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Privacy & Compliance

On-Device Personalization Trust & Privacy Preferences Survey

Measures user trust, comfort boundaries, and permission preferences for on-device personalization features. Designed for product and privacy teams validating data-handling approaches before launch.

Sample questions

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

25 questions · ~11 min
Q01
Message

Welcome, and thank you for participating in this survey about your experiences with on-device personalization and data privacy. Your participation is entirely voluntary, and you may stop at any time. There are no right or wrong answers—we are interested in your honest opinions. All responses are anonymous and will be reported only in aggregate to inform product research. This survey takes approximately 8–10 minutes to complete.

Q02
Multiple Choice

Which of the following devices do you use at least once a week? Select all that apply.

  • Smartphone
  • Tablet
  • Smartwatch
  • Laptop or desktop computer
  • Smart TV
  • Smart speaker
  • None of these
Q03
Multiple Choice

In the past 3 months, which of the following on-device personalization features have you personally used? Select all that apply.

  • Keyboard autocorrect or next-word suggestions
  • Photos grouped by faces or scenes on your device
  • Voice assistant that processes commands locally
  • App suggestions based on on-device usage patterns
  • Health or fitness insights processed on your device
  • None of these
Q04
Opinion Scale

Overall, how much do you trust on-device personalization to protect your data privacy?

Scale: 17
Min:Do not trust at allMax:Trust completely
Q05
Ranking

Please rank the following data types from most comfortable (1) to least comfortable (6) for on-device personalization to use.

  1. Contacts metadata (e.g., how often you contact someone)
  2. Typing patterns (not message content)
  3. Browsing history on this device
  4. Location history
  5. Photos metadata (e.g., timestamps, scenes)
  6. Health and fitness sensor data
Drag to rank
Q06
Multiple Choice

Imagine a keyboard app offers on-device learning with an optional encrypted cloud backup to sync predictions across your devices. Which option would you choose?

  • On-device learning only (no cloud backup)
  • On-device learning plus encrypted cloud backup
  • Cloud backup only
  • I would not use personalization in this app
Q07
AI Interview

We'd like to explore your thoughts on on-device personalization in a bit more depth. A short AI-guided conversation will ask you a couple of follow-up questions based on your earlier responses.

Q08
Dropdown

What is your age?

  • 18–24
  • 25–34
  • 35–44
  • 45–54
  • 55–64
  • 65+
  • Prefer not to say
Q09
Message

Thank you for completing this survey. Your feedback will help improve on-device personalization features and privacy practices.

Q10
Dropdown

What is your primary smartphone platform?

  • Apple iOS
  • Google Android
  • Other or no smartphone
Q11
Opinion Scale

Thinking about the past 30 days, how satisfied are you with the on-device personalization feature you used most often?

Scale: 17
Min:Not at all satisfiedMax:Extremely satisfied
Q12
Opinion Scale

To what extent do you agree or disagree with the following statement: "I understand how on-device personalization uses my data."

Scale: 17
Min:Strongly disagreeMax:Strongly agree
Q13
Multiple Choice

Which of the following types of data, if used for personalization, should never leave your device? Select all that apply.

  • Contacts metadata
  • Typing patterns (not content)
  • Browsing history
  • Location history
  • Photos metadata
  • Health and fitness sensor data
  • None of the above
  • Other (please specify)
Q14
Long Text

Based on your responses in this survey, is there anything else you would like companies to know about your data boundaries and preferences?

Q15
Multiple Choice

Which best describes your gender?

  • Woman
  • Man
  • Non-binary
  • Prefer to self-describe
  • Prefer not to say
Q16
Long Text

Was there anything about that feature that felt intrusive or unclear? If so, please describe it briefly.

Q17
Opinion Scale

To what extent do you agree or disagree with the following statement: "On-device personalization meaningfully improves my daily experience with my devices."

Scale: 17
Min:Strongly disagreeMax:Strongly agree
Q18
Multiple Choice

Which permission approach would you prefer for on-device personalization?

  • Ask every time data is first used
  • Ask once per data type, then remember my choice
  • One-time setup with a clear dashboard to change settings later
  • No prompts; features off by default unless I enable them
Q19
Dropdown

In which region do you currently reside?

  • United States
  • Canada
  • United Kingdom
  • European Union
  • Australia
  • India
  • Other
Q20
Opinion Scale

To what extent do you agree or disagree with the following statement: "I feel in control of what data on-device features can access."

Scale: 17
Min:Strongly disagreeMax:Strongly agree
Q21
Opinion Scale

How important is it to you to have a visible privacy dashboard on your device?

Scale: 17
Min:Not at all importantMax:Extremely important
Q22
Dropdown

What is the highest level of education you have completed?

  • Less than high school
  • High school or equivalent
  • Some college or vocational training
  • Associate degree (2-year)
  • Bachelor's degree (4-year)
  • Postgraduate degree
  • Prefer not to say
Q23
Long Text

In your own words, what does "on-device personalization" mean to you?

Q24
Ranking

Please rank the following from most important (1) to least important (5) when it comes to on-device personalization.

  1. Transparency about what data is used
  2. Speed and responsiveness of personalized features
  3. Accuracy and relevance of suggestions
  4. Assurance that data never leaves my device
  5. Easy controls to turn features on or off
Drag to rank
Q25
Multiple Choice

What is your current employment status?

  • Employed full-time
  • Employed part-time
  • Self-employed
  • Student
  • Homemaker
  • Unemployed and seeking work
  • Not seeking employment
  • Retired
  • Prefer not to say

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

  • Pairs multiple opinion-scale trust and agreement items (understanding of data use, perceived security, sense of control) so product and privacy teams get a multi-dimensional trust profile, not a single satisfaction score.
  • Uses ranking exercises that force respondents to trade off comfort across specific data types and priorities, surfacing real permission boundaries rather than abstract approval ratings.
  • Includes an adaptive AI follow-up interview that probes deeper into open-ended reasoning after the structured questions, catching nuance and edge cases a fixed-question form would miss.
  • Combines closed permission-preference and multiple-choice questions with open-text prompts on what felt intrusive or unclear, then rolls everything into an auto-generated report for privacy and product stakeholders.

SurveySparrow

New Product Launch Questionnaire Template | Product Survey Questions

This is a general market-research questionnaire for gauging reactions to a new product launch, not a privacy- or trust-specific instrument. It's a fielding-ready template but covers broad appeal/pricing/interest questions rather than data-handling comfort, permission models, or privacy dashboards. Useful as a generic launch-validation survey, not as a substitute for a dedicated on-device personalization trust study.

What it does well

  • Ready-to-deploy generic template for gauging early reactions to a new product or feature
  • Likely covers broad market-validation angles like interest, pricing, and appeal
  • Simple structured format that's fast to launch and analyze

Where it falls short

  • No privacy-, trust-, or permission-specific question set for personalization features
  • Static question flow with no adaptive AI follow-up to probe why users feel intrusive or unclear about a feature
  • No published methodology on automated response scoring or prompt transparency

Ready to launch?

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

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