Evaluates user comprehension, actionability, and satisfaction with error messages and troubleshooting flows. Designed for product and UX teams seeking to improve in-app error guidance based on recent user incidents within 30 days.
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
17
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! This short survey (approximately 5–7 minutes) asks about a recent error or confusing message you encountered in our product.
Your participation is voluntary—you may stop at any time. There are no right or wrong answers; we are interested in your honest experience. All responses are confidential and will be reported in aggregate only.
Q2
Multiple Choice
When did you most recently encounter an error or confusing message while using our product?
Today
In the last 3 days
4–7 days ago
8–14 days ago
15–30 days ago
I have not seen any errors or confusing messages in the last 30 days
Q3
Multiple Choice
Which types of messages have you seen recently? Select all that apply.
Error message
Warning or alert
Validation message (e.g., form field error)
Empty state message
Timeout or connection issue
App crash report
None of the above
Q4
Opinion Scale
Overall, how clear was the most recent error or message you saw?
Range: 1 – 7
Min: Not at all clearMid: NeutralMax: Extremely clear
Q5
Opinion Scale
How easy was it to understand what action to take after seeing the message?
Range: 1 – 7
Min: Very difficultMid: NeutralMax: Very easy
Q6
Opinion Scale
How appropriate was the tone of the message (e.g., helpful vs. blaming)?
Range: 1 – 7
Min: Very inappropriateMid: NeutralMax: Very appropriate
Q7
Opinion Scale
How specific was the message in describing what went wrong?
Range: 1 – 7
Min: Very vagueMid: NeutralMax: Very specific
Q8
Multiple Choice
Which actions did you take after seeing the message? Select all that apply.
Retried the action
Corrected my input
Used on-screen help or tips
Visited Help Center or FAQ
Contacted support
Searched the web
Refreshed or restarted the app
Abandoned the task
Other (please specify)
Q9
Dropdown
Approximately how long did it take to resolve the issue?
Under 1 minute
1–3 minutes
4–10 minutes
11–30 minutes
Over 30 minutes
Issue was not resolved
Not applicable
Q10
Ranking
Rank the following qualities of an error message from most important to least important.
Drag to order (top = most important)
Clear explanation of the cause
Suggested fix or workaround
Plain, jargon-free language
Next-step button or link
Unique reference code for support
Visual emphasis (e.g., color, icon)
Q11
Opinion Scale
Overall, how satisfied are you with how our product handles errors and guides you toward a resolution?
Range: 1 – 7
Min: Very dissatisfiedMid: NeutralMax: Very satisfied
Q12
Long Text
Based on your recent experience, what wording or steps would have made the error message clearer or more useful?
Max chars
Q13
AI Interview
We'd like to understand your experience with the error message in a bit more detail. Please share your thoughts and our AI moderator will ask follow-up questions.
AI InterviewLength: 2Personality: [Object Object]Mode: Fast
Reference questions: 6
Q14
Multiple Choice
What is your age group?
Under 18
18–24
25–34
35–44
45–54
55–64
65 or older
Prefer not to say
Q15
Multiple Choice
How do you describe your gender?
Woman
Man
Non-binary
Prefer not to say
Q16
Multiple Choice
Where do you currently live?
Africa
Asia
Europe
North America
South America
Oceania
Prefer not to say
Q17
Chat Message
Thank you for your time! Your feedback will directly help us improve error messages and troubleshooting guidance in our product.
Frequently Asked Questions
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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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