⚡ What’s New for Marketing Cloud Intelligence in Winter ’26?
More scenarios around data streams, mapping, and harmonization across ad platforms, CRM, web analytics, and offline data sources.
Increased focus on calculated dimensions and measurements, pacing, ROI, and attribution-related metrics.
More coverage of dashboard design, widgets, and executive storytelling, including how to build views for marketers, leadership, and media teams.
Scenarios involving CRM data, Data Cloud segments, and aligning Intelligence with campaign activation tools.
Marketing Cloud Intelligence Accredited Professional
Turn Fragmented Marketing Data into Unified, Actionable Insights
The Marketing Cloud Intelligence Accredited Professional credential validates your ability to integrate, harmonize, and analyze multi-source marketing data using Marketing Cloud Intelligence (formerly Datorama). It’s designed for consultants, analysts, and marketing ops professionals who deliver dashboards, insights, and decision support for marketing teams.
📊 Exam at a Glance
Exam Domains & Weightage (High-Level View)
1. Platform, Data Model & Architecture
~20%This domain tests your understanding of how Marketing Cloud Intelligence is structured and how data flows into it.
- Understanding the Intelligence platform architecture and core components.
- Marketing Cloud Intelligence data model: data streams, entities, and relationships.
- Types of data streams (media, analytics, CRM, offline, etc.).
- Business units, workspaces, users, and permissions concepts.
- When to use pre-built connectors vs. custom uploads / APIs.
Tip: Show that you know how Intelligence fits into a wider martech stack with multiple data sources.
2. Data Ingestion, Mapping & Harmonization
~26%This domain focuses on bringing data into the platform and making it consistent and trustworthy.
- Configuring data streams and advanced settings (update logic, keys, hierarchies).
- Mapping fields to standard entities, channels, and dimensions.
- Best practices for data harmonization across ad, web, and CRM sources.
- Handling data quality issues, missing values, and alignment across platforms.
- Managing multi-currency, multi-region, and multi-brand data.
Tip: Prefer designs that centralize and automate harmonization rather than relying on manual exports.
3. Calculations, Measurements & Dimensions
~20%This domain is about turning raw data into meaningful metrics and dimensions.
- Creating calculated measurements (CPC, CPA, ROAS, conversion rate, etc.).
- Defining calculated dimensions (groupings, classifications, and labels).
- Understanding data granularity, aggregation, and impact on calculations.
- Using calculations for pacing, budgets, and forecast-style metrics.
- Ensuring calculations are reusable and consistent across dashboards.
Tip: Good answers emphasize standardized, centrally managed metrics over ad-hoc calculations.
4. Dashboards, Visualizations & Insights
~22%This domain validates your ability to build dashboards that different audiences can understand and act on.
- Designing executive, channel, and campaign-level dashboards.
- Choosing the right widgets, charts, and layouts for the story.
- Using filters, drill-downs, and navigation for exploratory analysis.
- Building dashboards for specific stakeholders (media, CRM, leadership).
- Highlighting insights, anomalies, and recommended actions.
Tip: Think of dashboards as decision tools, not just pretty charts.
5. Governance, Operations & Best Practices
~12%Finally, you’re tested on how you run Intelligence as a reliable analytics platform.
- User management, roles, and permissions.
- Monitoring data freshness, stream failures, and quality issues.
- Documentation and training for marketing and analytics teams.
- Change management and rollout of new dashboards or metrics.
- Aligning Intelligence with privacy, governance, and audit requirements.
Percentages above are approximate and for study planning; Salesforce may adjust domain weightings over time.
📝 Sample Marketing Cloud Intelligence Questions
💡 Practice with Scenario-Based Questions
These practice questions are not from the real exam, but they reflect its style and reasoning. Focus on data modeling, harmonization, and dashboard strategy.
Question 1 – Harmonizing Media Data
A global brand runs campaigns across Google Ads, Meta Ads, and a local ad network. Each platform uses different
channel and campaign naming conventions. Leadership wants a single view of performance by region, channel,
and campaign objective.
What is the best approach in Marketing Cloud Intelligence?
✓ Correct Answer: B) Use data streams and mapping to harmonize fields into a standard set of dimensions, then build unified dashboards.
Option B leverages Intelligence’s data harmonization capabilities to create a consistent model across platforms. A and C rely on manual work, and D ignores key channels.
Question 2 – Calculated Metrics Strategy
A performance marketing team calculates ROAS (Return on Ad Spend) differently in each regional spreadsheet, leading
to inconsistent numbers in meetings.
How should the Intelligence specialist address this?
✓ Correct Answer: B) Create a central calculated measurement for ROAS in Intelligence and reuse it across all dashboards.
Option B ensures a single source of truth for ROAS, applied consistently across regions and views. A keeps inconsistency, C loses an important KPI, and D slows down reporting.
Question 3 – Dashboard Design for Executives
An executive team complains that the current dashboard is “too detailed” and makes it hard to see overall marketing
performance. They want a quick view of spend, revenue, and key KPIs by channel and region.
What design change should the specialist make?
✓ Correct Answer: B) Create an executive summary dashboard with high-level KPIs, trends, and simple breakdowns, linking to detailed views.
Option B matches audience-specific dashboard design: executives get a clean summary with the ability to drill down, while more detailed dashboards remain available for analysts.
🎯 4–6 Week Study Plan for Marketing Cloud Intelligence AP
Review the official exam guide and platform documentation. Focus on data streams, entities, and relationships. Draw a diagram of how paid media, web analytics, and CRM data flow into Intelligence for one sample brand.
Configure a few sample data streams and practice mapping and harmonizing fields. Create calculated measurements (CPC, ROAS, conversion rate) and dimensions (channel groupings, regions). Validate results with sample data.
Build an executive dashboard, a channel performance dashboard, and a simple campaign view. Add filters, drill-downs, and clear KPI tiles. Document how you would monitor data freshness and onboard new users. Practice scenario-based questions using 2–3 real marketing reporting challenges.
💡 Exam & Real-World Success Tips
Before jumping to dashboards, make sure you can explain which entities and relationships are needed to answer a business question.
The exam favors approaches where key KPIs are defined centrally and reused across views, reducing the risk of “dueling dashboards.”
Good Intelligence implementations serve both marketers and leadership. Think about the story each stakeholder needs to see when you design solutions.
Marketing Cloud Intelligence AP – FAQ
Who is the Marketing Cloud Intelligence AP exam for?
This exam is intended for marketing analysts, consultants, and marketing operations specialists who implement and manage Marketing Cloud Intelligence for multi-channel reporting.
Do I need to be a developer to pass this exam?
No. You should be comfortable with data, mappings, and calculations, but deep coding skills are not required. SQL or analytics experience is helpful but not mandatory.
How is this different from Marketing Cloud Engagement certifications?
Engagement certifications focus on campaign execution (emails, journeys, mobile). This AP focuses on measurement and analytics using Intelligence across all marketing channels.
How much hands-on experience should I have?
Most successful candidates have at least 1–2 years working with marketing data and a few projects involving Marketing Cloud Intelligence or similar BI tools.
What’s the best way to practice for scenario-based questions?
Take 2–3 real reporting challenges (e.g., unified media reporting, ROI dashboard, funnel performance) and design how you would solve them in Intelligence: data sources, mappings, calculations, and dashboards. Use those case studies as mental templates in the exam.