto report

    Themes, quotes, and a plain-English summary write themselves once responses come in.

How it compares

We reviewed the closest templates from other survey tools. Here’s what they do well — and where this template goes further.

Why this template

  • Includes an AI follow-up interview that reconstructs a recent real discovery or switching moment, surfacing the 'why' behind satisfaction ratings rather than stopping at a rating scale
  • Combines structured measurement (matrix agreement statements, MaxDiff on choice drivers, constant-sum allocation of monthly listening, ranking of discovery channels) with open-ended AI probing in one flow
  • Captures both behavioral frequency (days listened in the last 7 days, listening situations) and platform choice/demographics for segmentation
  • Ends with automated scoring and a generated report, so labels and platform teams get synthesized 'why' insights rather than raw open-text to sort through manually

SurveyMonkey

Music Listening Template

A ready-to-field template covering general music listening habits, likely with standard multiple-choice and rating questions. It's built on SurveyMonkey's broad survey infrastructure with strong reporting and distribution tools, but the template itself appears to be a fixed questionnaire rather than an adaptive interview.

What it does well

  • Backed by SurveyMonkey's mature survey distribution and analytics ecosystem
  • Likely quick to deploy with pre-built question logic and benchmarks
  • Familiar respondent experience that supports high completion rates

Where it falls short

  • No adaptive AI follow-up questioning — respondents answer fixed items with no probing into individual context
  • No voice AI interview option or guided screen-share tasks
  • No published prompt-level methodology or transparent AI scoring logic

SurveySparrow

Online Music Streaming Survey Template | Listener Insights

Focused specifically on online music streaming, this template likely covers platform choice and listener satisfaction in a conversational-style survey format. SurveySparrow emphasizes chat-like UI, but this is still a pre-set question sequence rather than dynamic AI-driven follow-up. No mention of voice interviews or automated quality scoring of responses.

What it does well

  • Conversational, chat-style survey format that can feel more engaging than grid-based forms
  • Purpose-built for streaming audience insights
  • Likely supports skip logic for platform-specific branching

Where it falls short

  • Conversational UI is scripted, not adaptive — it can't generate a new follow-up question based on a specific answer the way an AI interview can
  • No voice AI interview or guided screen-share task option
  • No automated per-response quality scoring or transparent prompt documentation

QuestionPro

Music Website Survey Template

Aimed more broadly at music website/platform feedback rather than streaming listening habits specifically, this template is a static question set for gauging site or service satisfaction. QuestionPro offers solid enterprise survey tooling, but this template doesn't appear tailored to discovery/switching behavior or streaming-specific metrics like the ones covered here.

What it does well

  • Enterprise-grade survey platform with extensive question-type library
  • Reasonable fit for general music website/service feedback
  • Supports standard reporting dashboards

Where it falls short

  • Template targets website feedback broadly, not streaming discovery/switching behavior specifically
  • No adaptive AI follow-up interview to dig into a respondent's actual recent decision moment
  • No voice AI interviews, guided screen-share tasks, or automated response-quality scoring

Ready to launch?

Open this template in the editor. Every part is yours to change before the first respondent sees it.

Use this templateStart free