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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Store Execution Configuration | 12% | - Configuration of Store Survey and Feedback - Configuration of Store Execution Process - Configuration of Assortment Monitoring - Configuration of Planogram Compliance |
| Topic 2: Visit Planning and Execution Configuration | 15% | - Configuration of Photo Capture and Survey - Configuration of Visit Tasks and Task Types - Configuration of Order Capture and Order Submission - Configuration of Inventory Checks and Product Listings - Configuration of Promotion Checks and Promotion Details - Configuration of Visit Plans and Visit Plan Targets |
| Topic 3: Admin and Configuration | 12% | - Reports and Dashboards - User Setup and Permissions - Mobile Configuration - Consumer Goods Cloud Data Model |
| Topic 4: Store Execution | 15% | - Store Execution Process - Assortment Monitoring - Planogram Compliance - Store Survey and Feedback |
| Topic 5: Visit Execution | 23% | - Order Capture and Order Submission - Promotion Check and Promotion Details - Inventory Check and Product Listing - Visit Execution Process - Photo Capture and Survey - Visit Tasks and Task Types |
| Topic 6: Visit Planning | 23% | - Territory Management - Visit Schedule and Frequency - Visit Plan and Visit Plan Targets - Visit Planning Process |
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The Salesforce AP-204 desktop-based practice exam is compatible with Windows-based computers and only requires an internet connection for the first-time license validation. The web-based Consumer Goods Cloud Accredited Professional (AP-204) practice test is accessible on any browser without needing to install any separate software. Finally, the Consumer Goods Cloud Accredited Professional (AP-204) dumps pdf is easily portable and can be used on smart devices or printed out.
NEW QUESTION # 33
A Field Rep is having challenges measuring their share-of-shelf due to a recent change in packaging to a competitor's product, which makes their products look almost identical. When using Einstein, the competitor's product was marked incorrectly as the rep's product. What should the rep do to prevent this from happening in the future?
Answer: D
Explanation:
To prevent Einstein from marking the competitor's product incorrectly as their own product when measuring their share-of-shelf, the field rep should edit product tags. Product tags are labels that identify and count products in an image using Einstein Vision. Einstein Vision is a feature that uses artificial intelligence to detect and count objects in an image. By editing product tags, the field rep can correct any errors or inaccuracies in the object detection process and ensure that their own products and their competitor's products are tagged correctly. Verified Reference: [Salesforce Consumer Goods Cloud Implementation Guide], page 24.
NEW QUESTION # 34
Which three fields are available on the Retail Store object that differentiate them from the Account object?
Answer: B,C,E
Explanation:
The Retail Store object includes retail-execution-specific attributes such as Delivery Method, Preferred Visit Hours, and Payment Method, which provide operational details required for managing field sales and distribution activities.
Delivery Method describes how orders are delivered to the store and supports logistics and Direct Store Delivery planning. Preferred Visit Hours identifies the periods during which field representatives should ideally visit the outlet and contributes to effective visit and route planning. Payment Method records the payment arrangement applicable to the retail location and supports store-specific commercial execution.
Salesforce ' s Retail Store data model explicitly includes fields corresponding to DeliveryMethod, PreferredVisitHoursText, and PaymentMethodId. It also contains attributes for delivery frequency, opening and closing times, recommended visit frequency, pricing strategy, primary contact, priority, and related retail- location information.
Shipping Address is a standard concept already available in the Account data model and therefore does not serve as a distinguishing Retail Store attribute. Operating Hours are handled through the broader operating- hours model and relationship rather than being one of the three specific Retail Store fields represented by the choices.
These store-specific attributes allow Agentforce Consumer Goods to distinguish the operational requirements of an individual physical outlet from its parent customer Account.
Study Guide Topics:Data Setup - > Retail Store - > Delivery Method - > Preferred Visit Hours - > Payment Method
NEW QUESTION # 35
Alpine, a Consumer Goods company, is launching a new division dedicated to fresh baked breads delivered to restaurants and groceries. In an effort to move product rapidly and pick up new clients they need to extend their current customer onboarding process to allow field reps to onboard new customers while on their daily route. Which option is a best practice to complete this requirement ?
Answer: D
Explanation:
The Click2Create function is a feature of Consumer Goods Cloud that allows a field rep to create a new retail store record from the mobile app by tapping on a point of interest on a map. This function automatically fills in the address fields with the data from the map and also allows the field rep to attach a follow up case or lead to onboard the outlet on an onboarding journey. Verified Reference: [Salesforce Consumer Goods Cloud Implementation Guide], page 34-35.
NEW QUESTION # 36
Which of the following is accurate regarding the Einstein Vision model?
Answer: D
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 # 37
A consultant for Northern Trail Outfitters (NTO) company advises NTO to leverage Visit Recommendations for the field team. Which build option ensures the strategy is scalable to meet the requirements of NTO?
Answer: C
Explanation:
For a Visit Recommendation implementation that must scale to production business volumes, the recommendation-selection logic should be implemented using an Apex class.
Salesforce supports Flow-based strategies for Einstein Visit Recommendations, but its documentation explicitly states that the flow-only approach is not scalable for a business use case and recommends using Apex for scalable Visit Recommendation processing.
With Apex, a developer can implement the business logic needed to identify the Retail Stores for which Einstein should generate recommendations. The Apex method can be exposed through an invocable action and incorporated into the recommendation strategy or an associated flow. This architecture provides more control over bulk processing, complex filtering, governor-limit management, reusable logic, and enterprise- scale execution.
Salesforce ' s Visit Recommendation setup documentation supports both Flow and Apex approaches. It specifically provides an Apex-based option to select the list of stores for which recommendations should be generated and then use that Apex action within the recommendation framework.
Workflow Rules and Process Builder are not the supported architectural mechanisms for implementing scalable Einstein Visit Recommendation strategies.
Study Guide Topics:Visit Planning - > Einstein Visit Recommendations - > Apex - > Scalability - > Recommendation Strategy
NEW QUESTION # 38
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