모든 템플릿

Consumer Data Trust & Privacy Perceptions Survey

Measures consumer trust in organizational data handling, breach response expectations, and permission transparency. Use with general consumer panels to benchmark trust levels and identify priority improvements for privacy practices.

샘플 질문

템플릿에 포함된 내용을 미리 확인해 보세요. 모든 질문은 설문 공개 전에 자유롭게 수정할 수 있습니다.

질문 17개 · 약 8분
Q01
메시지

Welcome to this survey on data privacy and trust. This survey asks about your experiences with how companies handle personal data, respond to breaches, and request permissions. There are no right or wrong answers — we are interested in your honest opinions. Your responses are confidential and will be reported only in aggregate. Participation is voluntary and you may stop at any time. Estimated time: 6–8 minutes.

Q02
드롭다운

In the past 3 months, how often did you use online accounts that store your personal information (e.g., email, shopping, banking)?

  • Several times a day
  • About once a day
  • A few times a week
  • About once a week
  • Less than weekly
  • Not in the past 3 months
Q03
의견 척도

Overall, in the past 3 months, how much did you trust companies to handle your personal data responsibly?

척도: 17
최소:Not at all최대:A great deal
Q04
의견 척도

How confident are you that companies you use would notify you promptly if a data breach affected your personal information?

척도: 17
최소:Not at all confident최대:Extremely confident
Q05
의견 척도

How transparent were the permission requests you encountered from apps or websites in the past 3 months?

척도: 17
최소:Not at all transparent최대:Extremely transparent
Q06
장문형

Based on your responses in this survey, what one change would most improve your trust in how companies handle your personal data?

Q07
드롭다운

What is your age?

  • 18–24
  • 25–34
  • 35–44
  • 45–54
  • 55–64
  • 65+
  • Prefer not to say
Q08
메시지

Thank you for completing this survey. Your responses will help improve data transparency and privacy practices. You may now close this page.

Q09
의견 척도

How clear were the privacy notices and data-use explanations you encountered in the past 3 months?

척도: 17
최소:Not at all clear최대:Extremely clear
Q10
객관식

Which actions would most increase your confidence in a company's response to a data breach? Select up to 3.

  • Notify affected users within 72 hours
  • Explain clearly what happened and why
  • Identify exactly what personal data was affected
  • Provide clear next steps I can take
  • Offer a dedicated support contact
  • Issue regular status updates until resolved
  • Offer remediation such as credit monitoring
  • Publish an independent post-incident report
Q11
순위 매기기

Rank the following controls from the one you trust most to the one you trust least for managing app or website permissions.

  1. Operating system or device permission controls
  2. In-app privacy or settings menu
  3. Account-level security and privacy dashboard
  4. Per-permission prompts at install or first use
  5. App store permissions summary
드래그하여 순위 지정
Q12
AI 인터뷰

We'd like to explore your views on data trust and privacy in a bit more depth. An AI moderator will ask you a couple of follow-up questions based on your earlier responses.

Q13
드롭다운

Which best describes your gender?

  • Woman
  • Man
  • Non-binary
  • Prefer not to say
Q14
순위 매기기

Rank the following types of personal data from the one you are most comfortable with companies collecting to the one you are least comfortable with.

  1. Name and contact information
  2. Location or GPS data
  3. Browsing and search history
  4. Financial or payment information
  5. Health or biometric data
  6. Social media activity
드래그하여 순위 지정
Q15
드롭다운

In which region do you currently live?

  • Africa
  • Asia
  • Europe
  • North America
  • South America
  • Oceania
  • Prefer not to say
Q16
드롭다운

What is the highest level of education you have completed?

  • Less than high school
  • High school or equivalent
  • Some college, no degree
  • Associate degree
  • Bachelor's degree
  • Master's degree
  • Doctorate or professional degree
  • Prefer not to say
Q17
드롭다운

What is your current employment status?

  • Employed full-time
  • Employed part-time
  • Self-employed
  • Student
  • Unemployed
  • Retired
  • Prefer not to say

포함된 기능

  • AI 후속 질문

    정형화된 설문이 놓치는 세부 내용을, 주관식 답변에 맞춰 AI가 심층 질문으로 끌어냅니다.

  • 주의력 확인 장치

    성의 없는 답변과 저품질 응답자를 걸러내는 내장 안전장치입니다.

  • AI가 작성한 문안

    문구, 질문 순서, 분기 로직까지 AI가 연구 목표에 맞춰 작성합니다.

  • 자동 리포트

    응답이 모이면 주요 주제, 인용문, 이해하기 쉬운 요약이 자동으로 작성됩니다.

다른 서비스와 비교

다른 설문 도구의 가장 유사한 템플릿을 검토했습니다. 그 도구들이 잘하는 점과, 이 템플릿이 한발 더 나아가는 지점을 정리했습니다.

이 템플릿을 선택하는 이유

  • Directly measures trust in data handling, breach-response confidence, and permission/notice transparency rather than general consumer behavior
  • Includes ranking exercises for both data-type sensitivity and trust in specific privacy controls, giving concrete prioritization data
  • Includes an adaptive AI follow-up interview that can probe open-ended answers on privacy concerns in real time, something static templates cannot do
  • Captures a final open-text 'what one change would most improve your trust' question plus demographics, enabling segmented benchmarking and auto-generated reporting

SurveyMonkey

Consumer Behavior Survey Template

This is a general-purpose consumer behavior template focused on purchasing habits and brand engagement rather than data privacy or trust specifically. It's a ready-to-field static form on a well-established survey platform, useful for broad consumer research but not purpose-built for privacy/trust benchmarking. Teams wanting privacy-specific insight would need to heavily customize the question set themselves.

잘하는 점

  • Backed by a widely recognized survey platform with broad panel distribution options
  • Quick to deploy for general consumer research needs
  • Familiar interface likely lowers setup time for standard behavior questions

아쉬운 점

  • No adaptive AI follow-up questioning — responses are fixed, so nuanced privacy concerns can't be probed further
  • Not designed around data trust, breach response, or permission transparency, so relevant questions would need to be built from scratch
  • No published methodology for question design or automated per-response quality scoring

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