Gauge marketer trust in MTA results and detect channel bias. Use this template to benchmark data quality and decision confidence.
What's Included
AI-Powered Questions
Intelligent follow-up questions based on responses
Automated Analysis
Real-time sentiment and insight detection
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Detailed Reports
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Template Overview
26
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 brief survey asks about your experience with MTA trust and potential biases. Most people finish in 5–7 minutes. Please answer based on your recent work.
Q2
Multiple Choice
Which attribution approaches has your organization used in the past 12 months? Select all that apply.
Multi-touch attribution (rules-based)
Multi-touch attribution (algorithmic/data-driven)
Marketing mix modeling (MMM)
Last-click attribution
First-touch attribution
Position-based/heuristic models
None of the above
Not sure
Q3
Multiple Choice
How is MTA delivered in your organization?
Vendor product
In-house model
Agency-provided
Not applicable—no MTA in use
Not sure
Q4
Rating
How much do you trust the outputs and documentation from your MTA solution?
Scale: 11 (star)
Min: Very low trustMax: Very high trust
Q5
Opinion Scale
Over the past 3 months, how much did you trust the MTA results you used?
Range: 1 – 10
Min: Not at allMid: NeutralMax: Completely
Q6
Multiple Choice
In the past 3 months, how often did MTA disagree with other measurement (e.g., MMM, experiments)?
Never
Rarely (less than monthly)
Sometimes (about monthly)
Often (weekly or more)
Not applicable—did not compare
Q7
Opinion Scale
Overall, how much do you trust MTA results in today’s environment?
Range: 1 – 10
Min: Not at allMid: NeutralMax: Completely
Q8
Matrix
How concerning are the following potential biases for MTA in your context?
Rows
Not a concern
Slight concern
Moderate
High
Major concern
Over-crediting branded search or direct traffic
•
•
•
•
•
Self-attribution by walled gardens
•
•
•
•
•
Incomplete tracking due to privacy/consent gaps
•
•
•
•
•
Recency bias toward last touches
•
•
•
•
•
Touchpoint inflation from ad stacking/high frequency
•
•
•
•
•
Model overfitting or instability
•
•
•
•
•
Selection bias in conversion data
•
•
•
•
•
Q9
Multiple Choice
Which single bias is your biggest concern today?
Over-crediting branded search or direct traffic
Self-attribution by walled gardens
Incomplete tracking due to privacy/consent gaps
Recency bias toward last touches
Touchpoint inflation from ad stacking/high frequency
Model overfitting or instability
Selection bias in conversion data
None of the above
Q10
Long Text
Please share a brief example of how this bias showed up and its impact.
Max 600 chars
Q11
Multiple Choice
Which steps have you taken to reduce bias in MTA outputs? Select all that apply.
Apply lookback windows/decay
Exclude brand search or direct from credit
Deduplicate conversions across platforms
Calibrate with MMM or causal lift
Run holdouts/geo experiments
Independent or vendor audit
Review model transparency and features
Data quality checks (consent, IDs, events)
Other
Q12
Multiple Choice
What would most increase your confidence in MTA? Select all that apply.
Attention check: To confirm you are paying attention, please select “Often” below.
Never
Rarely
Sometimes
Often
Always
Q14
Ranking
Rank the evidence sources that most increase your trust in MTA (top = most trust-building).
Drag to order (top = most important)
First-party site/app analytics
Ad platform logs
CRM/transactional data
Offline sales data
Experiments/holdouts
Third-party measurement
Panel/survey data
Q15
Constant Sum
Allocate 100 points to where MTA most influences your decisions.
Total must equal 100
Budget allocation
Channel/media mix
Bidding/optimization
Audience/targeting
Creative/messaging
Experiment design/validation
Reporting/KPI setting
Other
Min per option: 0Whole numbers only
Q16
Numeric
What minimum confidence level (%) do you require to act on MTA findings?
Accepts a numeric value
Whole numbers only
Q17
Multiple Choice
Which best describes your role?
Marketing leadership
Performance marketing
Growth/Acquisition
Data science/Analytics
Media/Activation
Product/MarTech
Consultant/Agency
Other
Q18
Multiple Choice
How many years have you worked with attribution or MTA?
0–1
2–4
5–7
8+
Q19
Multiple Choice
Company size (employees)
1–49
50–249
250–999
1,000–4,999
5,000+
Q20
Multiple Choice
Approximate annual paid media spend
<$1M
$1M–$4.9M
$5M–$19.9M
$20M–$99.9M
$100M+
Prefer not to say
Q21
Multiple Choice
Primary region
North America
Latin America
Europe
Middle East & Africa
Asia-Pacific
Other
Q22
Multiple Choice
Primary industry
Retail/ecommerce
Consumer services
B2B/Enterprise
Technology/Software
Media/Entertainment
Financial services
Travel/Hospitality
Healthcare/Pharma
Other
Prefer not to say
Q23
Multiple Choice
Your involvement in decisions based on MTA
I make final decisions
I influence decisions
I consume results but don’t decide
I implement/operate MTA
Not involved
Q24
Long Text
Anything else we should know about trust or bias in MTA at your organization?
Max 600 chars
Q25
AI Interview
AI Interview: 2 Follow-up Questions on Trust and Bias in MTA
AI InterviewLength: 2Personality: [Object Object]Mode: Fast
Q26
Chat Message
Thank you for your time—your input is greatly appreciated!
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