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| Section | Weight | Objectives |
|---|---|---|
| Segmentation | 18% | - Segment rules, filters and goals configuration - Segment performance reporting and analytics - Segment export and integration with Journey Builder - Segment creation and management |
| Setup & Administration | 6% | - Platform configuration and setup procedures - User attributes management - Identity system configuration |
| Einstein Capabilities | 10% | - Einstein recipes overview and usage - Ingredients configuration and application |
| Data Integration | 14% | - Event API usage and configuration - Salesforce Connector integration - ETL feed system implementation - Data flow management within and outside the platform |
| Sitemap | 18% | - Web SDK implementation - Unified customer profile building - Catalog and page mapping - Content zones configuration - Sitemap design and best practices |
| Activation | 18% | - Mobile and server-side campaigns - Campaign optimization and measurement - Campaign creation and execution - Open-time email campaigns - A/B testing setup and analysis |
| Solution Overview | 16% | - Definition and business value of Marketing Cloud Personalization - Product terminology and core implementation components - Real-time interaction management use cases |
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NEW QUESTION # 94
Which two items can be included in the total engagement score calculation?
Answer: A,B
Explanation:
* Visits (Answer B):
* The number of times a user visits a website or interacts with a channel.
* Actions (Answer C):
* Specific actions taken by the user, such as clicks, purchases, or form submissions.
These metrics reflect user interaction and engagement with the platform.
References:
* Salesforce Interaction Studio Documentation - Engagement Scoring
NEW QUESTION # 95
In the user interface what is the visual representation of the data about a single visitor including preference?
Answer: D
Explanation:
In the user interface of Interaction Studio, theUnified Customer Profile:
* Provides a detailed, real-time view of an individual visitor, including their preferences, behaviors, and interactions across all channels.
* This profile serves as a foundation for delivering personalized experiences.
References:
* Salesforce Interaction Studio Documentation - Unified Customer Profile
NEW QUESTION # 96
Which data feed integrates external system data into a user's profile leveraging identity attributes?
Answer: B
Explanation:
In Marketing Cloud Personalization, theUser Feedis specifically designed to integrate external system data into user profiles by leveraging identity attributes. This allows businesses to enrich user profiles with valuable information from various sources, such as CRM systems, loyalty programs, or other marketing platforms.
Here's how the User Feed works:
* Identity resolution:The User Feed utilizes identity attributes, such as email addresses, customer IDs, or loyalty numbers, to match incoming data with existing user profiles in Marketing Cloud Personalization. This ensures that data is accurately associated with the correct individuals.
* Data enrichment:Once a match is found, the User Feed appends the incoming data to the user's profile.
This can include a wide range of attributes, such as demographics, purchase history, preferences, loyalty status, or any other relevant information from the external system.
* Enhanced personalization:By enriching user profiles with data from various sources, the User Feed enables more granular segmentation, targeted campaigns, and personalized recommendations. This leads to a more relevant and engaging customer experience.
NEW QUESTION # 97
What are the three types of ingredients available for a recipe?
Answer: A,C,E
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 # 98
A marketer would like to display the most common products purchased by previous buyers along with the main item on a product page, which ingredient would they need to use in the recipe?
Answer: D
Explanation:
* TheCo-Buyingredient in a recipe identifies and displays products commonly purchased together.
* On a product page, it can recommend complementary items based on the main product being viewed.
References:
* Salesforce Interaction Studio Documentation - Recipes and Ingredients
NEW QUESTION # 99
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