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Exam Number : Salesforce-Certified-Marketing-Cloud-Consultant
Exam Name : Certified Marketing Cloud Consultant
Vendor Name : Salesforce
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Salesforce-Certified-Marketing-Cloud-Consultant Exam Format | Salesforce-Certified-Marketing-Cloud-Consultant Course Contents | Salesforce-Certified-Marketing-Cloud-Consultant Course Outline | Salesforce-Certified-Marketing-Cloud-Consultant Exam Syllabus | Salesforce-Certified-Marketing-Cloud-Consultant Exam Objectives

The Salesforce Marketing Cloud Consultant exam measures a candidates knowledge and skills related to the following objectives. A candidate should have hands-on experience with the Marketing Cloud Email application and demonstrate the knowledge and expertise in each of the areas below.

Discovery: 15%

Provided with a set of business requirements, determine what additional information is needed to design the recommended solution.

Provided with a list of branding and creative strategies, probe for additional information that is needed to recommend an appropriate solution.

Provided a customer environment and goals, determine the viability of external systems that need to be included in the solution (for example; POS, CRM, eCommerce, data warehouse, data source inputs).

Demonstrate how to gather requirements in order to put together the data and segmentation strategy for the customer (for example; frequency, complexity, volume of sending).

Given a scenario that includes customer information about subscriber acquisition, management, and attrition, utilize this information to select solution components.

Given a solution, recommend the appropriate customer skill sets required to utilize the Marketing Cloud application.

Conceptual Design: 12%

Analyze customer data to determine the appropriate data model (for example; List model, Data Extensions).

Given a scenario, determine the appropriate solution for given requirements considering technical expertise of personas (for example; Automation Studio vs. Journey Builder).

Given a narrative data flow, select the correct data flow diagram that depicts that data flow.

Given a customer scenario, identify which User Stories are appropriate to use for accessing Marketing Cloud.

Given a customer scenario, determine the factors to consider when scaling the solution.

Articulate how data construct will drive one-to-one messaging and content.

Explain the purpose of IP Warming and make a recommendation based on customer needs.

Marketing Cloud Connect: 6%

Understand the prerequisites to consider prior to starting a Marketing Cloud Connect configuration (for example; Salesforce edition, list of integration users, scope user, administrator credentials).

Understand how to send an email to a contact, lead, campaign, and report via the Sales/Service Cloud and Marketing Cloud (for example; sending, triggered, automated).

Understand how Sales/Service Cloud data in the Marketing Cloud can be segmented.

Account Configuration: 10%

Given a customer scenario, recommend the appropriate Marketing Cloud role based on User Stories.

Determine which type of customer scenario warrants the creation of a business unit (for example; publication types, demographic, workflow processes, and organizational structure).

Given a scenario, troubleshoot issues regarding Reply Mail Management.

Analyze the impact of applying a Sender Authentication Package (SAP) to a business unit (for example; link wrapping, Landing Pages, image URLs).

Reporting: 5%

Explain how the information in data views and tracking extracts are accessed.

Compare and contrast standard reports, data views, and tracking extracts.

Summarize Send Logs, including when/why to use it and how to create and manage.

Data Design: 12%

Explain the various data objects in the Marketing Cloud (for example; data extensions, list model, data retention model, publication lists, suppression lists).

Understand available data types, retention, and template options when building a data extension.

Understand how data is retrieved within a Relational Data Model (for example; basic SQL).

Given a customer scenario, recommend the appropriate import method with lists or data extensions.

Understand the implications of a system being database of record.

Automation: 8%

Given a customer scenario, select the appropriate workflow that meets the business requirement (for example; import, segmentation, email send).

Compare and contrast triggered and scheduled interactions.

Email Build: 7%

Understand the required steps to build, test, and deploy an email based on customer requirements.

Explain the various ways to individualize email content (for example; AMPscript, personalization strings, Dynamic Content, Guide Template Language).

Compare and contrast the ways to individualize content, such as SSJS vs. AMPscript, Dynamic Content Wizard vs. AMPscript/LookupRows function.

Explain various Marketing Cloud Email technologies (for example; Link Alias tags, Impression regions, Web Analytics Connector).

Contact Builder: 15%

Explain the role and capabilities within Contact Builder.

Understand how cardinality impacts data modeling.

Summarize how to use Data Designer to incorporate data source into Contact Builder.

Given a customer scenario, know how to build an Attribute Group to be used for a simple interaction.

Journey Builder: 10%

Compare and contrast automation tools, such as Journey Builder and Automation Studio.

Given a customer scenario that includes Journey Builder, evaluate the requirements, activities, and steps.

Explain the requirements for and the methods by which a contact can enter a Journey.

