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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Visit Planning | 6% | - Route planning - Visit templates - Territory management |
| Topic 2: Analytics and Reporting | 6% | - Compliance tracking - Shelf share analysis - Retail execution KPIs |
| Topic 3: Visit Execution | 36% | - Surveys - Custom Task - Direct Store Delivery - Planogram Check - Promotion Check - Inventory Check |
| Topic 4: Integrations | 6% | - Integration with external systems - Data synchronization - Master data management |
| Topic 5: Platform | 10% | - Platform features relevant to Consumer Goods Cloud - Mobile capabilities |
| Topic 6: Data Setup | 36% | - Action Plan Setup - Promotion Setup - Product Setup - Planogram Setup - Store Setup - Retail Store KPI Setup |
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NEW QUESTION # 47
Which statement is correct about Consumer Goods - Einstein Visit Recommendations?
Answer: B
Explanation:
Einstein Visit Recommendations support Next Best Action strategies for determining which retail stores should be recommended for visits. Salesforce allows administrators to configure a recommendation strategy that evaluates relevant records and business criteria and produces prioritized visit recommendations for sales managers and field representatives.
A Next Best Action strategy can load relevant data, apply business rules, generate scores and reasons, and return recommendations that support store-visit planning. When a user creates a Visit Recommendation Request, the selected recommendation strategy is executed for the specified store and date context. Salesforce can also incorporate prediction information from Einstein Discovery when organizations require model-based recommendations.
The architecture separates recommendation logic from visit execution. Administrators can therefore create multiple strategies for different business priorities-for example, prioritizing stores with declining inventory, important upcoming promotions, or revenue opportunities. Salesforce documentation specifically supports both flow-based strategies and Next Best Action strategies for Einstein Visit Recommendations, enabling organizations to select the implementation approach that aligns with their planning logic and scalability requirements.
Accordingly, the ability to create Visit Recommendations through a Next Best Action Strategy is a standard supported configuration.
Study Guide Topics:Visit Planning - > Einstein Visit Recommendations - > Next Best Action - > Recommendation Strategies - > Visit Prioritization
NEW QUESTION # 48
Northern Trail Outfitters (NTO) is expanding quickly and wants to improve their reps productivity. Business leadership has expressed their desire to leverage Salesforce Einstein Vision to accomplish this. What are the three recommended steps for setting up Einstein Vision with Consumer Goods Cloud for automatic detection of products on the shelf?
Answer: B,C,E
Explanation:
To set up Einstein Vision with Consumer Goods Cloud for automatic detection of products on the shelf, the following steps are recommended:
Enable Einstein Object Detection, which is a feature that allows you to detect and count multiple objects within an image.
Upload the training pictures as attachments to the planogram for Einstein Object Detection to work. A planogram is a visual representation of how products should be arranged on a shelf. The training pictures should show the actual shelf images with the products labeled and annotated.
Train Einstein Vision Models with marketing images of products to yield optimal results. Marketing images are high-quality images that show the product details clearly and consistently. Training with marketing images can improve the accuracy and performance of the object detection models. Verified Reference: [Salesforce Consumer Goods Cloud Implementation Guide], page 23-24.
NEW QUESTION # 49
A B2B communications company routinely manages intricate product configurations with over 1000 line items, leading to notable operational complexities. The company is concerned about the performance and scalability of the solution as the order volume is expected to increase progressively.
Which Salesforce Communications Cloud solution would you recommend to streamline the configure, price, and quote (CPQ) process and address the customer's performance and scalability concerns?
Answer: D
Explanation:
For B2B telecom companies dealing with complex configurations exceeding 1000 line items, the only Salesforce Communications Cloud solution purpose-built for performance, scalability, and large enterprise quoting is Enterprise Sales Management (ESM).
ESM enhances the CPQ experience by supporting:
Extremely high cart volumes (hundreds to thousands of lines)
Multi-site, multi-location enterprise networks
Enterprise-grade discounting and contract structures
Scalable pricing, validation, and asset handlings
Better separation of commercial vs. technical configurations
Options A, C, and D do not address enterprise-scale CPQ needs with thousands of line items. Large Account Sales Management focuses on account planning, not CPQ performance. Multiplay Subscription Management and Multi-site CPQ do not solve the scalability challenge.
NEW QUESTION # 50
Which Lightning component can an admin add to a Consumer Goods assessment task record page?
Answer: D
Explanation:
https://help.salesforce.com/s/articleView?id=sf.retail_task_admin_create_assessment_task_record_page.htm&type=5
NEW QUESTION # 51
What 3 actions should a consultant take during setup to ensure Einstein Vision works when deployed to field users?
Answer: A,B,D
Explanation:
An Einstein object-detection implementation depends on three essential elements: a suitable training dataset, a properly trained and evaluated model, and appropriate user access to the functionality.
The implementation begins by collecting representative images of the products or objects that must be detected. For object detection, the training images require labeled bounding boxes identifying the position and dimensions of each object. These examples are uploaded as a dataset and used by the training process to create an object-detection model.
The trained model should then be evaluated before deployment. Salesforce ' s model-training architecture reserves data for testing and provides model information that allows implementers to evaluate the model ' s detection performance. Reviewing model quality before exposing the capability to field representatives is essential because representative training data and adequate model performance directly affect detection results.
Finally, the field users who execute the functionality require the relevant access and permissions. Permissions are part of the Salesforce security model and determine whether users can access the required Consumer Goods and Einstein functionality.
OCR configuration and competitor-suppression datasets are not baseline requirements for this object- detection setup.
Study Guide Topics:Platform - > Einstein Vision - > Object Detection - > Dataset - > Model Training - > User Permissions
NEW QUESTION # 52
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