A/B Experimentation Trust & Data Quality Assessment
An internal diagnostic survey for teams that run or consume A/B tests, measuring trust in experiment results, identifying sources of flakiness, and prioritizing process and tooling improvements.
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
27
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 to the Experimentation Trust & Quality Survey.
We're gathering candid feedback on how A/B test results are used and trusted across the organization. Your responses are confidential and will be reported only in aggregate — there are no right or wrong answers.
Participation is voluntary, and you may exit at any time. The survey takes approximately 6–8 minutes. Results will be used internally to improve our experimentation practices and communication.
Q2
Multiple Choice
Which functional areas best describe your role? (Select up to three.)
Product Management
Engineering
Data Science / Analytics
Design / UX
Marketing / Growth
Operations / Support
Leadership / Strategy
Other
Q3
Multiple Choice
In the last 6 months, how often have you reviewed or acted on A/B test results?
Weekly or more
1 to 3 times per month
A few times total
Not in the last 6 months
Never
Q4
Chat Message
The following questions are for those who have not actively used A/B test results recently. If you regularly work with test results, you may skip ahead.
Q5
Opinion Scale
Based on your general impression, how reliable are our A/B test results overall?
Range: 1 – 7
Min: Not at all reliableMid: NeutralMax: Extremely reliable
Q6
Multiple Choice
What limits your use of A/B test results today? (Select all that apply.)
Hard to access results
Unsure how to interpret results
Don't trust the data quality
Not relevant to my work
No tests run in my area
Lack of time
Other
Q7
Opinion Scale
How useful would a short guide explaining key experimentation concepts (e.g., statistical power, minimum detectable effect, confidence intervals) be for your work?
Range: 1 – 7
Min: Not at all usefulMid: NeutralMax: Extremely useful
Q8
Chat Message
The following questions are for those who have actively worked with A/B test results in the past 3–6 months.
Q9
Dropdown
Approximately how many distinct A/B tests did you work on or review results from in the last 3 months?
1–2
3–5
6–10
11–20
More than 20
Q10
Multiple Choice
Where are the A/B tests you work with primarily run? (Select all that apply.)
Web
iOS app
Android app
Backend systems
Marketing channels (email / ads)
Other
Q11
Opinion Scale
How much do you trust the validity of our A/B test conclusions over the past 3 months?
Range: 1 – 7
Min: Do not trust at allMid: NeutralMax: Trust completely
Q12
Multiple Choice
How often do A/B test results meaningfully change your team's decisions?
Almost always
Often
Sometimes
Rarely
Almost never
Q13
Multiple Choice
In the past 3 months, have you observed flaky or inconsistent A/B test outcomes on key metrics?
No
Yes, occasionally
Yes, frequently
Unsure
Q14
Long Text
If you observed flaky or inconsistent outcomes, please share one or two examples and what you think caused them.
Max chars
Q15
Multiple Choice
How often do each of the following contribute to flaky or unreliable A/B test results in your area?
Insufficient sample size or test duration
Instrumentation or logging bugs
Peeking at results before reaching significance
Interactions between concurrent experiments
Unstable or delayed data pipelines
Poorly defined or overly sensitive metrics
External events or seasonality
Other
Q16
Opinion Scale
How clearly do shipped experiment reports communicate uncertainty (e.g., confidence intervals, statistical significance)?
Range: 1 – 7
Min: Not at all clearMid: NeutralMax: Extremely clear
Q17
Multiple Choice
Before launch, how often are minimum detectable effect (MDE) and statistical power planned explicitly for experiments?
Always
Often
Sometimes
Rarely
Never
Unsure
Q18
Dropdown
When deciding to ship based on a test result, what minimum effect size on the primary metric is typically meaningful for your team?
It depends on context
Any positive change
At least 0.5 percentage points
At least 1 percentage point
At least 2 percentage points
At least 5 percentage points
Q19
Ranking
Rank the following improvements by how much they would increase your trust in A/B test results. (Drag to reorder; most impactful first.)
Drag to order (top = most important)
Better instrumentation and QA
Guardrails against peeking at results early
Faster and more stable data pipelines
Pre-registration of hypotheses and metrics
Automated power / MDE checks before launch
Clearer result summaries and decision guidance
Q20
AI Interview
Based on your responses in this survey, please share any additional thoughts or concerns about the trustworthiness or reliability of our A/B testing program.
AI InterviewLength: 2Personality: [Object Object]Mode: Fast
Reference questions: 5
Q21
Chat Message
Finally, a few questions about your background for analysis purposes.
Q22
Dropdown
How long have you been at the company?
Less than 6 months
6 to 12 months
1 to 2 years
3 to 5 years
More than 5 years
Q23
Dropdown
How many years of total professional experience do you have?
0 to 2
3 to 5
6 to 10
11 to 15
More than 15
Q24
Dropdown
What is your seniority level?
Individual contributor
People manager
Director+
Prefer not to say
Q25
Multiple Choice
Where are you primarily located?
Americas
Europe
Middle East & Africa
Asia-Pacific
Multiple regions
Prefer not to say
Q26
Multiple Choice
Which product area(s) do you mostly support? (Select up to three.)
Consumer-facing experience
B2B / Enterprise
Infrastructure / Platform
Monetization / Payments
Marketing / Growth
Internal tools
Other
Prefer not to say
Q27
Chat Message
Thank you for your time. Your feedback will directly inform improvements to our experimentation practices, tooling, and communication. Results will be shared in aggregate with the broader team.
Frequently Asked Questions
What is QuestionPunk?
QuestionPunk is an AI-powered survey and research platform that turns traditional surveys into adaptive conversations. Describe your research goal and get a complete survey draft, conduct AI-moderated interviews with dynamic follow-ups, detect low-quality responses, and produce insights automatically. It's fast, flexible, and scalable across qualitative and quantitative research.
How do I create my first survey?
Sign up, then choose how to build: describe your research goal and let AI generate a survey, pick a template, or start from scratch. Add question types, set logic, preview, and share.
Can the AI generate a survey from a prompt?
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).
Can I test my survey before launching?
Yes. Use synthetic testing to create AI personas and run them through your survey. This helps catch issues with question flow, logic, and wording before real respondents see it.
How many languages are supported?
QuestionPunk supports 142+ languages. Add languages from the survey editor, auto-translate questions, and share language-specific links. AI interviews also adapt to the respondent's language automatically.
How can I share my survey?
Share via a direct link (with optional custom slug), embed on your website (iframe or script), distribute through Prolific for research panels, or generate a QR code for physical distribution.
Can I export survey results?
Yes. Export as CSV (flat or wide layout), Excel (XLSX), or export the survey structure as PDF/Word. Filter by suspicious level, response type, language, or date range before exporting.
Does QuestionPunk detect fraudulent responses?
Yes. Every response is automatically classified with a suspicious level (low/medium/high) based on attention checks, response timing, and behavioral signals. You can filter flagged responses in the Responses tab.
What are the pricing plans?
Basic (Free): 20 responses/month. Business ($50/month or $500/year): 5,000 responses/month with priority support. Enterprise (Custom): unlimited responses, remove branding, custom domain, and dedicated support.
How long does support take to reply?
We reply within 24 hours, often much sooner. Include key details in your message to help us assist you faster.