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Salesforce Marketing-Cloud-Personalization Exam Syllabus Topics:

SectionWeightObjectives
Segmentation18%- Segment rules
- Segment overview
- Journey Builder segment listener
- Reporting and analytics
- Filters and goals
- Segment export
Sitemap18%- Overview and best practices
- Web SDK implementation
- Content zones
- Catalog and page mapping
- Unified customer profile
Solution Overview16%- Core components of standard implementation
- Product terminology
- Definition of Marketing Cloud Personalization
- Business value of real-time interaction management
- Typical use cases
Setup & Administration6%- User attributes management
- Initial setup process
- Identity system configuration
Einstein Capabilities10%- Recipe ingredients
- Einstein recipes
Activation18%- Delivery channels
- Personalization campaigns
- Content creation and management
- Campaign testing and optimization
Data Integration14%- ETL feed system
- Data flows in and out of the system
- Event API
- Salesforce Connector

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Salesforce Marketing Cloud Personalization Accredited Professional Exam Sample Questions (Q81-Q86):

NEW QUESTION # 81
What are base item types that an administrator can use in a Catalog?

Answer: D


NEW QUESTION # 82
What would a marketer include in a Recipe if they don't want to display recommendations for products priced less than $15?

Answer: B

Explanation:
To prevent recommendations for products priced under $15 in a Marketing Cloud Personalization recipe, marketers should utilize theExclusioningredient. This powerful feature allows for fine-grained control over recommendations by specifying criteria that disqualify certain items from being suggested.
Here's how the Exclusion ingredient works:
* Defining exclusion criteria:Within the recipe, marketers can define specific criteria that exclude products from the recommendation set. In this case, the exclusion criterion would be "price less than
$15."
* Filtering recommendations:When the recipe generates recommendations, the Exclusion ingredient filters out any products that meet the defined criteria. This ensures that only products priced $15 or higher are included in the final recommendations.
* Flexibility:Exclusions can be based on various product attributes or dimensions, providing flexibility in tailoring recommendations. This allows marketers to create highly targeted recommendations that align with campaign goals and customer preferences.


NEW QUESTION # 83
Which three components of a server side campaign can be defined by a business user?

Answer: A,B,D


NEW QUESTION # 84
What are the three primary areas of data stored in IS which represent a company's key business informative?

Answer: B,D,E

Explanation:
The three primary areas of data stored in Interaction Studio include:
* User Behavior (Answer A):
* Tracks individual user actions and interactions across channels.
* Shadow Catalog Information (Answer C):
* Stores product, content, or service catalog data used for recommendations and personalization.
* Operational Information (Answer E):
* Represents system and business configurations necessary for running campaigns and tracking performance.
References:
* Salesforce Interaction Studio Documentation - Data Architecture


NEW QUESTION # 85
What are IS machine learning powered algorithms called?

Answer: D

Explanation:
Einstein Recipesare the machine-learning-powered algorithms used in Interaction Studio (IS) to deliver personalized recommendations.
These recipes allow businesses to customize AI models to align with their specific goals.
Reference: Salesforce Interaction Studio Documentation - Einstein Recipes Overview.


NEW QUESTION # 86
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