Q01
Message
All templatesSales & Revenue
Retail Shopper Demographics & Buying Habits Survey
Profiles who your retail customers are and how they actually shop — channel mix, spending split, satisfaction, and the store features that matter most — then uses an AI follow-up to uncover the real reason behind their most recent shopping decision. Built for retail and e-commerce teams segmenting customers for marketing, merchandising, and store experience decisions.
Sample questions
A preview of what’s in the template. Every question is editable before you launch.
15 questions · ~8 min
Q02
Multiple ChoiceRequired
In the last 30 days, how many times did you shop with us — in a store, online, or through our app?
- I didn't shop with us
- 1-2 times
- 3-5 times
- 6-10 times
- More than 10 times
Q03
Multiple ChoiceRequired
Which best describes how you usually shop with us?
- Almost always in-store
- Almost always online or through the app
- A mix of both, mostly in-store
- A mix of both, mostly online/app
- About equally split between in-store and online
Q04
Point Allocation
Thinking about your total spending with us over the last 3 months, how would you split it across these channels? (Points should add up to 100.)
- In-store
- Website (desktop or mobile browser)
- Mobile app
- Phone or mail order
- Third-party marketplace (Replace with your relevant marketplace, e.g., Amazon)
Allocate 100 points
Q05
Opinion ScaleRequired
Overall, how satisfied were you with your most recent shopping experience with us?
Scale: 1 – 7
Min:Very dissatisfiedMax:Very satisfied
Q06
MatrixRequired
How much do you agree with each statement about your recent shopping experience?
5 rows × 5 columns
- Staff were helpful and knowledgeable
- Checkout was quick and easy
- The products I wanted were in stock
- The store or website was easy to navigate
- Prices felt fair for the value
Columns: Strongly disagree · Disagree · Neutral · Agree · Strongly agree
Q07
Best–Worst Trade-off (MaxDiff)Required
For each set, choose which factor matters most and which matters least in your decision to shop with us.
- Low prices
- Product selection and variety
- Ease of shopping in-store or online
- Helpful staff
- Fast checkout or delivery
- Easy returns
- Loyalty or rewards program
- Product quality
Pick best & worst per setBest:Matters mostWorst:Matters least
Q08
AI Interview
Reference the respondent's satisfaction rating and channel preference. If satisfaction was low (1-3) or they mostly shop online, probe specifically what went wrong or what keeps them from visiting a store — a bad experience, distance, price, or lack of selection. If satisfaction was high, ask what single moment or interaction made them choose to keep shopping here instead of a competitor. Always ask them to name a specific store or retailer they compare us to and why.
Q09
Opinion ScaleRequired
How likely are you to recommend shopping with us to a friend or family member?
Scale: 0 – 10
Min:Not at all likelyMax:Extremely likely
Q10
Message
Last, a few quick questions about you — these help us understand who's shopping with us. All of these are optional.
Q11
Multiple Choice
What is your age range?
- Under 18
- 18-24
- 25-34
- 35-44
- 45-54
- 55-64
- 65 or older
- Prefer not to say
Q12
Multiple Choice
What is your gender?
- Woman
- Man
- Non-binary
- Prefer not to say
Q13
Multiple Choice
What is your total 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
Dropdown
Which region do you live in? (Template note: replace this list with your own regions or countries before launching.)
- Northeast
- Midwest
- South
- West
- Outside the listed regions
- Prefer not to say
Q15
Message
Thank you for sharing your shopping habits with us! Your answers are combined with others in aggregate to guide our retail team's decisions on pricing, store experience, and product selection.
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
- Goes beyond static profiling by using an AI follow-up interview that references the respondent's own satisfaction rating and channel preference to probe the real reason behind their most recent shopping decision
- Combines channel usage, spend split (constant sum), satisfaction, agreement statements (matrix), and a max-diff exercise to rank which store factors actually drive decisions — not just surface-level demographics
- Captures standard segmentation variables (age, gender, income, region) alongside behavioral and attitudinal data, so retail/e-commerce teams can build usable customer segments in one flow
- Auto-generated reporting and transparent AI prompts mean teams can see exactly what the AI asked and why, unlike static forms that only report top-line percentages
QuestionPro
Demographic and Retail Shopping Survey TemplateA ready-to-field template covering shopper demographics and retail shopping behavior, closely comparable in scope to our template. It's built on QuestionPro's standard survey engine, so it's strong for structured questioning but not designed for conversational follow-up. Good starting point for teams that just need a static demographic + shopping-habit questionnaire.
What it does well
- Purpose-built for retail demographic and shopping behavior data collection
- Backed by a mature survey platform with broad question-type support and reporting
- Likely includes standard demographic breakouts (age, income, region) common to this template category
Where it falls short
- No adaptive AI follow-up — cannot probe why a respondent gave a particular satisfaction or channel answer
- No voice AI interview option or guided screen-share tasks
- No indication of published prompt-level methodology or automated per-response quality scoring
SurveyMonkey
U.S. Demographics Survey TemplateThis is a general-purpose U.S. demographics template rather than a retail-shopping-specific survey, so it covers age/income/region-type questions but not channel mix, spend split, or in-store satisfaction. Useful only as a demographics module, not as a full shopper behavior instrument. Teams would need to build the retail-specific questions themselves.
What it does well
- Standardized, well-tested demographic question set applicable across industries
- Easy to deploy quickly via a widely used survey platform
- Likely benefits from SurveyMonkey's broad distribution and panel options
Where it falls short
- Not retail-specific — no channel mix, spend allocation, or shopping satisfaction questions
- Static question format with no adaptive AI follow-up to explore reasons behind answers
- No voice AI interview or guided task capability
SurveySparrow
Retail Store Evaluation Survey TemplateFocused on evaluating the in-store experience (staff, layout, service) rather than shopper demographics or channel/spend behavior, so it overlaps only partially with our template's scope. It's a fielding-ready form for store experience feedback but doesn't build customer segments or dig into purchase-decision reasoning. Best suited for operational store feedback rather than marketing segmentation.
What it does well
- Targeted specifically at retail store experience evaluation
- Conversational-style survey UI that SurveySparrow is known for
- Likely includes ratings on staff, cleanliness, and layout relevant to store operations
Where it falls short
- No shopper demographic or segmentation questions (age, income, region)
- No adaptive AI interview to uncover the underlying reason for a shopping decision
- No transparent prompt methodology or automated quality scoring of open responses
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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