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Industry-Specific

Fast Food Visit Experience & Ordering Satisfaction Survey

Captures how customers actually experience a fast food visit — speed, accuracy, taste, value, and channel choice — plus which improvements would matter most and how customers think about pricing. An AI follow-up interview reconstructs exactly what happened on the respondent's most recent visit instead of relying on vague satisfaction scores. Built for restaurant operators, franchise groups, and QSR marketing teams.

Sample questions

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

14 questions · ~7 min
Q01
Message

Thanks for taking a few minutes to tell us about your fast food experiences! Your responses are completely confidential and anonymized. We're especially interested in your most recent visit — honest details help us the most. About 8 minutes.

Q02
Multiple ChoiceRequired

In the last 30 days, how many times have you ordered from a fast food restaurant?

  • Not at all
  • 1-2 times
  • 3-5 times
  • 6-10 times
  • More than 10 times
Q03
Multiple ChoiceRequired

How did you place your most recent fast food order?

  • Drive-thru
  • Ordered inside at the counter
  • Self-service kiosk
  • Mobile app
  • Third-party delivery app
  • Website (pickup or delivery)
Q04
Opinion ScaleRequired

Overall, how satisfied were you with your most recent fast food visit?

Scale: 17
Min:Very dissatisfiedMax:Very satisfied
Q05
Opinion ScaleRequired

How likely are you to recommend this restaurant to a friend or colleague?

Scale: 010
Min:Not at all likelyMax:Extremely likely
Q06
MatrixRequired

Thinking about that same visit, how would you rate each of the following?

6 rows × 5 columns
  • Speed of service
  • Order accuracy
  • Food taste and quality
  • Value for the price
  • Cleanliness of the restaurant
  • +1 more
Columns: Poor · Below average · Average · Good · Excellent
Q07
Best–Worst Trade-off (MaxDiff)

Which of the following changes would do the most — and least — to improve your fast food experience?

  • Faster order fulfillment
  • Getting my order right every time
  • Lower prices
  • Healthier menu options
  • Cleaner dining areas
  • More menu variety
  • Friendlier staff
  • A better mobile app or ordering experience
  • More consistent food quality
Pick best & worst per setBest:Would improve my experience the mostWorst:Would improve my experience the least
Q08
Price Sensitivity (Van Westendorp)

Now think about a typical combo meal — a main item, a side, and a drink. (Template note: replace 'combo meal' with a specific menu item you want to price-test before launching.)

  • At what price would this combo meal be so inexpensive that you'd question the quality of the food or ingredients?
  • At what price would this combo meal start to feel like a bargain — a great deal for the money?
  • At what price would this combo meal start to feel expensive, though you'd still consider buying it?
  • At what price would this combo meal be so expensive that you would not consider buying it at all?
Q09
AI Interview

Reconstruct exactly what happened on the respondent's most recent fast food visit: which restaurant and channel they used, whether the order came out correct and how fast, and what specifically drove their satisfaction rating. If they rated the visit low or flagged an accuracy or speed problem, probe what went wrong, whether staff addressed it, and whether it would change their future visit frequency.

Q10
Message

Just a few quick optional questions about you, then we're done.

Q11
Multiple Choice

Which age range do you fall into?

  • Under 18
  • 18-24
  • 25-34
  • 35-44
  • 45-54
  • 55-64
  • 65 or older
  • Prefer not to say
Q12
Multiple Choice

How do you describe your gender?

  • Woman
  • Man
  • Non-binary
  • Prefer to self-describe
  • Prefer not to say
Q13
Multiple Choice

What is your approximate annual household income?

  • Under $25,000
  • $25,000-$49,999
  • $50,000-$74,999
  • $75,000-$99,999
  • $100,000-$149,999
  • $150,000 or more
  • Prefer not to say
Q14
Message

That's everything — thank you! Your answers will feed directly into a report on where we can speed up service, fix order accuracy, and prioritize the changes customers care about most.

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

  • Reconstructs the respondent's actual most recent visit through an AI follow-up interview instead of relying on a single satisfaction score
  • Captures channel choice (drive-thru, app, in-store, delivery) alongside order frequency to segment behavior, not just overall sentiment
  • Uses a matrix question to rate speed, accuracy, taste, and value separately for that same visit, plus a max-diff exercise to rank which improvements would matter most
  • Includes a Van Westendorp pricing exercise on a typical combo meal so operators get real price-sensitivity data, not just a satisfaction number

QuestionPro

Food survey questions | Food-related survey questions & template

This is a broad food-survey question bank/guide page covering food-related topics generally, rather than a dedicated, fielding-ready fast food ordering experience template. It's useful as a starting reference for sample question wording, but it doesn't focus specifically on order channel, visit accuracy, or combo-meal pricing the way a purpose-built QSR template would. As a category page it also mixes topics, so an operator would need to hand-pick and rebuild relevant questions.

What it does well

  • Backed by an established survey platform with standard logic, branching, and reporting tools
  • Offers a wide question bank spanning multiple food-related survey topics, which can speed up initial drafting
  • Likely supports common question types (rating scales, multiple choice) out of the box

Where it falls short

  • Static question list with no adaptive AI follow-up to reconstruct what actually happened on a specific visit
  • No automated per-response quality scoring or transparent AI prompt methodology
  • Presented as a general food-survey guide/category rather than a ready-to-field fast food ordering experience survey

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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