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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Visit Execution | 23% | - Order Capture and Order Submission - Visit Tasks and Task Types - Visit Execution Process - Promotion Check and Promotion Details - Photo Capture and Survey - Inventory Check and Product Listing |
| Topic 2: Admin and Configuration | 12% | - Mobile Configuration - Reports and Dashboards - Consumer Goods Cloud Data Model - User Setup and Permissions |
| Topic 3: Store Execution | 15% | - Store Execution Process - Assortment Monitoring - Planogram Compliance - Store Survey and Feedback |
| Topic 4: Visit Planning and Execution Configuration | 15% | - Configuration of Visit Plans and Visit Plan Targets - Configuration of Order Capture and Order Submission - Configuration of Visit Tasks and Task Types - Configuration of Photo Capture and Survey - Configuration of Inventory Checks and Product Listings - Configuration of Promotion Checks and Promotion Details |
| Topic 5: Store Execution Configuration | 12% | - Configuration of Store Execution Process - Configuration of Store Survey and Feedback - Configuration of Planogram Compliance - Configuration of Assortment Monitoring |
| Topic 6: Visit Planning | 23% | - Visit Schedule and Frequency - Visit Plan and Visit Plan Targets - Visit Planning Process - Territory Management |
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NEW QUESTION # 49
Which of the following is accurate regarding the Einstein Vision model?
Answer: B
Explanation:
An Einstein Vision object-detection model must be developed from a training dataset containing representative images of the objects that the model is expected to recognize. Model creation is therefore an implementation activity rather than something that occurs automatically from a single image or during ordinary field execution.
Salesforce ' s Einstein Vision development process begins by collecting representative training images. For object detection, each training example must also identify the relevant objects using bounding-box coordinates. The resulting examples are assembled into a dataset and submitted to the Einstein Vision training service. Training that dataset produces a model that can subsequently identify, classify, count, and locate corresponding objects in new images.
The quality and diversity of the base image set directly influence model performance. A sufficiently representative dataset must account for differences such as product orientation, lighting, shelf arrangement, packaging appearance, and surrounding objects. Salesforce also allows multiple models to be trained from evolving datasets so their performance can be evaluated and refined.
Consequently, the model is deliberately built during implementation from a prepared base dataset before it is incorporated into the field-execution process.
Study Guide Topics:Platform - > Einstein Vision - > Object Detection - > Training Dataset - > Model Creation
NEW QUESTION # 50
Sales Reps in the field are reporting that no surveys are available when they try to complete a visit survey on their mobile devices. What are two explanations for this?
Answer: A,E
Explanation:
In-Store Survey execution depends on both an available Salesforce Survey and a corresponding Survey Invitation. The survey supplies the questionnaire that the field representative must complete, while the invitation creates the specific survey instance that becomes available in the context of the visit, retail store, or contact.
Salesforce ' s Consumer Goods configuration process requires the administrator to set up and activate the survey before it can be distributed. An Assessment Task Definition of type In-Store Survey is then incorporated into the Action Plan Template used for the visit. To expose the actual survey instance, Salesforce requires a Survey Invitation to be generated, commonly through the Retail Store ' s primary contact. The invitation is associated with the relevant records so that it appears within the survey task during visit execution.
Field representatives do not require permission to create surveys merely to respond to them. Survey authoring is an administrative function. Likewise, the standard process does not depend on creating a custom task definition or on a separate Retail Execution Survey Lightning Flow.
Therefore, absence of either the activated Survey or the related Survey Invitation prevents the survey from being available to the field representative.
Study Guide Topics:Visit Execution - > In-Store Survey - > Salesforce Surveys - > Survey Invitations - > Visit
NEW QUESTION # 51
GreenTech, a Consumer Goods company wants to sell new products in a particular retail store Which Tableau CRM dashboard should they use to find opportunities to sell new products in a retail store location
Answer: D
Explanation:
White Space Analysis is a Tableau CRM dashboard that shows opportunities to sell new products in a retail store location. It analyzes the sales performance and product distribution across different stores and segments, and identifies gaps or white spaces where new products can be introduced or existing products can be expanded. Verified Reference: [Salesforce Consumer Goods Cloud Implementation Guide], page 37.
NEW QUESTION # 52
United Telecom is moving its assets to Communications Cloud as part of its digital transformation. During the asset migration process, a Consultant includes a step to create a No change MACD order.
Why is it necessary to have this step in the migration process?
Answer: A
Explanation:
When assets are migrated into Communications Cloud, Salesforce best practices require performing a "No-Change MACD Order" after data loading. This process creates a technical MACD order that does not modify any service, but instead tests whether the MACD orchestration, decomposition, and asset-based ordering logic work correctly with the migrated asset records.
Salesforce documentation explains that migrated assets must be fully compatible with:
Order decomposition mappings
Technical product relationships
Association to Service Accounts, Billing Accounts, Premises
Child/parent asset hierarchies
Fulfillment Request Line generation
Change order processing (A โ B transitions)
A no-change MACD validates that the migrated assets are structurally correct and "MACD-ready." If this test fails, the migration did not properly map assets to the Communications Cloud asset data model.
Options A and C overlap with validation but do not address MACD execution. Option B (Inventory Items) is not created through MACD and is unrelated.
NEW QUESTION # 53
Universal Connect (UC) sells several mobile devices to its customers. UC has several attributes like color, storage, and screen size that are common across mobile devices. UC is looking for recommendations around efficiently modeling them using the SFI product catalog.
How should the Consultant model the product catalog to achieve UC's requirements?
Answer: B
Explanation:
Salesforce EPC provides Object Types to group products that share common attributes. For mobile devices that all share color, storage, screen size, the correct modeling approach is:
โ Create a Mobile Offer Spec Type
Add all common attributes (color, storage, screen size).
Set parent = Base Offer Spec Type (standard hierarchy).
Associate mobile device products with this Object Type.
This ensures:
Attribute reuse
Cleaner catalog modeling
Easier maintenance
Declared inheritance from Base Offer Spec Type โ Mobile Offer Spec Type โ Device Offer Why others are incorrect:
A: Associates devices with Base Type instead of Mobile-specific type.
B: Suggests reversing hierarchy (incorrect structure).
D: Putting all attributes on Base Offer Spec Type violates specialization and bloats the base type.
NEW QUESTION # 54
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