All templates
Marketing & Growth

Multi-Touch Attribution Trust & Bias Assessment

Measures marketer trust in multi-touch attribution outputs and identifies perceived channel biases. Designed for marketing, analytics, and media professionals who work with attribution data to inform budget and optimization decisions.

Sample questions

A preview of what’s in the template. Every question is editable before you launch.

24 questions · ~11 min
Q01
Message

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.

Q02
Multiple Choice

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

  • Yes
  • No
Q03
Multiple Choice

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
Q04
Opinion Scale

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

Scale: 17
Min:Not at allMax:Completely
Q05
Ranking

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
Drag to rank
Q06
Multiple Choice

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
Q07
Ranking

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
Drag to rank
Q08
AI Interview

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.

Q09
Multiple Choice

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)
Q10
Message

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

Q11
Multiple Choice

How is MTA primarily delivered in your organization?

  • Vendor product
  • In-house model
  • Agency-provided
  • Combination of approaches
  • Not sure
Q12
Opinion Scale

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

Scale: 17
Min:Not at all confidentMax:Extremely confident
Q13
Long Text

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

Q14
Multiple Choice

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)
Q15
Ranking

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
Drag to rank
Q16
Long Text

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

Q17
Multiple Choice

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
Q18
Multiple Choice

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
Q19
Multiple Choice

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
Q20
Dropdown

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
Q21
Multiple Choice

Approximately how many employees does your company have?

  • 1–49
  • 50–249
  • 250–999
  • 1,000–4,999
  • 5,000+
Q22
Multiple Choice

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
Q23
Multiple Choice

In which region is your organization primarily based?

  • North America
  • Latin America
  • Europe
  • Middle East & Africa
  • Asia-Pacific
  • Other
Q24
Multiple Choice

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

What’s included

  • AI follow-ups

    Adaptive probes on open-ended answers that pull out detail a static form would miss.

  • Attention checks

    Built-in safeguards against rushed answers and low-quality respondents.

  • AI-drafted copy

    Wording, ordering, and branching written by the AI — tuned to your research goal.

  • Auto report

    Themes, quotes, and a plain-English summary write themselves once responses come in.

Why this template

What this template is built to do — we found no directly comparable template from other survey tools to review.

What sets it apart

  • Includes multiple ranking exercises that force respondents to prioritize specific MTA biases, trusted evidence sources, and decision areas—yielding relative, not just absolute, bias signals
  • Combines quantitative trust and confidence opinion-scale questions with an open-text prompt asking for a concrete example of bias, plus a follow-up open-text reflection at the end
  • Uses an AI follow-up interview to probe deeper into individual trust/bias experiences after the structured questions, something a static form cannot replicate
  • Segments respondents by role, experience, company size, media spend, region, and industry, enabling cross-cuts of trust and bias perception by professional context

Frequently asked questions

What questions are in the “Multi-Touch Attribution Trust & Bias Assessment” template?

The template includes 24 ready-to-use questions, starting with: “Welcome! This survey explores your experience with multi-touch attribution (MTA) and how it informs your marketing decis…” · “In the past 12 months, have you personally used, reviewed, or made decisions based on multi-touch attribution data or re…” · “Which of the following attribution or measurement approaches has your organization used in the past 12 months? Select al…”. The full set is previewed above, and every question is editable.

How long does this survey take to complete?

Respondents typically finish the 24 questions in about 11 minutes.

Can I customize this template?

Yes — every question, answer option, and the ordering is editable before you launch. You can add or remove questions, or ask the AI editor to rework the survey around your research goal.

Is this template free to use?

Yes. Open it in the editor and start customizing right away — no account required to try it, and the free plan covers launching your survey.

Ready to launch?

Open this template in the editor. Every part is yours to change before the first respondent sees it.

Related templates

More studies on similar topics.

See all
Marketing & Growth

MMM Readiness & Data Governance Assessment

Evaluates an organization's Marketing Mix Modeling maturity across data foundations, governance practices, validation methods, and resourcing. Designed for marketing, analytics, and media professionals involved in or planning MMM initiatives.

View template
Marketing & Growth

Digital Marketing Channel Effectiveness & Ad Recall Survey

Measures which digital marketing channels customers actually notice, trust, and act on — from social ads to email to influencer content — and how they'd prioritize messaging and budget. An AI follow-up reconstructs the specific ad moment that shaped their perception, surfacing the 'why' behind trust or annoyance that closed questions miss. Built for marketing teams evaluating channel mix, creative, and spend.

View template
Marketing & Growth

Brand Asset Recognition & Attribution Survey

Measures unaided recall and recognition accuracy of brand logos, color palettes, and taglines to benchmark brand asset attribution strength across audience segments.

View template
Marketing & Growth

Brand Pulse: Attribute Perception Tracker

Tracks how your brand is perceived on key attributes like trust, quality, and value, and identifies which of those attributes actually drive choice through a best-worst trade-off exercise. An AI follow-up interview digs into the story behind the respondent's lowest-rated attribute. Built for brand and marketing teams running recurring pulse checks.

View template
Marketing & Growth

Consumer Trust & Acceptance of AI-Generated Advertising

Measures consumer trust, perceived quality, and contextual acceptance of AI-generated ads. Designed for advertising researchers and brand strategists evaluating disclosure norms, comfort thresholds, and creative-format preferences.

View template
Marketing & Growth

AI Content Watermark Perception & Trust Survey

Measures consumer awareness, trust, acceptability, and behavioral intentions regarding AI content provenance watermarks, designed for technology policy researchers and platform designers evaluating labeling strategies.

View template