Measures marketing professionals' awareness, trust, perceived accuracy, and adoption barriers related to data clean rooms for measurement. Ideal for ad tech vendors, industry bodies, or research teams benchmarking clean room sentiment.
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! This survey explores how marketing professionals view data clean rooms for measurement purposes. It should take approximately 8–10 minutes to complete.
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 and experiences based on your organization's current practices. All responses are confidential and will be reported only in aggregate for research purposes.
Q2
Multiple Choice
Which of the following best describes your involvement in measurement or data clean room decisions at your organization?
I am a primary decision-maker
I influence or recommend decisions
I am involved but do not make or recommend decisions
I am not involved in these decisions
Q3
Multiple Choice
Which of the following best describes your familiarity with and current stance on data clean rooms for marketing measurement?
Currently use a data clean room
Piloting or evaluating a data clean room
Familiar but not planning to use one
Not familiar with data clean rooms
Q4
Chat Message
For context: A data clean room is a secure environment where multiple parties can combine and analyze data under strict privacy controls. Raw, user-level data is never directly shared — only approved queries producing aggregated outputs are permitted, supporting use cases such as measurement and audience analysis.
Q5
Multiple Choice
Based on the definition above, how interested are you in exploring or evaluating a data clean room for your organization this year?
Very interested
Somewhat interested
Not very interested
Not interested at all
Q6
Multiple Choice
What are the main reasons your organization is not currently planning to use a data clean room? Select all that apply.
Insufficient internal resources or skills
Legal or privacy risk concerns
Total cost of ownership
Limited access to platforms or partners
Complexity of setup and operations
Unclear measurement improvement over current methods
Data sharing restrictions with partners
Other (please specify)
Q7
Multiple Choice
Which of the following measurement use cases does your organization currently run in a data clean room? Select all that apply.
Incrementality or lift testing
Attribution or contribution analysis
Reach and frequency deduplication
Audience overlap or sizing
Marketing mix modeling (MMM) calibration or validation
Data enrichment for measurement
Cross-publisher cohort analysis
Other (please specify)
Q8
Opinion Scale
Thinking about the past 6 months, how much do you trust the measurement results produced through data clean rooms?
Range: 1 – 7
Min: Do not trust at allMid: NeutralMax: Completely trust
Q9
Opinion Scale
How comfortable would you be sharing your organization's first-party data in a clean room operated by a major platform (e.g., Google, Meta, Amazon)?
Range: 1 – 7
Min: Not at all comfortableMid: NeutralMax: Extremely comfortable
Q10
Opinion Scale
How comfortable would you be sharing your organization's first-party data in a clean room operated by an independent third-party provider?
Range: 1 – 7
Min: Not at all comfortableMid: NeutralMax: Extremely comfortable
Q11
Opinion Scale
How comfortable would you be sharing your organization's first-party data in a clean room operated and managed by your own organization?
Range: 1 – 7
Min: Not at all comfortableMid: NeutralMax: Extremely comfortable
Q12
Opinion Scale
How accurate do you believe data clean room outputs are today for attribution or contribution analysis?
Range: 1 – 7
Min: Not at all accurateMid: NeutralMax: Extremely accurate
Q13
Opinion Scale
How accurate do you believe data clean room outputs are today for incrementality or lift testing?
Range: 1 – 7
Min: Not at all accurateMid: NeutralMax: Extremely accurate
Q14
Opinion Scale
How accurate do you believe data clean room outputs are today for reach and frequency measurement?
Range: 1 – 7
Min: Not at all accurateMid: NeutralMax: Extremely accurate
Q15
Multiple Choice
Which of the following would most increase your trust in clean-room-based measurement? Select up to three.
Transparent query templates and documentation
Ability to reproduce results independently
Third-party audit or certification
Open-source or inspectable methods
Publisher- or platform-level verification
Use of randomized holdouts or gold-standard tests
Clear privacy guarantees and controls
Q16
Ranking
Please rank the following obstacles to reliable clean-room measurement for your organization, from biggest obstacle (1) to smallest.
Drag to order (top = most important)
Interoperability across platforms or partners
Data latency or limited query flexibility
Legal/privacy risk or policy uncertainty
Cost of tools and services
Internal skills or bandwidth
Limited transparency into methods
Vendor or partner lock-in
Q17
Ranking
Please rank the following outcomes you value most from data clean rooms, from most valuable (1) to least valuable.
Drag to order (top = most important)
Improved measurement accuracy
Cross-partner interoperability
Privacy protection and compliance
Speed and query flexibility
Cost efficiency
Control and reproducibility
Access to partner or platform data
Q18
Multiple Choice
Over the next 12 months, how do you expect your organization's investment in data clean-room-based measurement to change?
Increase significantly
Increase somewhat
No change
Decrease somewhat
Decrease significantly
Unsure
Q19
Long Text
Based on your responses throughout this survey, what is the single biggest change that would increase your trust or comfort with data clean room measurement?
Max chars
Q20
AI Interview
We'd like to understand your experience with data clean rooms in a bit more depth. Please share your thoughts on what has shaped your current views, and we may ask a couple of follow-up questions.
AI InterviewLength: 2Personality: [Object Object]Mode: Fast
Reference questions: 11
Q21
Multiple Choice
Which of the following best describes your organization?
Brand or advertiser
Agency
Publisher or platform
Ad tech or measurement provider
Consulting or other services
Other (please specify)
Q22
Multiple Choice
Which of the following best describes your primary role?
Marketing or Media
Analytics or Measurement
Data or Engineering
Privacy, Legal, or Compliance
Executive or Leadership
Other (please specify)
Q23
Multiple Choice
In which region is your organization primarily based?
North America
Europe
Asia-Pacific
Latin America
Middle East or Africa
Multiple regions
Q24
Multiple Choice
Approximately how many employees does your organization have?
1–49
50–249
250–999
1,000–4,999
5,000+
Q25
Multiple Choice
What is your organization's approximate annual media spend?
Less than $1M
$1M–$9.9M
$10M–$49.9M
$50M–$199.9M
$200M+
Prefer not to say
Q26
Multiple Choice
How many years of experience do you have in marketing or analytics?
0–2 years
3–5 years
6–10 years
11+ years
Q27
Chat Message
Thank you for completing this survey! Your insights will help shape how the industry approaches data clean room measurement. All responses will be reported only in aggregate, and your individual answers will remain confidential.
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