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Industry-Specific

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.

Sample questions

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

24 questions · ~11 min
Q01
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.

Q02
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
Q03
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.

Q04
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
Q05
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
Q06
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.

Q07
Message

Finally, we have a few optional questions about you to help us understand patterns across different groups.

Q08
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.

Q09
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)
Q10
Opinion Scale

Overall, how fair did that most recent queue or hold feel?

Scale: 17
Min:Very unfairMax:Very fair
Q11
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.

  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
Drag to rank
Q12
Dropdown

What is your age?

  • 18–24
  • 25–34
  • 35–44
  • 45–54
  • 55–64
  • 65+
  • Prefer not to say
Q13
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
Q14
Opinion Scale

I understood why I was placed in the position I was in the queue.

Scale: 17
Min:Strongly disagreeMax:Strongly agree
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.

  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
Drag to rank
Q16
Multiple Choice

Which gender do you identify with?

  • Man
  • Woman
  • Non-binary
  • Prefer not to say
Q17
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
Q18
Opinion Scale

The estimated wait time I was given was accurate.

Scale: 17
Min:Strongly disagreeMax:Strongly agree
Q19
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
Q20
Opinion Scale

I felt the queue or hold treated all customers equally.

Scale: 17
Min:Strongly disagreeMax:Strongly agree
Q21
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
Q22
Opinion Scale

I felt the retailer valued my time during the wait.

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

How did that queue or hold experience affect your trust in the retailer?

Scale: 17
Min:Greatly decreased my trustMax:Greatly increased my trust

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.

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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