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Retail Virtual Queue & Hold Fairness Survey

Measures shopper perceptions of fairness across virtual queues and hold experiences in retail, capturing wait context, fairness judgments, policy preferences, behavioral responses, and trust impact to identify CX improvement opportunities.

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AI-Powered Questions

Intelligent follow-up questions based on responses

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Comprehensive insights and recommendations

Template Overview

24

Questions

AI-Powered

Smart Analysis

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This professionally designed survey template helps you gather valuable insights with intelligent question flow and automated analysis.

Sample Survey Items

Q1
Chat Message
Welcome to this survey about your experiences with virtual queues and holds when shopping or contacting retailers. This survey takes approximately 6–8 minutes to complete. 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. Your responses will be kept confidential, reported only in aggregate, and used for research purposes to improve customer experiences. By continuing, you agree to participate.
Q2
Multiple Choice
Have you experienced a virtual queue or hold with a retailer in the last 3 months? (e.g., waiting in an online checkout queue, being placed on hold for customer support, waiting for a store pickup slot, etc.)
  • Yes
  • No
Q3
Multiple Choice
In which of the following settings did you experience a virtual queue or hold? Select all that apply.
  • Online checkout during high demand
  • Customer support chat
  • Store pickup or appointment scheduling
  • Limited-release or product drop
  • Phone support hold
  • Other (please specify)
Q4
Dropdown
When was your most recent virtual queue or hold with a retailer?
  • Within the last 7 days
  • 8–30 days ago
  • 1–3 months ago
Q5
Dropdown
Approximately how long did you wait in that most recent queue or hold?
  • Less than 5 minutes
  • 5–10 minutes
  • 11–20 minutes
  • 21–30 minutes
  • 31–60 minutes
  • More than 60 minutes
  • I'm not sure
Q6
Chat Message
We'd like to understand how fair your most recent queue or hold experience felt. Please answer the following questions about that specific experience.
Q7
Opinion Scale
Overall, how fair did that most recent queue or hold feel?
Range: 1 7
Min: Very unfairMid: NeutralMax: Very fair
Q8
Opinion Scale
I understood why I was placed in the position I was in the queue.
Range: 1 7
Min: Strongly disagreeMid: NeutralMax: Strongly agree
Q9
Opinion Scale
The estimated wait time I was given was accurate.
Range: 1 7
Min: Strongly disagreeMid: NeutralMax: Strongly agree
Q10
Opinion Scale
I felt the queue or hold treated all customers equally.
Range: 1 7
Min: Strongly disagreeMid: NeutralMax: Strongly agree
Q11
Opinion Scale
I felt the retailer valued my time during the wait.
Range: 1 7
Min: Strongly disagreeMid: NeutralMax: Strongly agree
Q12
Opinion Scale
How did that queue or hold experience affect your trust in the retailer?
Range: 1 7
Min: Greatly decreased my trustMid: NeutralMax: Greatly increased my trust
Q13
Multiple Choice
Which of the following queue or hold policies feel fair to you when waits are long? Select all that apply.
  • Show estimated wait time
  • Show my exact position in line
  • Offer a callback instead of waiting on hold
  • Limit per-customer purchases
  • Invite windows or scheduled time slots
  • Cap queue length and temporarily close entry
  • Automatic timeout after inactivity
  • None of these feel fair
Q14
Ranking
Rank the following factors by how acceptable you find them for determining queue order during high demand. Place the most acceptable at the top.
Drag to order (top = most important)
  1. Arrival time (first-come, first-served)
  2. Membership tier or loyalty status
  3. Past spend with the retailer
  4. Recovery from technical issues or disconnections
  5. Accessibility or disability-related needs
  6. Randomized order to deter bots
Q15
Ranking
Rank the following aspects by how much they determine whether a queue or hold feels fair to you. Place the most important at the top.
Drag to order (top = most important)
  1. First-come, first-served order
  2. Clear and transparent rules
  3. Accurate position updates
  4. Estimated wait time accuracy
  5. Control options (e.g., callback, pause, return)
  6. Accessibility accommodations
  7. Protections against bots and abuse
Q16
Multiple Choice
In the last 3 months, how did you respond when faced with a long queue or hold? Select all that apply.
  • Waited and completed my task
  • Switched to a different retailer
  • Came back later
  • Abandoned the purchase or inquiry
  • Used multiple devices or browser tabs
  • Contacted support through another channel
  • Gave up immediately
Q17
AI Interview
Based on your responses throughout this survey, what would make virtual queues and holds feel more fair to you? Please share any additional thoughts, suggestions, or experiences.
AI InterviewLength: 2Personality: [Object Object]Mode: Fast
Reference questions: 5
Q18
Chat Message
Finally, we have a few optional questions about you to help us understand patterns across different groups.
Q19
Dropdown
What is your age?
  • 18–24
  • 25–34
  • 35–44
  • 45–54
  • 55–64
  • 65+
  • Prefer not to say
Q20
Multiple Choice
Which gender do you identify with?
  • Man
  • Woman
  • Non-binary
  • Prefer not to say
Q21
Dropdown
Which region best describes where you live?
  • North America
  • Latin America
  • Europe
  • Middle East / North Africa
  • Sub-Saharan Africa
  • Asia
  • Oceania
  • Prefer not to say
Q22
Dropdown
What is your highest level of education?
  • Some high school or less
  • High school diploma or equivalent
  • Some college or associate degree
  • Bachelor's degree
  • Postgraduate or professional degree
  • Prefer not to say
Q23
Dropdown
What is your current employment status?
  • Employed full-time
  • Employed part-time
  • Self-employed
  • Unemployed and seeking work
  • Not seeking work
  • Student
  • Retired
  • Homemaker / caregiver
  • Prefer not to say
Q24
Chat Message
Thank you for completing this survey. Your responses will help retailers design fairer, more transparent queue and hold experiences. Your answers are confidential and will be reported only in aggregate.

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