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Marketing & Growth

Marketer Trust in Identity Resolution & Graph Accuracy

Measures marketing professionals' confidence in identity resolution accuracy, validation practices, and vendor evaluation criteria. Designed for B2B research targeting practitioners and decision-makers responsible for customer identity strategy.

Sample questions

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

30 questions · ~13 min
Q01
Message

Welcome! This survey (approximately 13 minutes) explores how marketing professionals evaluate identity resolution and identity graph accuracy. 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 in aggregate only for research purposes.

Q02
Multiple Choice

Which of the following best describes your current marketing role?

  • Brand / Content marketing
  • Performance / Demand generation
  • CRM / Lifecycle / Retention
  • Product marketing
  • Growth / Acquisition
  • Media / Advertising
  • Marketing operations
  • Marketing analytics / Insights
  • Other (please specify)
Q03
Multiple Choice

Does your organization currently use identity resolution or a customer identity graph?

  • Yes, in production
  • Piloting / testing
  • No, but considering
  • No, not considering
  • Not sure
Q04
Opinion Scale

How confident are you in the overall accuracy of your organization's identity resolution?

Scale: 17
Min:Not at all confidentMax:Extremely confident
Q05
Multiple Choice

Which of the following methods has your organization used in the past 12 months to validate identity resolution accuracy? (Select all that apply)

  • Holdout / ground-truth testing
  • Manual review / spot checks
  • Independent third-party audit
  • Match against deterministic keys (e.g., login / email)
  • Incrementality / lift experiments
  • Vendor-provided accuracy proof
  • Customer service feedback / returns
  • Production monitoring alerts
  • None of the above
Q06
Ranking

Please rank the following factors from most to least important when evaluating trust in identity resolution.

  1. Underlying data quality and coverage
  2. Deterministic vs. probabilistic matching method
  3. Recency and freshness of the graph
  4. Transparency and documentation
  5. Independent third-party validation
  6. Privacy compliance and controls
  7. Ongoing monitoring and SLAs
Drag to rank
Q07
Opinion Scale

How likely is your organization to evaluate or expand its identity resolution capabilities in the next 12 months?

Scale: 17
Min:Not at all likelyMax:Extremely likely
Q08
Long Text

Based on your responses in this survey, what would most increase your trust in identity graphs and match accuracy?

Q09
Multiple Choice

What is your current seniority level?

  • Individual contributor
  • Manager
  • Director
  • VP / Senior Director
  • C-level / Head of Marketing
  • Consultant / Agency
  • Other (please specify)
Q10
Message

Thank you for completing this survey! Your insights will help advance transparency and accuracy in identity resolution. If you have any questions about this research, please contact the research team.

Q11
Multiple Choice

Which of the following solutions support identity resolution at your organization? (Select all that apply)

  • Customer Data Platform (CDP)
  • Master Data Management (MDM)
  • Marketing cloud suite
  • Advertising ID graph (ad-tech)
  • Homegrown / custom solution
  • Data clean room
  • CRM / DMP
  • Other (please specify)
Q12
Multiple Choice

What minimum match accuracy would you require before deploying identity resolution in production?

  • Below 70%
  • 70–79%
  • 80–89%
  • 90–95%
  • 96–99%
  • 100% (only exact matches)
  • Don't know / haven't defined a threshold
Q13
Opinion Scale

How important is each of the following when selecting an identity graph provider? Match accuracy and precision

Scale: 17
Min:Not at all importantMax:Extremely important
Q14
AI Interview

We'd like to explore your experiences with identity resolution in a bit more depth. An AI moderator will ask you a couple of follow-up questions.

Q15
Dropdown

How many years of experience do you have in marketing?

  • Less than 2 years
  • 2–5 years
  • 6–10 years
  • 11–15 years
  • 16–20 years
  • More than 20 years
Q16
Multiple Choice

To the best of your knowledge, approximately what percentage of your resolved identities were correct in the past 6 months?

