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.
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
We'd like to understand how fair your most recent queue or hold experience felt. Please answer the following questions about that specific experience.
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
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
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.
Finally, we have a few optional questions about you to help us understand patterns across different groups.
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.
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)
Overall, how fair did that most recent queue or hold feel?
Rank the following factors by how acceptable you find them for determining queue order during high demand. Place the most acceptable at the top.
- Arrival time (first-come, first-served)
- Membership tier or loyalty status
- Past spend with the retailer
- Recovery from technical issues or disconnections
- Accessibility or disability-related needs
- Randomized order to deter bots
What is your age?
- 18–24
- 25–34
- 35–44
- 45–54
- 55–64
- 65+
- Prefer not to say
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
I understood why I was placed in the position I was in the queue.
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.
- First-come, first-served order
- Clear and transparent rules
- Accurate position updates
- Estimated wait time accuracy
- Control options (e.g., callback, pause, return)
- Accessibility accommodations
- Protections against bots and abuse
Which gender do you identify with?
- Man
- Woman
- Non-binary
- Prefer not to say
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
The estimated wait time I was given was accurate.
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
I felt the queue or hold treated all customers equally.
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
I felt the retailer valued my time during the wait.
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
How did that queue or hold experience affect your trust in the retailer?
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.
Frequently asked questions
What questions are in the “Retail Virtual Queue & Hold Fairness Survey” template?
The template includes 24 ready-to-use questions, starting with: “Welcome to this survey about your experiences with virtual queues and holds when shopping or contacting retailers. This…” · “Have you experienced a virtual queue or hold with a retailer in the last 3 months? (e.g., waiting in an online checkout…” · “We'd like to understand how fair your most recent queue or hold experience felt. Please answer the following questions a…”. The full set is previewed above, and every question is editable.
How long does this survey take to complete?
Respondents typically finish the 24 questions in about 11 minutes.
Can I customize this template?
Yes — every question, answer option, and the ordering is editable before you launch. You can add or remove questions, or ask the AI editor to rework the survey around your research goal.
Is this template free to use?
Yes. Open it in the editor and start customizing right away — no account required to try it, and the free plan covers launching your survey.
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 on similar topics.
Restaurant QR Code Menu Usability & Preference Survey
Measures diner experiences with QR code menus across usability, accessibility, and format preferences to inform restaurant digital menu strategy. Designed for adult diners who have encountered QR code menus in the past 3 months.
View templateWaitlist Fairness & Transparency Experience Survey
Measures customer perceptions of fairness, transparency, and wait-time accuracy across virtual and in-person restaurant and hospitality waitlists. Ideal for hospitality operators and CX researchers seeking actionable insights on queue management.
View templateDynamic Pricing Fairness Perceptions Survey
Measures consumer attitudes toward dynamic and surge pricing across rideshare, delivery, travel, and retail, identifying key fairness drivers, transparency preferences, and acceptable price thresholds to inform pricing strategy.
View templateGrocery Delivery Substitution Fairness & Satisfaction Survey
Measures customer perceptions of grocery delivery substitution fairness, communication preferences, and compensation expectations. Designed for grocery delivery services seeking to optimize substitution policies and improve customer satisfaction.
View templateChatbot-to-Agent Handoff Fairness & Trust Survey
Measures perceived fairness, transparency, and trust impact when customers encounter a chatbot before reaching a human agent. Designed for post-interaction feedback to diagnose friction in chatbot routing and escalation workflows.
View templateRemote Exam Fairness & Privacy Perceptions Survey
Measures student perceptions of fairness, privacy, and acceptability of proctoring practices in remote exams. Designed for higher-education institutions seeking to evaluate and improve remote assessment policies.
View template