Q01
Message
All templates
Restaurant Menu And Portion Preferences For GLP-1 Users
Explores how people taking GLP-1 medications (Ozempic, Wegovy, Mounjaro, Zepbound, etc.) actually order, eat, and evaluate restaurant meals now that their appetite has changed. Combines portion satisfaction, trade-off prioritization, and an AI follow-up interview that reconstructs a real recent meal to surface concrete menu and pricing fixes. Built for restaurant chains, menu R&D teams, and food-service researchers.
Sample questions
A preview of what’s in the template. Every question is editable before you launch.
13 questions · ~7 min
Q02
Multiple Choice
How long have you been taking a GLP-1 medication (for weight management or diabetes)?
- Less than 1 month
- 1-3 months
- 4-6 months
- 7-12 months
- More than 1 year
- Prefer not to say
Q03
Multiple ChoiceRequired
Compared to before you started the medication, how often do you eat at sit-down or fast-casual restaurants now?
- Much less often
- Somewhat less often
- About the same
- Somewhat more often
- Much more often
Q04
Rating ScaleRequired
How satisfied are you with the portion sizes offered at most restaurants you visit?
Range: 1 – 5
Min:Very dissatisfiedMax:Very satisfied
Q05
MatrixRequired
How much do you agree with each statement about eating at restaurants since starting your medication?
5 rows × 5 columns
- I often ask for a to-go box before I start eating.
- I skip appetizers or sides because the main portion is already too much.
- I look for calorie or protein information before ordering.
- I feel judged or questioned when I order less food than expected.
- I would order out more often if half-size portions were priced at roughly half the cost.
Columns: Strongly disagree · Disagree · Neutral · Agree · Strongly agree
Q06
Best–Worst Trade-off (MaxDiff)Required
Which of the following menu changes would most improve your experience dining out?
- Half-portion sizes at proportionally lower prices
- More protein-forward entrees (fish, chicken, tofu, etc.)
- Smaller or lighter appetizer options
- Nutrition information (calories, protein) listed on the menu
- Default option to box half the meal to go
- More vegetable-forward or lower-carb sides
- Shareable or small-plate formats across the whole menu
- Lower-sugar desserts available in smaller sizes
Pick best & worst per setBest:Would improve my experience the mostWorst:Would improve my experience the least
Q07
Point AllocationRequired
If a restaurant chain asked you to help prioritize its next menu redesign, how would you split 100 points across these investments?
- Smaller portion options
- Lower prices for smaller portions
- Healthier ingredient choices
- More variety within each portion size
- Clear nutrition labeling
- Faster service for lighter meals
Allocate 100 points
Q08
Opinion ScaleRequired
How likely are you to choose a restaurant specifically because it offers half-portion or 'lighter' menu options?
Scale: 0 – 10
Min:Not at all likelyMax:Extremely likely
Q09
AI Interview
Reconstruct the respondent's most recent restaurant meal since starting their GLP-1 medication: what they ordered, how much they actually ate versus what arrived, and what happened to the leftovers. Probe any specific moment where portion size, pricing, or menu design didn't fit their appetite, and ask what exact change would have made that meal work better. If they say portions haven't changed much for them, ask what they'd still want restaurants to offer for people in their situation.
Q10
Multiple Choice
Which age range do you fall into?
- Under 25
- 25-34
- 35-44
- 45-54
- 55-64
- 65 or older
- Prefer not to say
Q11
Multiple Choice
How do you describe your gender?
- Woman
- Man
- Non-binary
- Prefer not to say
Q12
Multiple Choice
What is your annual household income?
- Under $50,000
- $50,000-$99,999
- $100,000-$149,999
- $150,000 or more
- Prefer not to say
Q13
Message
Thank you! Your answers will help restaurants and menu designers build portion sizes, pricing, and options that better fit changing appetites like yours.
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 a rating and matrix block that quantify portion satisfaction and post-medication attitude shifts, then a max-diff and constant-sum exercise that force respondents to trade off and prioritize specific menu changes instead of just rating them
- Pairs those quantitative trade-offs with an AI follow-up interview that reconstructs a respondent's actual most recent restaurant meal, turning vague complaints into concrete, orderable menu and pricing fixes
- Purpose-built for the GLP-1 population specifically (medication tenure, dining-frequency shift, half-portion likelihood) rather than a generic diner satisfaction survey
- Standard demographic screening (age, gender, household income) lets restaurant chains and menu R&D teams segment findings by respondent profile
Jotform
50+ Restaurant Evaluation FormsThis is a category page listing 50+ generic restaurant evaluation form templates rather than a single fielding-ready survey. It covers general dine-in satisfaction and service quality but has no content aimed at GLP-1 users or appetite-driven ordering behavior.
What it does well
- Large library of ready-made form layouts to start from
- Familiar drag-and-drop form builder for quick customization
- Covers broad restaurant evaluation use cases (service, cleanliness, food quality)
Where it falls short
- Static form fields only — no adaptive AI follow-up questions to probe individual answers
- No mechanism to reconstruct a specific recent meal or surface concrete menu/pricing fixes
- No published scoring methodology or automated report generation tied to response quality
QuestionPro
Food survey questions | Food-related survey questions & templateA fast-food/restaurant survey template with a bank of food-related questions, aimed at general dining feedback rather than the GLP-1 or medication-driven appetite-change population. Useful as a generic starting question set but not tailored to portion-size trade-offs for this audience.
What it does well
- Established survey platform with broad question-library support
- Covers general fast-food ordering and satisfaction topics
- Supports standard survey logic and reporting features
Where it falls short
- No adaptive AI interview to dig into an individual's actual recent meal
- No built-in trade-off/prioritization exercise for menu redesign decisions
- No GLP-1-specific framing (medication tenure, appetite change, half-portion preference)
SurveyMonkey
Restaurant Feedback Survey Template & QuestionsA standard restaurant feedback template covering service, food quality, and overall satisfaction — solid for general dine-in feedback but not designed around appetite-changed diners or portion-size trade-off decisions. It's a static question set rather than an interview-style probe.
What it does well
- Widely used, easy-to-deploy survey builder
- Good for broad satisfaction tracking across many restaurant visits
- Simple reporting dashboards for aggregate results
Where it falls short
- Fixed questions with no adaptive follow-up to reconstruct a specific meal
- No max-diff or constant-sum style prioritization for menu redesign trade-offs
- No focus on GLP-1 medication context or portion-satisfaction shifts over time
Ready to launch?
Open this template in the editor. Every part is yours to change before the first respondent sees it.