  • Below 50%
  • 50–69%
  • 70–79%
  • 80–89%
  • 90–95%
  • 96–100%
  • Don't know
Q17
Opinion Scale

In the past 12 months, how problematic has each of the following been for your identity resolution efforts? Duplicate or fragmented customer profiles

Scale: 15
Min:Not at all problematicMax:Extremely problematic
Q18
Opinion Scale

How important is each of the following when selecting an identity graph provider? Scale and coverage of identity data

Scale: 17
Min:Not at all importantMax:Extremely important
Q19
Multiple Choice

Approximately how many employees are in your company?

  • 1–49
  • 50–249
  • 250–999
  • 1,000–4,999
  • 5,000+
Q20
Multiple Choice

What are the main reasons your organization is not currently using identity resolution? (Select all that apply)

  • Insufficient budget
  • Privacy / compliance risk
  • Data quality / coverage concerns
  • Integration complexity
  • Lack of internal expertise
  • Unclear ROI or business case
  • Vendor credibility / trust
  • Stakeholder misalignment
  • We do not need it
  • Competing priorities
  • Other (please specify)
Q21
Opinion Scale

In the past 12 months, how problematic has each of the following been for your identity resolution efforts? Incorrect cross-device or cross-channel matching

Scale: 15
Min:Not at all problematicMax:Extremely problematic
Q22
Opinion Scale

How important is each of the following when selecting an identity graph provider? Ease of integration with existing tech stack

Scale: 17
Min:Not at all importantMax:Extremely important
Q23
Multiple Choice

Which industry best describes your organization?

  • Retail / Ecommerce
  • Financial services
  • Technology / SaaS
  • Media / Entertainment
  • Healthcare / Pharma
  • Travel / Hospitality
  • Telecom
  • Consumer packaged goods
  • Automotive
  • Other (please specify)
Q24
Opinion Scale

In the past 12 months, how problematic has each of the following been for your identity resolution efforts? Stale or outdated identity graph data

Scale: 15
Min:Not at all problematicMax:Extremely problematic
Q25
Opinion Scale

How important is each of the following when selecting an identity graph provider? Privacy compliance certifications and controls

Scale: 17
Min:Not at all importantMax:Extremely important
Q26
Multiple Choice

In which region are you primarily located?

  • North America
  • Europe
  • Asia-Pacific
  • Latin America
  • Middle East / Africa
Q27
Opinion Scale

In the past 12 months, how problematic has each of the following been for your identity resolution efforts? Privacy or compliance violations related to identity data

Scale: 15
Min:Not at all problematicMax:Extremely problematic
Q28
Opinion Scale

How important is each of the following when selecting an identity graph provider? Transparency into matching methodology

Scale: 17
Min:Not at all importantMax:Extremely important
Q29
Opinion Scale

In the past 12 months, how problematic has each of the following been for your identity resolution efforts? Lack of transparency into how matches are made

Scale: 15
Min:Not at all problematicMax:Extremely problematic
Q30
Opinion Scale

How important is each of the following when selecting an identity graph provider? Ongoing accuracy monitoring and SLAs

Scale: 17
Min:Not at all importantMax:Extremely important

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 a dedicated adaptive AI follow-up interview segment that lets marketers elaborate on identity resolution pain points beyond fixed-choice answers
  • Combines quantitative opinion-scale batteries (match accuracy confidence, vendor evaluation criteria, problem areas) with an open-text question on what would increase trust in identity resolution
  • Captures firmographic and role-based segmentation (seniority, company size, industry, region) so results can be cut by respondent type
  • Built for B2B practitioner research with transparent, auto-scored responses and an auto-generated report, rather than being a generic identity or demographic form

Frequently asked questions

What questions are in the “Marketer Trust in Identity Resolution & Graph Accuracy” template?

The template includes 30 ready-to-use questions, starting with: “Welcome! This survey (approximately 13 minutes) explores how marketing professionals evaluate identity resolution and id…” · “Which of the following best describes your current marketing role?” · “Does your organization currently use identity resolution or a customer identity graph?”. The full set is previewed above, and every question is editable.

How long does this survey take to complete?

Respondents typically finish the 30 questions in about 13 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.

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