Marketing-Cloud-Personalization Knowledge Points, Marketing-Cloud-Personalization Pass Leader Dumps

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Salesforce Marketing-Cloud-Personalization Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Einstein Capabilities10%- Recipe ingredients
- Einstein recipes
Topic 2: Activation18%- Personalization campaigns
- Campaign testing and optimization
- Content creation and management
- Delivery channels
Topic 3: Solution Overview16%- Definition of Marketing Cloud Personalization
- Core components of standard implementation
- Typical use cases
- Product terminology
- Business value of real-time interaction management
Topic 4: Sitemap18%- Web SDK implementation
- Unified customer profile
- Content zones
- Overview and best practices
- Catalog and page mapping
Topic 5: Data Integration14%- ETL feed system
- Event API
- Salesforce Connector
- Data flows in and out of the system
Topic 6: Setup & Administration6%- User attributes management
- Initial setup process
- Identity system configuration
Topic 7: Segmentation18%- Filters and goals
- Journey Builder segment listener
- Segment export
- Segment rules
- Reporting and analytics
- Segment overview

>> Marketing-Cloud-Personalization Knowledge Points <<

100% Pass Quiz Useful Marketing-Cloud-Personalization - Marketing Cloud Personalization Accredited Professional Exam Knowledge Points

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Salesforce Marketing Cloud Personalization Accredited Professional Exam Sample Questions (Q17-Q22):

NEW QUESTION # 17
A brand's website is seeing high traffic but much of the behaviour is anonymous. How does IS unify anonymous identifies?

Answer: A


NEW QUESTION # 18
What are the three types of ingredients available for a recipe?

Answer: A,B,D

Explanation:
Within the context of Salesforce Marketing Cloud's Interaction Studio (formerly Evergage), "recipes" are pre- built configurations for personalized recommendations. These recipes utilize different types of "ingredients" to determine which items to recommend. Let's break down the correct options:
A: Catalog-based and Trending
* Verified:This is a type of ingredient used in Interaction Studio recipes.
* Explanation:
* Catalog-based:This ingredient leverages data from your product or content catalog. It can recommend items based on various catalog attributes like:
* Category:Recommending items from the same or related categories as items the user has viewed or interacted with.
* Attributes:Recommending items that share specific attributes (e.g., color, brand, size) with items the user has shown interest in.
* Keywords:Recommending items whose descriptions or metadata match keywords derived from user behavior.
* Trending:This ingredient considers the overall popularity or trending status of items within your catalog, often within a specific timeframe (e.g., "Trending in the last 7 days").
* Salesforce Marketing Cloud References:
* Interaction Studio Recipes:The Interaction Studio documentation describes the various recipe types and the ingredients they use.
B: Recommendations
* Verified:This is a broad category encompassing ingredients that generate recommendations based on various algorithms.
* Explanation:
* Recommendation Algorithms:Interaction Studio employs different algorithms to generate recommendations, including:
* Collaborative Filtering:Recommending items that similar users have liked or interacted with.
* Content-Based Filtering:Recommending items that are similar in content or attributes to items the user has shown interest in.
* User Affinity:Recommending items based on the user's overall affinity for particular categories, brands, or attributes, calculated from their historical interactions.
* Note:"Recommendations" is a more general term. Specific recommendation ingredients might have names like "User-to-Item Affinity," "Item-to-Item Similarity," or use algorithm names directly.
C: Co-Occurrence
* Verified:This is a specific type of recommendation ingredient that focuses on items frequently viewed or purchased together.
* Explanation:
* Co-occurrence Logic:This ingredient identifies items that are often viewed or purchased in the same session or within a short timeframe. It suggests that if a user is interested in item A, they are also likely to be interested in item B because other users have frequently interacted with both items together.
* Examples:
* "Customers who bought this item also bought..."
* "Frequently viewed together"


NEW QUESTION # 19
Which three components of a server side campaign can be defined by a business user?

Answer: C,D,E

Explanation:
In aserver-side campaignwithin Interaction Studio, business users can define:
* Promoted Content (Answer C):
* Content that should be prioritized or highlighted in recommendations or experiences.
* Experience Rules (Answer D):
* Rules governing the personalization logic, such as conditions for content display or user targeting.
* User Attributes (Answer E):
* Attributes that define user characteristics, enabling personalized interactions based on user profiles.
References:
* Salesforce Interaction Studio Documentation - Campaign Management


NEW QUESTION # 20
Which two successs metrics can a company achieve with IS their web channel?

Answer: A,D

Explanation:
* Interaction Studio (IS) helps businesses achieve significant success metrics through web channel personalization:
* Increase in Conversion Rate: By delivering tailored experiences and recommendations, IS drives more users to take desired actions (e.g., purchases, sign-ups).
* Increase in Revenue: Enhanced user engagement and conversions contribute directly to revenue growth.


NEW QUESTION # 21
Which scenario is a valid interaction studio use case?

Answer: B


NEW QUESTION # 22
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