모든 템플릿

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.

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질문 26개 · 약 11분
Q01
메시지

Welcome to the MMM Readiness & Data Governance Assessment. This survey explores your organization's current Marketing Mix Modeling capabilities, data infrastructure, and governance practices. Your responses will help identify strengths, gaps, and opportunities to improve MMM effectiveness. • Participation is voluntary and you may stop at any time. • There are no right or wrong answers—we are interested in your honest perspective. • All responses are confidential and will be reported in aggregate only. • Estimated time: 7–9 minutes. Please proceed to begin.

Q02
객관식

Are you currently involved in—or do you have visibility into—marketing analytics, media measurement, or budget planning at your organization?

  • Yes
  • No
Q03
객관식

Which best describes your organization's current stage with Marketing Mix Modeling (MMM)?

  • Actively running MMM
  • Ran MMM in the last 12 months
  • Piloting or prototyping MMM
  • Planning to start within 12 months
  • Not planning MMM
Q04
객관식

Which data sources does your organization currently use or plan to use for MMM? (Select all that apply.)

  • Paid media spend and impressions by channel
  • Search data (paid and organic)
  • Social platform data
  • Website and app analytics
  • CRM and marketing automation engagement
  • Sales data by product or region
  • Pricing and promotions
  • Distribution and availability
  • Brand tracking
  • Competitor spend estimates
  • Economic, weather, or other external factors
  • Experiment and lift test results
Q05
의견 척도

Overall, how ready is your organization to leverage MMM for marketing decisions in the next 12 months?

척도: 17
최소:Not at all ready최대:Fully ready
Q06
객관식

Which governance practices are currently in place for your MMM-related data and models? (Select all that apply.)

  • Documented data dictionary or definitions
  • Data catalog or lineage tracking
  • Named data owner or steward
  • SLA for data refresh and issue resolution
  • Formal QA or validation checklist
  • Access controls and role-based permissions
  • Change log or versioning for datasets and models
  • Model governance committee or review board
  • Documented data retention policy
  • None of the above
Q07
객관식

What best describes your current or planned MMM approach?

  • In-house team
  • External vendor or consultancy
  • Hybrid (in-house plus partner)
  • Automated cloud service
  • Open-source stack built internally
  • Not sure or still evaluating
Q08
장문형

Based on your responses in this survey, what single change would most improve your organization's MMM effectiveness in the next 6–12 months?

Q09
드롭다운

What is your primary role?

  • Marketing leader
  • Growth or performance marketer
  • Media and activation
  • Data science or analytics
  • Finance or revenue operations
  • Product or CRM
  • Consultant or agency
  • Other
  • Prefer not to say
Q10
메시지

Thank you for completing this survey. Your responses have been recorded and will be analyzed in aggregate to advance MMM best practices. If you have any questions, please contact the research team.

Q11
객관식

Which decision areas does your organization currently use—or plan to use—MMM to inform? (Select all that apply.)

  • Budget allocation across channels
  • Media mix within a channel
  • Campaign flighting and timing
  • Geographic allocation
  • Creative and messaging strategy
  • Pricing and promotions
  • Scenario planning and forecasting
Q12
드롭다운

Approximately how many distinct data sources are integrated (or planned) in your MMM dataset?

  • 1–3
  • 4–7
  • 8–12
  • 13–20
  • More than 20
  • Not sure
Q13
순위 매기기

Rank the biggest inhibitors to effective MMM at your organization. (Drag to reorder; most limiting at top.)

  1. Data quality and coverage
  2. Analytics talent and ownership
  3. Budget constraints
  4. Stakeholder buy-in
  5. Fragmented martech and data stack
  6. Time and bandwidth
드래그하여 순위 지정
Q14
의견 척도

How confident are you that your MMM workflow complies with applicable privacy regulations and internal data policies?

척도: 17
최소:Not at all confident최대:Extremely confident
Q15
객관식

Which validation methods do you use (or plan to use) to assess MMM reliability? (Select all that apply.)

