Q01
Message
All templatesIndustry-Specific
In-Store Shopper Trip and Checkout Experience Survey
Captures what shoppers came to buy, how they navigated the store, what they did when an item was missing, and how checkout felt — with an AI follow-up that digs into the real reasoning behind substitution choices and navigation friction. Built for retail insights and category management teams.
Sample questions
A preview of what’s in the template. Every question is editable before you launch.
14 questions · ~7 min
Q02
Multiple ChoiceRequired
In the last 30 days, about how many times have you shopped at this store?
- This was my first visit
- 1-2 times
- 3-5 times
- 6-10 times
- More than 10 times
Q03
Multiple ChoiceRequired
What best describes the main reason for today's trip?
- Big weekly/monthly stock-up
- Quick top-up trip (a few items)
- Specific errand (one or two items)
- Fill-in for a meal or event
- Browsing / no specific plan
Q04
Multiple ChoiceRequired
How much of today's shopping did you plan in advance (list, app, or in your head) versus decide on in the store?
- Entirely planned in advance
- Mostly planned, a few extras
- About half and half
- Mostly decided in-store
- Entirely decided in-store
Q05
Multiple Choice
How did you find your way to the items you needed today? Select all that apply.
- Store layout memory from past visits
- In-store signage or aisle markers
- Store map or directory
- Store app or website
- Asked a store associate
- Just wandered until I found it
Q06
Rating ScaleRequired
Overall today, how easy was it to find the items on your list?
Range: 1 – 5
Min:Very difficultMax:Very easy
Q07
Multiple Choice
Thinking about the last time an item you wanted was out of stock here, what did you do?
- Bought a different brand or size in the same category
- Bought the same brand at a different size/pack
- Skipped the item entirely
- Went to a different store to get it
- Ordered it online instead
- Asked a staff member to check the back or another location
- This hasn't happened to me recently
Q08
MatrixRequired
Thinking about checkout today, how much do you agree with each statement?
5 rows × 5 columns
- The wait time to check out was reasonable
- Staff were friendly and helpful at checkout
- The self-checkout or scanning process was easy to use
- I had the payment method I wanted to use
- The checkout area felt organized and not crowded
Columns: Strongly disagree · Disagree · Neutral · Agree · Strongly agree
Q09
Opinion ScaleRequired
How likely are you to recommend this store to a friend or family member, based on today's visit?
Scale: 0 – 10
Min:Not at all likelyMax:Extremely likely
Q10
AI Interview
Probe the specific moment of friction in this shopper's trip: if they described a substitution or an item they couldn't find, reconstruct exactly what happened — what they were looking for, what alternative (if any) they chose, and whether they'd have bought more if it had been in stock or easier to locate. If navigation involved wandering or asking staff, dig into what signage or layout change would have prevented that. If everything went smoothly, ask what almost went wrong or what would make their next trip faster.
Q11
Long Text
Anything else about today's trip — good or bad — you'd want the store to know?
Q12
Multiple Choice
Which age range do you fall into?
- Under 18
- 18-24
- 25-34
- 35-44
- 45-54
- 55-64
- 65+
- Prefer not to say
Q13
Multiple Choice
How do you describe your gender?
- Woman
- Man
- Non-binary
- Prefer to self-describe
- Prefer not to say
Q14
Message
Thank you for sharing your trip with us! Your answers feed directly into decisions about store layout, stocking, and checkout — helping make your next visit smoother.
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
- Captures the full trip arc — trip purpose, planned vs. unplanned shopping, in-store navigation, and checkout — in one flow rather than a generic satisfaction survey
- Includes a dedicated multiple-choice question on what shoppers actually did the last time an item was out of stock, giving structured substitution behavior data before the AI probe
- Uses an AI follow-up interview step to probe the specific moment of friction a shopper described, digging into the real reasoning behind substitution choices and navigation friction instead of stopping at a rating
- Pairs a matrix on checkout agreement statements with an opinion-scale recommend question and an open open-text, so quantifiable and open-ended feedback both feed the auto-generated report
SurveyMonkey
Shopper Insights Survey TemplateA fielding-ready static template covering general shopper insights, likely with standard question types like ratings and multiple choice. It's a reasonable starting point for retail feedback but appears built as a fixed questionnaire rather than one that adapts per respondent. Good for benchmarking against a broad question bank, less suited to digging into individual shopper reasoning.
What it does well
- Backed by a widely-used, established survey platform with broad template library
- Likely quick to deploy for general shopper insight collection
- Familiar interface for teams already using SurveyMonkey
Where it falls short
- No adaptive AI follow-up — questions are static and fixed at design time, so unexpected shopper friction can't be probed further
- No indication of automated per-response quality scoring or transparent prompt methodology
- No voice AI interview or guided screen-share task option for deeper behavioral capture
SurveySparrow
Shopper Insights Survey Template | Understand Buyer BehaviorA conversational-style template aimed at understanding buyer behavior, positioned as fielding-ready for retail teams. It likely offers a more chat-like respondent experience than a plain form, but the questions themselves appear pre-set rather than dynamically generated from prior answers. No mention of AI-driven follow-up probing or automated scoring.
What it does well
- Conversational survey format may improve completion rates versus a traditional grid form
- Framed specifically around buyer behavior, showing retail-focused intent
- Likely easy to customize branding and question wording for a specific store
Where it falls short
- No adaptive AI interview that probes the specific reasoning behind an individual shopper's answers
- No published methodology or transparent prompt logic behind how questions are asked
- No automated quality scoring of open-ended responses or auto-generated analytical report
Frequently asked questions
What questions are in the “In-Store Shopper Trip and Checkout Experience Survey” template?
The template includes 14 ready-to-use questions, starting with: “Thanks for shopping with us today! We'd love to hear about your visit — what you came for, how easy it was to find thing…” · “In the last 30 days, about how many times have you shopped at this store?” · “What best describes the main reason for today's trip?”. The full set is previewed above, and every question is editable.
How long does this survey take to complete?
Respondents typically finish the 14 questions in about 7 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.
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