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| Section | Objectives |
|---|---|
| Reporting and Analytics | - Dashboards and performance tracking - KPIs and retail execution metrics |
| Mobile and Offline Capabilities | - Mobile app usage for field reps - Offline synchronization and data handling |
| Visit Planning and Route Optimization | - Scheduling and field rep optimization - Territory and route planning concepts |
| Order Capture and Trade Promotion | - Order taking processes in Consumer Goods Cloud - Trade promotion management basics |
| Consumer Goods Cloud Fundamentals | - Data model overview (accounts, retail stores, visits) - Core platform concepts and Consumer Goods Cloud positioning |
| Retail Execution | - Store visits and field execution processes - In-store task management and compliance tracking |
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NEW QUESTION # 54
Which Action Plan Type should be selected when creating an Action Plan for Consumer Goods Cloud?
Answer: D
Explanation:
The Action Plan Type that should be selected when creating an Action Plan for Consumer Goods Cloud is Visit Execution. An Action Plan Type is a metadata record that defines the type and configuration of an action plan. An action plan is a set of tasks that need to be completed for a specific purpose or goal. The Visit Execution Action Plan Type is designed for Consumer Goods Cloud users who need to create action plans for their store visits. A visit is an interaction between a field rep and a retail store. Verified Reference: [Salesforce Consumer Goods Cloud Implementation Guide], page 25.
NEW QUESTION # 55
Northern Trail Outfitters (NTO) has a 7-tier product hierarchy that they use to track products in their Enterprise Resource Planning (ERP) platform. Assuming this functionality is available in the Consumer Goods Cloud, what should a consultant at NTO determine which tier of data contains the information required to set up products in Consumer Goods Cloud NTO wishes to measure share-of-shelf?
Answer: B
Explanation:
The consultant must identify the hierarchy level that represents the stock keeping unit (SKU). In the Consumer Goods Retail Execution data model, individual products are represented through Product2 records, and Salesforce describes each Product2 record as a SKU or sellable unit. Consequently, the ERP hierarchy level that contains SKU-level information provides the appropriate product granularity for product-specific retail execution processes.
Share-of-shelf measurement requires Salesforce to identify precisely which products occupy shelf space so that actual shelf presence can be evaluated against configured targets. Retail Store KPIs can associate Assessment Indicator Definitions such as Share of Shelf with products, product categories, planograms, store groups, and in-store location categories. The underlying product master therefore needs a level that reliably represents the individual sellable products being measured.
Salesforce product master data can contain multiple hierarchy levels such as categories, subcategories, brands, and SKUs. The numerical position of a tier is not itself significant; what matters is the business meaning of that tier. For this requirement, the tier representing SKUs provides the required product-level data for shelf measurement and Retail Execution processing.
Study Guide Topics:Data Setup - > Product2 - > Product Hierarchy - > SKU - > Share-of-Shelf KPI
NEW QUESTION # 56
What does this out of the box Einstein Analytics dashboard inform about? Product Performance
Answer: B
Explanation:
The Product Performance dashboard is designed to help sales managers analyze how products, product categories, brands, and assortments are performing across the Consumer Goods organization. It provides detailed performance views that allow users to identify both strong and weak performers and then drill into the underlying metrics.
Salesforce states that the Product Performance dashboard analyzes product category, brand, product, assortment, and the impact of promotions on performance. Its Product page shows overall product trends and enables managers to identify high-performing products and analyze recently launched products. Its Category and Assortment pages provide equivalent analysis at those organizational levels.
Typical measures include revenue, quantity, average order value, store coverage, average compliance, and related sales-performance indicators. Salesforce specifically describes the dashboard as answering questions such as which products, categories, brands, and assortments are high-performing or least-performing.
Managers can drill into individual entities to investigate performance trends and identify where intervention or additional investment is appropriate.
Therefore, the dashboard gives the Sales Manager the ability to identify top- and low-performing products, categories, and assortments and investigate their performance in greater detail.
Study Guide Topics:Analytics - > Product Performance - > Product Categories - > Assortments - > Performance Analysis
NEW QUESTION # 57
How can an Account Manager visualize store visits in their territory for the day by their current status?
Answer: B
NEW QUESTION # 58
A company is selling voice products to business customers. The other allows customers to select for rent or purchase up to 700 phone devices of various models. The product modeller intends to create a phone add-on product specification and add it as a child of the voice offer, with a cardinality that allows up to 700.
Which three statements are valid regarding the product model in this scenario?
Answer: B,C,D
Explanation:
In Salesforce Industries Enterprise Product Catalog (EPC), hierarchical product modeling with child specifications and cardinalities is natively supported, which makes option E correct. Defining a voice offer with a "phone add-on" child product and a cardinality of up to 700 leverages standard EPC capabilities such as product specifications, child relationships, and cardinality rules.
However, Salesforce guidance for EPC and Industries CPQ warns that very large cardinalities on child products can introduce performance and processing challenges, especially in high-volume telecom scenarios. During MACD (Modify, Add, Change, Disconnect) operations, every instance of the child product (each phone device) has to be evaluated, updated, and sometimes decomposed into order items or service orders. With hundreds of instances, this can lead to processing inefficiencies and long-running transactions, which supports statement A.
Additionally, although the model technically uses out-of-the-box features, extreme volumes (such as hundreds of children per parent) can stress the decomposition engine. Under heavy load or complex rule combinations, decomposition may time out or fail when the maximum number of instances are ordered, making C valid as well.
Option B is incorrect because EPC does support this pattern; flat-only modeling is not a requirement. Option D is incorrect because using OOTB features does not guarantee optimal MACD and decomposition behavior at very high instance volumes.
NEW QUESTION # 59
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