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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.

What's Included

AI-Powered Questions

Intelligent follow-up questions based on responses

Automated Analysis

Real-time sentiment and insight detection

Smart Distribution

Target the right audience automatically

Detailed Reports

Comprehensive insights and recommendations

Template Overview

24

Questions

AI-Powered

Smart Analysis

Ready-to-Use

Launch in Minutes

This professionally designed survey template helps you gather valuable insights with intelligent question flow and automated analysis.

Sample Survey Items

Q1
Chat Message
Welcome! Thank you for participating in this survey about your experience with product recommendations. This survey takes approximately 3–4 minutes. Your participation is entirely voluntary and you may stop at any time. There are no right or wrong answers — we are interested in your honest opinions. All responses are confidential, will be reported only in aggregate, and will be used to improve the recommendation experience.
Q2
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
Q3
Opinion Scale
How often do you engage with recommendations when using the product?
Range: 1 7
Min: NeverMid: NeutralMax: Very often
Q4
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
Q5
Multiple Choice
During that session, did you act on any recommendation (e.g., click, save, or purchase)?
  • Yes
  • No
  • Not sure
Q6
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)
Q7
Opinion Scale
Overall, how useful are our recommendations for achieving your goals?
Range: 1 7
Min: Not at all usefulMid: NeutralMax: Extremely useful
Q8
Opinion Scale
The recommendations I see are relevant to my interests.
Range: 1 7
Min: Strongly disagreeMid: NeutralMax: Strongly agree
Q9
Opinion Scale
The recommendations I see are timely for what I need.
Range: 1 7
Min: Strongly disagreeMid: NeutralMax: Strongly agree
Q10
Opinion Scale
I trust the accuracy of the recommendations I receive.
Range: 1 7
Min: Strongly disagreeMid: NeutralMax: Strongly agree
Q11
Opinion Scale
The recommendations introduce me to items I would not have found on my own.
Range: 1 7
Min: Strongly disagreeMid: NeutralMax: Strongly agree
Q12
Opinion Scale
How often do recommendations lead to a successful outcome for you (e.g., finding what you need, saving time)?
Range: 1 7
Min: NeverMid: NeutralMax: Always
Q13
Opinion Scale
How much control do you feel you have over the recommendations you see?
Range: 1 7
Min: No control at allMid: NeutralMax: Complete control
Q14
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
Q15
Opinion Scale
To what extent did the controls you used improve your recommendations?
Range: 1 7
Min: No improvement at allMid: NeutralMax: Major improvement
Q16
Ranking
Which of the following recommendation controls would be most useful to you? (Rank your top 3)
Drag to order (top = most important)
  1. More visible feedback buttons
  2. Per-item controls (hide/mute)
  3. Topic or source follow/block
  4. Adjustable diversity slider
  5. Profile preference settings
  6. Clearer explanations of why items are recommended
Q17
Opinion Scale
How much variety do you typically see across the recommendations shown to you?
Range: 1 7
Min: Very little varietyMid: NeutralMax: A great deal of variety
Q18
Opinion Scale
In the last 7 days, how often did you notice near-duplicate recommendations?
Range: 1 7
Min: NeverMid: NeutralMax: Very often
Q19
Ranking
Rank the following in order of how much you would like to see them in your recommendations (most desired first).
Drag to order (top = most important)
  1. Familiar items I already know
  2. New items I haven't seen before
  3. Variety across different topics or categories
Q20
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?
AI InterviewLength: 2Personality: [Object Object]Mode: Fast
Reference questions: 5
Q21
Long Text
Based on your experience, what one change would most improve the recommendations you receive?
Max chars
Q22
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
Q23
Dropdown
Which region do you primarily use the product from?
  • North America
  • Europe
  • Asia-Pacific
  • Latin America
  • Middle East & Africa
  • Prefer not to say
Q24
Chat Message
Thank you for completing this survey — your feedback directly helps us improve your recommendation experience!

Frequently Asked Questions

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Yes. Describe your research goal in plain language and QuestionPunk drafts a complete survey with appropriate question types, ordering, and AI follow-up logic. You can then customize before publishing.
What question types are available?
QuestionPunk supports a wide range of question types: opinion scale, rating, multiple choice, dropdown, ranking, matrix, constant sum, AI interview (text and audio), long text, short text, email, phone, date, address, website, numeric, audio/video recording, contact form, chat message, conversation reset, button, page breaks, and more.
How do AI interviews work?
AI interviews conduct adaptive conversations with respondents. The AI asks follow-up questions based on what the respondent says, probing for clarity and depth. You control the personality, tone, model (Haiku, Sonnet, or Opus), and question mode (fixed count, AI decides when to stop, or time-based).
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Can I export survey results?
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