Multi-Touch Attribution Trust & Bias Assessment

Welcome! This survey explores your experience with multi-touch attribution (MTA) and how it informs your marketing decisions. It should take approximately 11 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. All responses are confidential and will be reported only in aggregate. Results will be used for internal research to improve measurement practices. Please answer based on your experience over the past 3–6 months.

In the past 12 months, have you personally used, reviewed, or made decisions based on multi-touch attribution data or results?

• Yes
• No

Which of the following attribution or measurement 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

How is MTA primarily delivered in your organization?

• Vendor product
• In-house model
• Agency-provided
• Combination of approaches
• Not sure

How would you describe your involvement in decisions informed by MTA?

• I make final decisions
• I influence decisions
• I consume results but don't decide
• I implement/operate MTA
• Not involved

Over the past 3 months, how much did you trust the MTA results you used to inform decisions?

Looking ahead, how confident are you that MTA will produce reliable results for your organization?

In the past 3 months, how often did MTA results disagree with other measurement approaches (e.g., MMM, experiments)?

• Never
• Rarely (less than monthly)
• Sometimes (about monthly)
• Often (weekly or more)
• Not applicable—did not compare

Rank the following potential biases in MTA from most concerning to least concerning in your context. Drag the most concerning to the top.

1. Over-crediting branded search or direct traffic
2. Self-attribution by walled gardens
3. Incomplete tracking due to privacy/consent gaps
4. Recency bias toward last touches
5. Touchpoint inflation from ad stacking/high frequency
6. Model overfitting or instability
7. Selection bias in conversion data

Please share a brief example of how bias in MTA has shown up in your work and what impact it had.

Which of the following steps has your organization taken to reduce bias in MTA outputs? Select all that apply.

• Apply lookback windows or decay functions
• Exclude brand search or direct from credit
• Deduplicate conversions across platforms
• Calibrate with MMM or causal lift studies
• Run holdouts or geo experiments
• Commission independent or vendor audit
• Review model transparency and features
• Data quality checks (consent, IDs, events)
• Other (please specify)
• None of the above

Which of the following would meaningfully increase your confidence in MTA results? Select all that apply.

• Transparent methodology and assumptions
• Third-party audit or validation
• Alignment with MMM or causal lift studies
• Regular back-testing and out-of-sample validation
• Access to raw signals and feature importances
• Better identity resolution or clean-room integrations
• Clear conversion deduplication policy
• Geo or cell-level experiments
• Other (please specify)

Rank the following evidence sources by how much they increase your trust in MTA results. Drag the most trust-building source to the top.

1. First-party site/app analytics
2. Ad platform logs
3. CRM/transactional data
4. Offline sales data
5. Experiments/holdouts
6. Third-party measurement
7. Panel/survey data

Rank the following areas by how much MTA influences your decisions. Drag the most influenced area to the top.

1. Budget allocation across channels
2. Channel and media mix planning
3. Bidding and optimization
4. Audience and targeting
5. Creative and messaging
6. Experiment design and validation
7. Reporting and KPI setting

What minimum confidence level do you typically require before acting on MTA findings?

• Below 50%
• 50–59%
• 60–69%
• 70–79%
• 80–89%
• 90–95%
• Above 95%
• I don't use a specific threshold
• Not sure

We'd like to explore your experiences with MTA trust and bias in a bit more depth. An AI moderator will ask you a couple of follow-up questions based on your earlier responses.

Based on your responses in this survey, please share any additional thoughts about trust or bias in MTA at your organization.

Which of the following best describes your primary role?

• Marketing leadership
• Performance marketing
• Growth/Acquisition
• Data science/Analytics
• Media/Activation
• Product/MarTech
• Consultant/Agency
• Other (please specify)

How many years of experience do you have working with attribution or MTA?

• Less than 1 year
• 1–2 years
• 3–4 years
• 5–7 years
• 8+ years

Approximately how many employees does your company have?

• 1–49
• 50–249
• 250–999
• 1,000–4,999
• 5,000+

What is your organization's approximate annual paid media spend?

• Under $1M
• $1M–$4.9M
• $5M–$19.9M
• $20M–$99.9M
• $100M+
• Prefer not to say

In which region is your organization primarily based?

• North America
• Latin America
• Europe
• Middle East & Africa
• Asia-Pacific
• Other

Which industry best describes your organization?

• Retail/E-commerce
• Consumer services
• B2B/Enterprise
• Technology/Software
• Media/Entertainment
• Financial services
• Travel/Hospitality
• Healthcare/Pharma
• Other
• Prefer not to say

Thank you for completing this survey—your insights are greatly appreciated and will help improve MTA measurement practices.