Q01
Message
All templates
Retail 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.
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, how did you mostly shop for the products you buy? (Replace with your product category if you want responses focused on it.)
- Only in physical stores
- Mostly in-store, some online
- Roughly equal mix of both
- Mostly online, some in-store
- Only online
Q03
Multiple ChoiceRequired
When you're looking for a specific product, where do you usually start your search first?
- The retailer's own website or app search bar
- A general search engine (e.g., Google)
- A marketplace site (e.g., Amazon)
- Social media or short-video platforms
- Walking into a physical store to browse
- Asking friends or family
- Other
Q04
Opinion ScaleRequired
In the last 30 days, how easy was it to find the specific products you were looking for?
Scale: 1 – 7
Min:Very difficultMax:Very easy
Q05
Best–Worst Trade-off (MaxDiff)Required
When deciding what to actually buy, which of these matter most versus least to you?
- Price
- Customer reviews and ratings
- Brand reputation
- Product is in stock and available now
- Shipping speed and cost
- Return policy
- Product images and descriptions
Pick best & worst per setBest:Matters mostWorst:Matters least
Q06
Matrix
How satisfied are you with each of the following when searching for products, whether online or in-store?
6 rows × 5 columns
- Accuracy of search results
- Filter and sort options
- Product recommendations shown to you
- Reviews and ratings available
- Product images and descriptions
- +1 more
Columns: Very dissatisfied · Dissatisfied · Neutral · Satisfied · Very satisfied
Q07
Multiple ChoiceRequired
In the last 30 days, how often did you give up on a search or abandon a cart because you couldn't find what you wanted?
- Never
- Once
- A few times
- Many times
Q08
Multiple Choice
Which device do you use most often when searching for products to buy?
- Smartphone
- Laptop or desktop computer
- Tablet
- In-store kiosk or staff assistance
- Voice assistant
Q09
AI Interview
Reconstruct the most recent time this respondent searched for a product and it did NOT go smoothly — what were they looking for, where did they search first, and exactly where did the search break down (bad results, no filters, out of stock, confusing site, unhelpful staff)? Anchor on specifics: what they clicked or asked, how long they tried before giving up, and what they did next (switched retailer, bought a substitute, abandoned the purchase entirely). If they said searches usually go fine, probe the single feature that would most improve how they discover products.
Q10
Message
Just a few quick questions about you so we can compare shopping habits across groups — all 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 to self-describe
- Prefer not to say
Q13
Multiple Choice
What is your 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
Q14
Message
Thank you for sharing how you shop and search! Your answers feed into a report our product and merchandising teams use to fix broken search paths and prioritize the features that help you find things faster.
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 dedicated AI follow-up interview that reconstructs the most recent time the respondent couldn't find a product, digging into what broke down and why
- Combines quantitative measures (opinion scale on search ease, MaxDiff on purchase-decision factors, matrix satisfaction ratings) with open-ended AI probing in one flow
- Captures channel behavior (in-store, online, marketplace) and device usage alongside search abandonment frequency, giving a full funnel view of discovery and drop-off
- Ends with a clear respondent-facing explanation that answers feed into a cross-group comparison report, plus standard demographic segmentation (age, gender, income)
QuestionPro
Retail shopping and search behavior survey questions + Sample questionnaire templateThis is a static questionnaire template covering retail shopping and search behavior topics, similar in subject scope to ours. It reads as a fixed question list meant for manual customization rather than an adaptive interview experience, and there's no indication of AI-driven follow-up or automated scoring.
What it does well
- Directly topic-matched to retail shopping and search behavior
- Backed by a large established survey platform with broad question-library support
- Likely includes sample questions researchers can copy or adapt quickly
Where it falls short
- Static question set with no adaptive AI follow-up probing into individual responses
- No mention of per-response quality scoring or transparent AI prompt methodology
- No voice-based interview option for richer qualitative capture
Jotform
Shopping Behavior Survey Form TemplateA form-builder template focused on general shopping behavior, useful for quick deployment and easy customization within Jotform's drag-and-drop editor. It's a standard form rather than a conversational or AI-assisted interview, so depth on any single answer depends entirely on how many questions you manually add.
What it does well
- Easy drag-and-drop customization typical of Jotform's builder
- Simple, quick to deploy for basic shopping behavior data collection
- Wide integration options common to Jotform's ecosystem
Where it falls short
- No adaptive AI follow-up interview to explore why a search or purchase failed
- No automated quality scoring of open-ended responses
- No voice AI interview capability for deeper qualitative insight
SurveyMonkey
Market Research Product Survey QuestionsThis is a broader market research product survey template rather than one specifically built around retail search and discovery behavior. It's a fixed questionnaire suited to general product feedback, with SurveyMonkey's standard analytics layered on top rather than an AI-guided interview.
What it does well
- Backed by SurveyMonkey's mature analytics and reporting dashboard
- Broad applicability across general product market research use cases
- Established platform with strong distribution and panel options
Where it falls short
- No adaptive AI interview to reconstruct a specific recent shopping search failure
- Static question format without automated per-response quality scoring
- No guided task or screen-share capability for observing search behavior directly
SurveySparrow
Product Market Research Survey TemplateA conversational-style product market research template that covers general product feedback rather than retail-specific search and discovery behavior in depth. It offers a chat-like UI for respondents but relies on pre-set questions rather than AI-generated follow-up probing.
What it does well
- Conversational chat-style UI that may feel more engaging than plain forms
- General product market research focus with broad applicability
- Likely mobile-friendly given SurveySparrow's product positioning
Where it falls short
- No true adaptive AI follow-up interview reconstructing a specific search breakdown
- No published methodology or transparent AI prompt structure
- No automated quality scoring or voice AI interview option
Ready to launch?
Open this template in the editor. Every part is yours to change before the first respondent sees it.