GLP-1 Medication Impact on Grocery & Snack Purchases
Measures how GLP-1 medications (like Ozempic, Wegovy, or Zepbound) are reshaping household grocery and snack shopping — spending shifts, category cuts, and snack decision factors. Built for CPG and retail researchers, with an AI follow-up interview that reconstructs a real recent shopping trip instead of relying on general impressions.
Sample questions
A preview of what’s in the template. Every question is editable before you launch.
Which best describes your household's use of GLP-1 medications (such as Ozempic, Wegovy, Mounjaro, or Zepbound) for weight loss or diabetes management?
- I am currently using one
- I used one in the past but stopped
- Someone else in my household currently uses one
- No one in my household has used one
Compared to before this medication use began (or was noticed) in your household, how has your overall grocery spending changed?
For each category below, how has your household's buying changed?
- Salty snacks (chips, pretzels)
- Sweets and candy
- Baked goods (cookies, bread)
- Sugary beverages
- Frozen convenience meals
- +1 more
If you have 100 points representing your current monthly grocery budget, how would you distribute them across these categories today?
- Fresh produce
- Protein (meat, poultry, fish)
- Snacks & sweets
- Frozen or prepared meals
- Beverages (including alcohol)
When choosing snacks today, which of these factors matters most to you, and which matters least?
- Portion size
- Protein content
- Low sugar or low carb content
- Price
- Convenience (ready-to-eat)
- Brand familiarity
- Package or multipack count
- Ingredient quality
In the last 30 days, how has your frequency of grocery shopping trips changed compared to before this medication use began?
- Much less often
- Somewhat less often
- About the same
- Somewhat more often
- Much more often
How satisfied are you with the snack options currently available that fit smaller-appetite needs?
If the respondent or someone in their household is currently using a GLP-1 medication, reconstruct a specific recent grocery trip: which snacks or categories they picked up versus skipped, and how appetite or nausea shaped the decision. Probe any brand or format switching (e.g., single-serve instead of family-size, protein-forward instead of full-sugar) and what still tempts them despite reduced appetite. If no one in the household uses these medications, ask what changes, if any, they've noticed in their own household's shopping and treat the impact as minimal if none is reported.
Almost done — just a few background questions to help us compare results across household types. All are optional.
What is your age range?
- 18-24
- 25-34
- 35-44
- 45-54
- 55-64
- 65 or older
- Prefer not to say
What is your total annual household income?
- Under $50,000
- $50,000-$99,999
- $100,000-$149,999
- $150,000 or more
- Prefer not to say
How many people live in your household, including yourself?
- 1
- 2
- 3-4
- 5 or more
- Prefer not to say
Thank you for sharing these details! Your answers feed directly into research on how grocery and snack assortments should adapt to changing appetite and health trends. No individual responses are shared with any brand.
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.
Why this template
What this template is built to do — we found no directly comparable template from other survey tools to review.
What sets it apart
- Reconstructs a specific recent shopping trip through an AI follow-up interview instead of relying on generalized recall, giving CPG and retail researchers concrete behavioral detail tied to GLP-1 use
- Uses a matrix question to capture category-by-category buying shifts (e.g., snacks, produce, packaged foods) rather than a single blunt impact rating
- Includes a constant-sum budget allocation task so respondents show exactly how their 100-point monthly grocery budget has been redistributed, not just whether spending went up or down
- Combines a max-diff exercise on snack decision factors with satisfaction rating and shopping-frequency questions, then auto-generates a report — no manual tallying required
Ready to launch?
Open this template in the editor. Every part is yours to change before the first respondent sees it.