Q01
メッセージ
すべてのテンプレートIndustry-Specific
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.
設問の例
テンプレートの内容をプレビューできます。すべての設問は公開前に自由に編集できます。
全12問・約7分
Q02
選択式必須
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
数値必須
In the last 7 days, on how many days did you listen to music for at least 10 minutes?
Q04
選択式必須
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
マトリクス必須
How much do you agree with each statement about the music service you use most?
4行 × 5列
- 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)
列: Strongly disagree · Disagree · Neutral · Agree · Strongly agree
Q06
ベスト・ワースト選択（MaxDiff）必須
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
各セットで最も良いもの・最も悪いものを選択最も良い:Matters most最も悪い:Matters least
Q07
ポイント配分必須
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
100ポイントを配分
Q08
ランク付け
Rank these ways of discovering new music from most to least important to you.
- Algorithm-generated recommendations
- Curated playlists
- Friends or word of mouth
- Social media
- Radio
- Live shows or festivals
ドラッグして順位を付ける
Q09
AIインタビュー
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
評価スケール必須
Overall, how satisfied are you with your current music listening experience?
範囲: 1 – 5
最小:Very dissatisfied最大:Very satisfied
Q11
選択式
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
メッセージ
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.
含まれる機能
AIによる深掘り
自由回答に合わせてAIが追加で質問し、固定のフォームでは拾えない具体的な内容を引き出します。
注意確認設問
急いだ回答や質の低い回答者を除外する仕組みを標準で備えています。
AIが作成する設問文
文言、設問の順序、条件分岐をAIが調査の目的に合わせて作成します。
自動レポート
回答が集まると、テーマ、引用、わかりやすい要約が自動で作成されます。
他ツールとの比較
ほかのアンケートツールで最も近いテンプレートを調べました。それぞれの優れている点と、このテンプレートがさらに踏み込んでいる点をまとめています。
このテンプレートを選ぶ理由
- 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 TemplateA 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.
優れている点
- 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
物足りない点
- 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 InsightsFocused 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.
優れている点
- 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
物足りない点
- 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 TemplateAimed 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.
優れている点
- Enterprise-grade survey platform with extensive question-type library
- Reasonable fit for general music website/service feedback
- Supports standard reporting dashboards
物足りない点
- 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
よくあるご質問
「Music Listening Habits & Streaming Experience Survey」テンプレートにはどのような設問が含まれていますか？
すぐに使える設問が12問含まれており、最初の設問は次のとおりです：「Hi! Thanks for taking a few minutes to talk about your music listening habits — how you find music, what services you us…」・「Which music streaming service do you use most often?」・「In the last 7 days, on how many days did you listen to music for at least 10 minutes?」。すべての設問は上でプレビューでき、自由に編集できます。
このアンケートの回答にはどのくらい時間がかかりますか？
回答者は通常、12問を約7分で回答し終えます。
テンプレートは編集できますか？
はい。公開前であれば、すべての設問、選択肢、順序を編集できます。設問の追加や削除のほか、調査の目的に合わせた作り直しをAIエディターに依頼することもできます。
このテンプレートは無料で使えますか？
はい。エディターで開けば、すぐに編集を始められます。お試しにアカウントは不要で、無料プランでアンケートを公開できます。
公開の準備はできましたか？
このテンプレートをエディターで開いてみてください。最初の回答者が目にする前に、すべてを自由に変更できます。
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