Assesses experimentation program maturity across culture, process, tooling, governance, and outcomes. Designed for product, growth, and data teams to benchmark capabilities and identify improvement priorities.
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AI-Powered Questions
Intelligent follow-up questions based on responses
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Detailed Reports
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Template Overview
32
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 & A/B Testing Maturity Assessment.
This survey evaluates how your team and organization approach experimentation — covering process, tooling, governance, and outcomes. Your responses will help benchmark maturity and identify areas for improvement.
• Participation is voluntary and you may stop at any time.
• There are no right or wrong answers — we are interested in your honest perspective.
• All responses are confidential and will be reported only in aggregate.
• Estimated completion time: 10–12 minutes.
Please proceed to begin.
Q2
Multiple Choice
Which function best describes your primary role?
Product management
Growth / performance marketing
Lifecycle / CRM
Brand / creative marketing
Data / analytics
Engineering
Design / UX
Other (please specify)
Q3
Dropdown
Approximately how many people on your team are directly involved in experimentation?
1
2–5
6–10
11–20
21–50
51+
Q4
Multiple Choice
In the last 90 days, approximately how many experiments did your team launch?
0
1–2
3–5
6–10
11–20
21+
Q5
Multiple Choice
What are the primary objectives your experiments target? (Select up to 5)
Conversion rate
Retention / churn
Engagement
Monetization / revenue
Activation / onboarding
Acquisition / traffic
Feature adoption
Pricing / packaging
Brand / creative effectiveness
Learning about user behavior
Other (please specify)
Q6
Opinion Scale
Over the past 6 months, how would you rate the overall rigor of your team's experiment hypotheses?
Range: 1 – 7
Min: Not at all rigorousMid: NeutralMax: Extremely rigorous
Q7
Opinion Scale
Our team documents a clear hypothesis for every experiment before launch.
Which test or study types does your team run regularly? (Select all that apply)
A/B or split tests
Multivariate tests (MVT)
Holdout / control tests
Quasi-experiments / observational studies
Multi-armed bandits
Sequential tests
UX / usability studies
Surveys / concept tests
Feature-flag rollouts / experiments
Other (please specify)
Q12
Dropdown
What is the typical runtime for a single experiment, from launch to decision?
Same day
1–3 days
4–7 days
1–2 weeks
3–4 weeks
Over 4 weeks
Varies widely
Q13
Ranking
Rank the following phases by where your team spends the most effort in a typical experiment (most effort first).
Drag to order (top = most important)
Ideation / prioritization
Design, UX, and copy
Instrumentation and data quality
Implementation / engineering
QA and launch
Monitoring during run
Analysis and interpretation
Documentation and sharing
Rollout and follow-up
Q14
Multiple Choice
Which experimentation tools or platforms does your team currently use? (Select all that apply)
Optimizely
VWO
AB Tasty
Statsig
Eppo
Amplitude Experiment
LaunchDarkly or Flagsmith
Google Optimize (legacy)
In-house / custom platform
None currently
Other (please specify)
Q15
Multiple Choice
How are experiment datasets integrated with your analytics and data warehouse?
Fully integrated with analytics and warehouse
Partial integration; some manual pulls required
Isolated within the experimentation tool only
I don't know
Q16
Multiple Choice
Do you have a defined and versioned metrics catalog for experiments?
Yes, centrally defined and versioned
Yes, team-specific only
In progress
No
Q17
Multiple Choice
How does your team typically determine sample size and test duration?
Fixed-horizon power analysis
Sequential testing / alpha spending
Heuristics or benchmarks
Vendor tool auto-calculates
We usually don't calculate this
I don't know
Other (please specify)
Q18
Ranking
When deciding whether to ship a winning variant, rank these factors by importance to your team (most important first).
Drag to order (top = most important)
Effect size vs. baseline
Statistical significance or credible interval
Impact on guardrail metrics
Estimated business value
Implementation cost / complexity
Qualitative feedback / UX signals
Q19
Multiple Choice
Which risk controls does your team typically apply to experiments? (Select all that apply)
Guardrail metrics monitored
Kill switches / instant rollback
Ethics / privacy review when needed
Traffic allocation caps
Country / segment exclusions
QA and instrumentation checklist
None of the above
Other (please specify)
Q20
Multiple Choice
Is there an experimentation council or governance body at your organization?
Yes, org-wide
Yes, within my business unit
No, but being considered
No
Q21
Multiple Choice
Where are experiment plans and results typically documented? (Select all that apply)
Central system of record
Team wiki or docs
Within the testing tool
Spreadsheets
Not consistently documented
Other (please specify)
Q22
Opinion Scale
Overall, how would you rate the maturity of experimentation in your organization today?
Range: 1 – 7
Min: Very immature / ad-hocMid: NeutralMax: Best-in-class
Q23
Dropdown
Typically, how many business days elapse between a test ending and a final decision being made?
Same day
1–2 days
3–5 days
6–10 days
11–20 days
Over 20 days
We don't track this
Q24
Multiple Choice
In the last 6 months, approximately what share of completed experiments led to a production rollout?
0–10%
11–25%
26–40%
41–60%
61–80%
81–100%
We don't track this
Q25
Long Text
What are the biggest blockers or challenges to effective experimentation in your organization right now?
Max chars
Q26
AI Interview
Based on your survey responses, we'd like to explore your experimentation challenges and aspirations in a bit more depth.
AI InterviewLength: 2Personality: [Object Object]Mode: Fast
Reference questions: 6
Q27
Dropdown
What is your seniority level?
Individual contributor
Manager
Director
VP
C-level
Other
Q28
Dropdown
Approximately how many employees are in your company?
1–10
11–50
51–200
201–1,000
1,001–5,000
5,001–10,000
10,001+
Q29
Dropdown
Which industry best describes your organization?
Consumer software
B2B / SaaS
E-commerce / retail
Financial services / fintech
Media / entertainment
Healthcare / life sciences
Gaming
Telecom
Travel / hospitality
Other (please specify)
Q30
Dropdown
Where are you primarily based?
North America
Latin America
Europe
Middle East
Africa
Asia
Oceania
Q31
Dropdown
How many years have you worked with experimentation or A/B testing?
Less than 1
1–3
4–6
7–10
11+
Q32
Chat Message
Thank you for completing the Experimentation Maturity Assessment!
Your responses will be analyzed in aggregate to produce benchmarking insights. If you opted in, results will be shared with participants once the analysis is complete.
If you have any questions, please contact the research team at the email provided in your invitation.
Frequently Asked Questions
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