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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.

設問の例

テンプレートの内容をプレビューできます。すべての設問は公開前に自由に編集できます。

全24問・約11分
Q01
メッセージ

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
選択式

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

  • Yes
  • No
Q03
選択式

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
オピニオンスケール

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

スケール: 1 – 7
最小:Not at all最大:Completely
Q05
ランク付け

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
ドラッグして順位を付ける
Q06
選択式

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
ランク付け

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
ドラッグして順位を付ける
Q08
AIインタビュー

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
選択式

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
メッセージ

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

Q11
選択式

How is MTA primarily delivered in your organization?

  • Vendor product
  • In-house model
  • Agency-provided
  • Combination of approaches
  • Not sure
Q12
オピニオンスケール

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

スケール: 1 – 7
最小:Not at all confident最大:Extremely confident
Q13
自由回答(長文)

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

Q14
選択式

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
ランク付け

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
ドラッグして順位を付ける
Q16
自由回答(長文)

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

Q17
選択式

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
選択式

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
選択式

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
プルダウン

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
選択式

Approximately how many employees does your company have?

  • 1–49
  • 50–249
  • 250–999
  • 1,000–4,999
  • 5,000+
Q22
選択式

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
選択式

In which region is your organization primarily based?

  • North America
  • Latin America
  • Europe
  • Middle East & Africa
  • Asia-Pacific
  • Other
Q24
選択式

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

含まれる機能

  • AIによる深掘り

    自由回答に合わせてAIが追加で質問し、固定のフォームでは拾えない具体的な内容を引き出します。

  • 注意確認設問

    急いだ回答や質の低い回答者を除外する仕組みを標準で備えています。

  • AIが作成する設問文

    文言、設問の順序、条件分岐をAIが調査の目的に合わせて作成します。

  • 自動レポート

    回答が集まると、テーマ、引用、わかりやすい要約が自動で作成されます。

このテンプレートを選ぶ理由

このテンプレートの設計意図をご紹介します。ほかのアンケートツールには、直接比較できるテンプレートが見つかりませんでした。

ここが違う

  • 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

よくあるご質問

「Multi-Touch Attribution Trust & Bias Assessment」テンプレートにはどのような設問が含まれていますか?

すぐに使える設問が24問含まれており、最初の設問は次のとおりです:「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…」。すべての設問は上でプレビューでき、自由に編集できます。

このアンケートの回答にはどのくらい時間がかかりますか?

回答者は通常、24問を約11分で回答し終えます。

テンプレートは編集できますか?

はい。公開前であれば、すべての設問、選択肢、順序を編集できます。設問の追加や削除のほか、調査の目的に合わせた作り直しをAIエディターに依頼することもできます。

このテンプレートは無料で使えますか?

はい。エディターで開けば、すぐに編集を始められます。お試しにアカウントは不要で、無料プランでアンケートを公開できます。

公開の準備はできましたか?

このテンプレートをエディターで開いてみてください。最初の回答者が目にする前に、すべてを自由に変更できます。

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