All templates
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.

Sample questions

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

26 questions · ~11 min
Q01
Message

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
Multiple Choice

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

  • Yes
  • No
Q03
Multiple Choice

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
Multiple Choice

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
Opinion Scale

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

Scale: 17
Min:Not at all readyMax:Fully ready
Q06
Multiple Choice

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
Multiple Choice

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
Long Text

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
Dropdown

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
Message

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
Multiple Choice

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
Dropdown

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
Ranking

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
Drag to rank
Q14
Opinion Scale

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

Scale: 17
Min:Not at all confidentMax:Extremely confident
Q15
Multiple Choice

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 Interview

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
Dropdown

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
Multiple Choice

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
Dropdown

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
Dropdown

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
Dropdown

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
Opinion Scale

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

Scale: 17
Min:Very incompleteMax:Very complete
Q23
Dropdown

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
Opinion Scale

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

Scale: 17
Min:Very inconsistentMax:Very consistent
Q25
Dropdown

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
Opinion Scale

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

Scale: 17
Min:Rarely timelyMax:Always timely

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 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

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 from the same category.

See all
Marketing & Growth

Campaign Goals & Attribution Practices Audit

A 90-day diagnostic survey for ecommerce teams to evaluate campaign goal-setting, attribution methods, tool effectiveness, and cross-functional alignment — surfacing gaps in ROAS, CAC measurement, and reporting workflows.

View template
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.

View template
Marketing & Growth

Brand Name Testing: Memorability & Distinctiveness Evaluation

Evaluates and compares candidate brand names on memorability, distinctiveness, and category appropriateness to identify the strongest option for a product or service launch.

View template
Marketing & Growth

Data Clean Room Adoption & Trust Assessment

Measures marketing professionals' awareness, trust, perceived accuracy, and adoption barriers related to data clean rooms for measurement. Ideal for ad tech vendors, industry bodies, or research teams benchmarking clean room sentiment.

View template
Marketing & Growth

App Store Listing A/B Concept Test

Evaluates two app store listing variants on clarity, appeal, trust, and conversion intent to identify the higher-performing concept. Designed for respondents who have recently browsed or installed apps.

View template
Marketing & Growth

Marketing Chatbot Experience & Effectiveness Survey

Measures how well your website or marketing chatbot resolves visitor questions, builds trust, and moves people toward a purchase or signup. An AI follow-up interview reconstructs the respondent's most recent chatbot conversation in detail, surfacing exactly where it helped or broke down. Built for marketing and CX teams evaluating a live chatbot deployment.

View template