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Salesforce Cloud Exam Cram

Salesforce Unveils Marketing GPT, Commerce GPT, and Google Cloud Partnership

Salesforce at its Connections event yesterday introduced Marketing GPT and Commerce GPT, its latest generative artificial intelligence product offerings. The company also expanded its partnership with Google Cloud to help businesses use data and AI to deliver more personalized customer experiences, better understand customer behavior, and run more effective campaigns at a lower cost across marketing, sales, service, and commerce.

With Marketing GPT, marketers will be able to automatically generate personalized emails, smarter audience segments, and marketing journeys. And with Commerce GPT, companies will be able to deliver personalized shopping experiences and customized offers using GPT-powered dynamic buying journeys.

Marketing GPT combines generative AI and trusted first-party data from Data Cloud. It includes the following:

Segment Creation to improve targeting using natural language prompts and AI-driven recommendations.

Email Content Creation, which can auto-generate personalized emails for improved testing and engagement.

Segment Intelligence for Data Cloud, which automatically connects first-party data, revenue data, and third-party paid media data for a more comprehensive view of audience engagement.

Rapid Identity Resolution, Segmentation, and Engagement, which automatically resolves customer identities and refreshes segments in Data Cloud to help ensure up-to-date accuracy.

Typeface's generative AI content platform to create contextual visual assets for multichannel campaigns within Marketing GPT based on specific brand voice, style guides, and messaging.

Commerce GPT will enable companies to deliver customized commerce experiences at every step of the buyer's journey with auto-generated insights and recommendations based on unified real-time data from Data Cloud. It includes the following:

Goals-Based Commerce, which empowers businesses to set targets and goals and then provides actionable insights and proactive recommendations powered by Data Cloud, Einstein AI, and Flow.

Dynamic Product Descriptions that automatically fill in missing catalog data and generate product descriptions tailored to every buyer.

Commerce Concierge, to power personalized conversations and help shoppers discover products through natural language interactions across channels, from digital storefronts to messaging apps.

"Businesses are looking to harness new AI advances and tap into vast troves of data to deliver personalized customer experiences across every interaction. Marketing GPT and Commerce GPT, fueled by trusted and harmonized first-party data, will revolutionize how businesses interact with customers and at the same time dramatically improve employee productivity," said David Schmaier, president and chief product officer of Salesforce, in a statement.

Salesforce's expanded partnership with Google Cloud will help companies use data and AI to deliver more personalized customer experiences, better understand customer behavior, and run more effective campaigns at a lower cost across marketing, sales, service, and commerce.

Two new data and AI innovations will bring real-time data sharing with enhanced predictive and generative AI capabilities to better predict customer needs and reduce the cost, risk, and complexity of synchronizing data across platforms.

The new integration between Salesforce Data Cloud and Google's BigQuery will help companies create unified profiles of their customers. Salesforce and Google Cloud will provide customers with seamless data access across platforms and across clouds.

New integrations between Salesforce Data Cloud and Google Cloud's Vertex AI will enable companies to bring their own models from Vertex and use them across the Salesforce Platform.

"AI and data are revolutionizing the way businesses operate and innovate, and together Salesforce and Google are empowering organizations to unlock the full potential of their trusted data, put AI insights into action, and personalize customer experiences like never before. This partnership paves the way for unprecedented innovation and business value for our customers," Schmaier said.

"Google Cloud and Salesforce share a commitment to helping businesses accelerate their data-driven transformations. This new partnership brings together one of the world's largest data clouds from Salesforce with analytics and AI capabilities from Google Cloud, and represents a significant leap forward in businesses' ability to generate more value and insights from their customer data," said Thomas Kurian, CEO of Google Cloud, in a statement.

Salesforce, Google Cloud announce expanded strategic partnership to bolster AI offerings

SAN FRANCISCO, June 7 (Xinhua) -- Salesforce and Google Cloud on Wednesday announced an expanded strategic partnership to help businesses utilize data and artificial intelligence (AI) to deliver more personalized customer experiences, and run more effective campaigns at a lower cost across marketing, sales, service, and commerce.

The tie-up spans products and services including Google's BigQuery tooling, Salesforce's Data Cloud and Vertex AI, Google's fully managed AI platform.

The new data and AI innovations will bring real-time data sharing with enhanced predictive and generative AI capabilities, so businesses can use their data and their custom AI models to better predict customer needs and reduce the cost, risk, and complexity of synchronizing data across platforms, the announcement said.

"AI and data are revolutionizing the way businesses operate and innovate, and together Salesforce and Google are empowering organizations to unlock the full potential of their trusted data, put AI insights into action, and personalize customer experiences like never before," Chief Product Officer of Salesforce David Schmaier said.

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