  • Time-based cross-validation (rolling origin)
  • Holdout or out-of-time testing
  • Alignment with experiments or incrementality tests
  • Back-testing on historical shocks
  • External benchmarks or market events sanity check
  • Business stakeholder review
  • None of the above
Q16
AI 인터뷰

Thank you for your survey responses. We'd like to explore a few of your answers in more depth. Please share your thoughts in the conversation below.

Q17
드롭다운

How many years of experience do you have in marketing, analytics, or related fields?

  • Less than 1
  • 1–3
  • 4–6
  • 7–10
  • 11–15
  • 16+
  • Prefer not to say
Q18
객관식

Which integration challenges are most significant for your MMM data pipeline? (Select all that apply.)

  • Inconsistent IDs or keys across sources
  • Missing or incomplete historical data
  • Different time grains (daily, weekly, monthly)
  • Taxonomy and naming differences
  • Data silos and access constraints
  • Data latency or delayed availability
  • Vendor definition changes over time
  • Legal or privacy restrictions
  • None of the above
Q19
드롭다운

Approximately how many employees does your organization have?

  • 1–49
  • 50–249
  • 250–999
  • 1,000–4,999
  • 5,000+
  • Prefer not to say
Q20
드롭다운

What is the typical refresh cadence of your MMM dataset?

  • Near real-time
  • Daily
  • Weekly
  • Monthly
  • Quarterly
  • Ad hoc or as needed
  • Not yet established
Q21
드롭다운

Which industry best describes your organization?

  • Retail or ecommerce
  • Consumer packaged goods (CPG)
  • Technology or software
  • Financial services
  • Media or entertainment
  • Healthcare or pharma
  • Travel or hospitality
  • Automotive
  • Other
  • Prefer not to say
Q22
의견 척도

How would you rate the completeness of the data available for your MMM (i.e., minimal missing values or gaps)?

척도: 17
최소:Very incomplete최대:Very complete
Q23
드롭다운

What is your organization's primary region of operation?

  • North America
  • Latin America
  • Europe
  • Middle East & Africa
  • Asia-Pacific
  • Global
  • Prefer not to say
Q24
의견 척도

How would you rate the consistency of your MMM data across sources (i.e., aligned definitions, taxonomies, and formats)?

척도: 17
최소:Very inconsistent최대:Very consistent
Q25
드롭다운

What is your level of influence on paid media budget decisions?

  • Final decision maker
  • Recommender or approver
  • Contributor or analyst
  • No direct role
  • Prefer not to say
Q26
의견 척도

How would you rate the timeliness of your MMM data (i.e., data is available when needed for modeling and decisions)?

척도: 17
최소:Rarely timely최대:Always timely

포함된 기능

  • AI 후속 질문

    정형화된 설문이 놓치는 세부 내용을, 주관식 답변에 맞춰 AI가 심층 질문으로 끌어냅니다.

  • 주의력 확인 장치

    성의 없는 답변과 저품질 응답자를 걸러내는 내장 안전장치입니다.

  • AI가 작성한 문안

    문구, 질문 순서, 분기 로직까지 AI가 연구 목표에 맞춰 작성합니다.

  • 자동 리포트

    응답이 모이면 주요 주제, 인용문, 이해하기 쉬운 요약이 자동으로 작성됩니다.

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차별화 포인트

  • Includes an AI follow-up interview that probes inconsistent or vague answers from the earlier structured questions, rather than stopping at fixed-choice responses
  • Covers the specific MMM maturity dimensions (data completeness, consistency, timeliness, refresh cadence, validation methods, governance practices) rather than generic marketing data collection
  • Combines opinion-scale ratings, a ranking exercise on inhibitors, and an open-text prioritization question to build a structured readiness profile, then synthesizes findings into an auto-generated report
  • Captures respondent context (role, tenure, org size, industry, region, budget influence) to segment MMM readiness findings by professional background

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