Mall Shopping Behavior & Purchase Habits Survey
Explores how often people visit the mall, what they buy, how they allocate spend across categories, and what drives their choice of retail destination. Built for mall operators, retail marketers, and tenant-mix planners; the AI follow-up interview reconstructs the real story behind a shopper's most recent purchase decision, including near-misses and price hesitation that closed questions miss.
Sample questions
A preview of what’s in the template. Every question is editable before you launch.
In the last 3 months, how often have you visited a physical mall?
- Almost daily
- A few times a week
- About once a week
- A few times a month
- Once a month or less
- This was my first visit in months
Thinking about your most recent mall visit, what best describes your main purpose?
- Buying something specific I needed
- Browsing without a specific purchase in mind
- Meeting friends or family
- Eating at a restaurant or food court
- Watching a movie or other entertainment activity
- Returning or exchanging an item
Thinking about a typical month, how do you split your mall spending across these categories? Please allocate 100 points based on where your money actually goes.
- Clothing & apparel
- Footwear
- Electronics & gadgets
- Food & dining
- Personal care & beauty
- Entertainment (movies, arcade, etc.)
- Other
When deciding which mall to shop at, some things matter more than others. For each set, tell us which factor matters most and which matters least to you.
- Location convenience
- Parking availability
- Variety of stores
- Prices and deals
- Food and dining options
- Store atmosphere and ambiance
- Special events or promotions
- Overall safety and cleanliness
How much do you agree with each statement about the mall you visit most often?
- It has a good variety of stores
- Prices are reasonable for what I get
- It is clean and well-maintained
- Store staff are helpful when I need them
- It's a pleasant place to spend time, not just shop
How likely are you to recommend this mall to a friend or family member looking for a place to shop?
Reconstruct the respondent's most recent mall purchase decision: what they bought or almost bought, what nearly stopped them (price, not finding the right size or item, long lines, etc.), and what would have made them spend more. If they said their main purpose was 'just browsing,' probe what would have converted that visit into a purchase. Anchor follow-ups on their recommendation-likelihood answer if it was notably low or high.
What payment method do you use most often for mall purchases?
- Credit or debit card
- Mobile payment (Apple Pay, Google Pay, etc.)
- Cash
- Buy now, pay later service
- Store credit card or loyalty account
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
How do you describe your gender?
- Woman
- Man
- Non-binary
- Prefer to self-describe
- Prefer not to say
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
All done — thank you! Your answers, along with everyone else's, will be combined into a report on mall shopping habits used to guide store mix, pricing, and mall experience decisions. No individual responses are shared.
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 an AI follow-up interview that reconstructs the shopper's actual most recent purchase decision, surfacing near-misses and price hesitation that closed questions can't capture
- Uses a constant-sum question to get precise spend-allocation percentages across mall categories rather than vague ranking
- Combines a MaxDiff exercise and matrix agreement scale to rigorously prioritize what drives mall choice and satisfaction with the primary mall
- Pairs quantitative screening (visit frequency, purpose, NPS-style recommend likelihood, demographics) with automated quality scoring and an auto-generated report for mall operators and tenant-mix planners
QuestionPro
Mall purchase habits survey questions + sample questionnaire templateThis is a direct topical match: a ready-to-use questionnaire covering mall visit frequency, purpose, and purchase habits. It's a static template of pre-written closed questions rather than an adaptive interview, so it works well as a quick-start question bank but relies on the researcher to interpret open-ended nuance manually.
What it does well
- Purpose-built sample questionnaire specifically for mall/retail purchase habits, so questions are pre-vetted for this exact use case
- Likely offers customizable, fielding-ready questions within QuestionPro's established survey platform
- Backed by a large survey template library and platform with broad distribution options
Where it falls short
- No adaptive AI follow-up interview to probe why a shopper chose one purchase over another or reconstruct near-miss decisions
- No indication of automated per-response quality scoring
- No transparent prompt/methodology disclosure since it's a fixed question list, not an AI-driven interview
Frequently asked questions
What questions are in the “Mall Shopping Behavior & Purchase Habits Survey” template?
The template includes 13 ready-to-use questions, starting with: “Thanks for taking a few minutes to share how you shop at the mall! This helps retailers and mall operators understand re…” · “In the last 3 months, how often have you visited a physical mall?” · “Thinking about your most recent mall visit, what best describes your main purpose?”. The full set is previewed above, and every question is editable.
How long does this survey take to complete?
Respondents typically finish the 13 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.
Related templates
More studies on similar topics.
Market Segmentation & Customer Needs Discovery Survey
Groups your customers into meaningful segments by combining behavioral usage patterns, need-based attitudes, purchase-driver trade-offs, and demographics. Built for marketers and researchers building or refreshing a segmentation model. The AI follow-up interview digs into the 'why' behind each respondent's top purchase driver so segments are grounded in real reasoning, not just survey scores.
View templateGeneral Shopping Behavior & Demographics Survey
Maps how, where, and why people shop — channel mix, category spend, decision drivers, and core demographics — with an AI follow-up interview that reconstructs a recent real purchase decision instead of relying on stated preferences. Built for retail, e-commerce, and market-sizing teams profiling a customer base.
View templateSupermarket Shopping Attitudes and Habits Survey
Captures how shoppers choose, evaluate, and switch between grocery stores and channels — price sensitivity, loyalty behavior, and channel mix — for retail and CPG researchers. An AI follow-up interview digs into the real story behind a shopper's most recent store choice or channel switch, beyond what a closed question can capture.
View templateRetail Shopping and Product Search Behavior Survey
Maps how shoppers browse, search, and decide across in-store, online, and marketplace channels — where product searches succeed or break down, which purchase factors carry the most weight, and what an AI follow-up interview uncovers about the last time someone couldn't find what they wanted. Built for retail, e-commerce, and merchandising teams optimizing search, navigation, and discovery.
View templateOnline Purchasing Habits and Decision Drivers Survey
Measures how often people shop online, what actually drives a buy-or-abandon decision, and where friction shows up in checkout, delivery, and returns. An AI follow-up interview reconstructs a real recent purchase (or near-purchase) moment instead of relying on generic satisfaction ratings, making it useful for e-commerce and retail teams diagnosing drop-off.
View templateRetail 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.
View template