Q01
Message
All templatesProduct & UX
Product Recommendation Experience & Personalization Survey
Measures user satisfaction with recommendation relevance, perceived control, and content diversity. Designed for product teams optimizing personalization engines and recommendation UX.
Sample questions
A preview of what’s in the template. Every question is editable before you launch.
24 questions · ~11 min
Q02
Dropdown
How long have you been using this product?
- Less than 1 month
- 1–6 months
- 7–12 months
- 1–2 years
- More than 2 years
- I do not use it regularly
- Prefer not to say
Q03
Opinion Scale
Overall, how useful are our recommendations for achieving your goals?
Scale: 1 – 7
Min:Not at all usefulMax:Extremely useful
Q04
Opinion Scale
How much control do you feel you have over the recommendations you see?
Scale: 1 – 7
Min:No control at allMax:Complete control
Q05
Opinion Scale
How much variety do you typically see across the recommendations shown to you?
Scale: 1 – 7
Min:Very little varietyMax:A great deal of variety
Q06
AI Interview
I'd like to understand your recommendation experience a bit more. Let's start: What stands out most — positively or negatively — about the recommendations you've been seeing recently?
Q07
Dropdown
What is your age group?
- Under 18
- 18–24
- 25–34
- 35–44
- 45–54
- 55–64
- 65 or older
- Prefer not to say
Q08
Message
Thank you for completing this survey — your feedback directly helps us improve your recommendation experience!
Q09
Opinion Scale
How often do you engage with recommendations when using the product?
Scale: 1 – 7
Min:NeverMax:Very often
Q10
Opinion Scale
The recommendations I see are relevant to my interests.
Scale: 1 – 7
Min:Strongly disagreeMax:Strongly agree
Q11
Multiple Choice
Which of the following controls have you used to influence your recommendations in the last 30 days? (Select all that apply)
- Like / thumb up
- Dislike / thumb down
- Hide or mute items
- Follow topics or sources
- Adjust interests or preferences
- Clear or reset history
- Mark 'not interested' or skip
- None of these
Q12
Opinion Scale
In the last 7 days, how often did you notice near-duplicate recommendations?
Scale: 1 – 7
Min:NeverMax:Very often
Q13
Long Text
Based on your experience, what one change would most improve the recommendations you receive?
Q14
Dropdown
Which region do you primarily use the product from?
- North America
- Europe
- Asia-Pacific
- Latin America
- Middle East & Africa
- Prefer not to say
Q15
Dropdown
When did you last see recommendations in our product?
- Within the last 7 days
- 8–14 days ago
- 15–30 days ago
- More than 30 days ago
- I don't recall
Q16
Opinion Scale
The recommendations I see are timely for what I need.
Scale: 1 – 7
Min:Strongly disagreeMax:Strongly agree
Q17
Opinion Scale
To what extent did the controls you used improve your recommendations?
Scale: 1 – 7
Min:No improvement at allMax:Major improvement
Q18
Ranking
Rank the following in order of how much you would like to see them in your recommendations (most desired first).
- Familiar items I already know
- New items I haven't seen before
- Variety across different topics or categories
Drag to rank
Q19
Multiple Choice
During that session, did you act on any recommendation (e.g., click, save, or purchase)?
- Yes
- No
- Not sure
Q20
Opinion Scale
I trust the accuracy of the recommendations I receive.
Scale: 1 – 7
Min:Strongly disagreeMax:Strongly agree
Q21
Ranking
Which of the following recommendation controls would be most useful to you? (Rank your top 3)
- More visible feedback buttons
- Per-item controls (hide/mute)
- Topic or source follow/block
- Adjustable diversity slider
- Profile preference settings
- Clearer explanations of why items are recommended
Drag to rank
Q22
Multiple Choice
What prevented you from acting on a recommendation? (Select all that apply)
- Did not seem relevant to me
- Already had enough options
- Not enough helpful details provided
- Concerns about accuracy or trust
- Not timely for what I was doing
- I prefer finding items myself
- I was just browsing
- Other (please specify)
Q23
Opinion Scale
The recommendations introduce me to items I would not have found on my own.
Scale: 1 – 7
Min:Strongly disagreeMax:Strongly agree
Q24
Opinion Scale
How often do recommendations lead to a successful outcome for you (e.g., finding what you need, saving time)?
Scale: 1 – 7
Min:NeverMax:Always
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
- Our template dedicates multiple opinion-scale items specifically to recommendation relevance, timeliness, trust/accuracy, and content diversity (including a near-duplicate detection question), rather than treating recommendations as one line item in a general satisfaction survey
- It includes two ranking questions so product teams can quantify which recommendation controls and which content types users actually want prioritized
- It includes an adaptive AI follow-up interview that probes deeper into a respondent's specific recommendation experience based on their prior answers, plus an open-text question capturing one concrete improvement suggestion
- Responses feed into an automated report with per-response quality scoring, and QuestionPunk's prompts are transparent, unlike static form tools
QuestionPro
Product Satisfaction Survey Questions + Sample TemplateThis is a general product satisfaction survey template rather than one built specifically around recommendation relevance, control, or content diversity. It's a fielding-ready static template from an established survey platform, useful as a broad satisfaction instrument but not tailored to personalization-engine UX research. Teams would need to heavily customize it to get recommendation-specific insight.
What it does well
- Comes from a mature, full-featured survey platform with a large template library
- Provides a ready sample question set that teams can deploy quickly
- Likely supports standard survey logic and reporting common to QuestionPro's toolset
Where it falls short
- No adaptive AI follow-up interviewing — it's a fixed, static question set
- Not focused on recommendation-specific constructs like content diversity, control, or trust in personalization
- No automated per-response quality scoring or transparent AI prompt methodology
Frequently asked questions
What questions are in the “Product Recommendation Experience & Personalization Survey” template?
The template includes 24 ready-to-use questions, starting with: “Welcome! Thank you for participating in this survey about your experience with product recommendations. This survey take…” · “How long have you been using this product?” · “Overall, how useful are our recommendations for achieving your goals?”. The full set is previewed above, and every question is editable.
How long does this survey take to complete?
Respondents typically finish the 24 questions in about 11 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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