Dark Pattern Acceptability & Transparency Trust Survey
Measures consumer reactions to common dark-pattern design tactics and transparency preferences, providing actionable data on trust drivers for UX and product teams.
Sample questions
A preview of what’s in the template. Every question is editable before you launch.
In the past 30 days, have you used any websites or apps to shop, book, or start or modify a subscription?
- Yes
- No
The following scenarios describe common design practices you may encounter online. Please read each one carefully and rate how acceptable you find it.
Which of the following transparency features matter most to you when using websites or apps? Select all that apply.
- Clear total price shown upfront
- Easy cancellation in one or two steps
- Plain-language data use summary
- Consent toggles set to off by default
- No auto-added items in cart
- Prominent labels for ads or sponsored content
- Change log for pricing or policy updates
- Other (please specify in the next question)
Describe a recent time when a website or app influenced your choice in a way you found concerning or unclear. What happened, and how did you respond?
What is your age group?
- 18–24
- 25–34
- 35–44
- 45–54
- 55–64
- 65+
- Prefer not to say
Thank you for your time — your input helps inform the design of clearer, more trustworthy online experiences. You may now close this survey.
Which of the following types of websites or apps have you used in the past 30 days? Select all that apply.
- Retail or marketplace websites
- Mobile shopping apps
- Food delivery apps
- Travel or ticket booking sites
- Streaming or media subscriptions
- Social media shops
- Utilities, bill pay, or banking apps
- Other
Imagine you are shopping online. A product page shows a 10-minute countdown timer, after which a discount will no longer be available. How acceptable do you find this design practice?
If you selected 'Other' above, please describe the transparency feature you value.
Based on your responses in this survey, please share any additional thoughts or feelings about persuasive design practices or transparency in your online experiences. Our AI moderator may ask a follow-up question to better understand your perspective.
What is your gender?
- Woman
- Man
- Non-binary
- Prefer to self-describe
- Prefer not to say
In the past 30 days, how often did you encounter a website or app design that felt misleading or manipulative (e.g., hidden fees, hard-to-cancel subscriptions, urgency messages)?
Imagine you are completing an online purchase. Additional fees (e.g., service charges or handling fees) appear for the first time on the final checkout step. How acceptable do you find this design practice?
To what extent do clear, transparent practices influence your trust in a brand?
If you selected 'Prefer to self-describe' above, please specify your gender.
Imagine you are about to check out online. An add-on product (e.g., extended warranty or accessory) has been pre-selected in your cart, increasing the total unless you remove it. How acceptable do you find this design practice?
When choosing which brand or website to purchase from, rank the following factors from most important (1) to least important (5).
- Price and value for money
- Product or service quality
- Ease of use
- Transparency and clarity of information
- Brand reputation and trustworthiness
In which region do you currently live?
- North America
- Europe
- Latin America
- Asia
- Africa
- Oceania
- Middle East
- Prefer not to say
Thinking about the three scenarios you just rated, to what extent would encountering these practices reduce your likelihood of completing a purchase?
What is the highest level of education you have completed?
- Less than high school
- High school or equivalent
- Some college or Associate degree
- Bachelor's degree
- Postgraduate degree
- Prefer not to say
Please rank the following design practices from most concerning (1) to least concerning (6).
- Fees shown only at final checkout
- Hard-to-find unsubscribe or cancel steps
- Countdown timers or urgent messaging
- Low-stock or scarcity claims
- Pre-selected add-ons
- Ambiguous or unclear buttons
What is your current employment status?
- Employed full-time
- Employed part-time
- Self-employed
- Unemployed and looking for work
- Student
- Retired
- Homemaker or caregiver
- 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
- Includes three concrete dark-pattern scenarios (countdown timers, hidden fees, forced add-on defaults) rated on opinion scales, giving quantifiable acceptability data rather than generic satisfaction questions
- Includes ranking exercises for both 'most concerning design practices' and 'purchase-decision factors', producing prioritized trust drivers instead of flat averages
- Follows up automatically with an AI-moderated interview that probes the reasoning behind each respondent's ratings, surfacing the 'why' behind the scores
- Captures self-described transparency preferences via open-text plus full demographic segmentation (age, region, education, employment) for cross-cut analysis
SurveySparrow
Product Design Survey Questionnaire | For Market ResearchThis is a fielding-ready generic product design/UX feedback questionnaire aimed at market research teams, not a dark-pattern or transparency-trust specific instrument. It's a reasonable adjacent template for product teams gathering general design feedback, but it doesn't address manipulative-design acceptability or trust-in-transparency questions directly.
What it does well
- Ready-to-use, fieldable template built for product/UX design feedback
- SurveySparrow's conversational survey format may improve completion rates
- Positioned specifically for market research use by product teams
Where it falls short
- Static question set with no adaptive AI follow-up to probe why respondents rate a design a certain way
- No scenario-based dark-pattern testing (e.g., countdown timers, hidden fees, forced add-ons)
- No automated per-response quality scoring or published prompt-level methodology
Ready to launch?
Open this template in the editor. Every part is yours to change before the first respondent sees it.
Related templates
More studies from the same category.
Cross-Border Data Transfer Trust Assessment (GDPR)
Measures customer trust, comfort, and consent preferences regarding international personal data transfers. Use this instrument to identify key drivers of acceptance, benchmark transparency satisfaction, and inform GDPR-aligned communication strategies.
View templateCookie Paywall Fairness & Consent Alternatives Survey
Measures consumer perceptions of fairness, transparency, and trust in cookie paywalls versus privacy-friendly content-access alternatives. Designed for UX researchers, privacy professionals, and publishers seeking GDPR-aligned consent insights.
View templateCookie Consent Banner Fatigue & Control Preferences
Measures user fatigue with GDPR cookie consent banners and preferences for privacy control interfaces. Designed for UX researchers and compliance teams seeking to improve consent experiences based on real browsing behavior.
View templateAI Contract Review & Redlining Adoption Survey
Measures legal professionals' adoption levels, satisfaction, barriers, and safeguard requirements for AI-assisted contract review and redlining. Designed for legal operations, in-house teams, and law firm practitioners.
View templateGDPR Consent Copy & Preference Center Usability Study
A UX research instrument that evaluates clarity, trust, and usability of GDPR consent messages and privacy preference center controls through A/B stimulus comparison and behavioral preference measures.
View templateVendor Security and Risk Assessment Questionnaire
Assesses a vendor's security controls, certifications, data handling, and incident history for procurement, security, and compliance teams running third-party risk reviews. An AI follow-up interview digs into the vendor's single most significant unresolved risk instead of accepting a checklist of certifications at face value.
View template