Explanation:
This question tests knowledge of structuring retail execution data to provide location context for field tasks. In CGC, the In-Store Location object is the standard, scalable way to map the physical layout of a store (e.g., aisles, shelves, coolers). Associating products to these predefined locations allows the system to automatically inform field reps where to find items during tasks like inventory checks, ensuring efficiency and accuracy.

Correct Option:

A. Create an In-Store Location called 'Frozen Food Aisle'.
This is the foundational first step. The consultant must create this master location record. Subsequently, this In-Store Location can be linked to relevant Products and to the specific Retail Store. Once configured, tasks generated for those products at that store will display the "Frozen Food Aisle" location to the field rep.

Incorrect Option:

B. Create a record type called 'Frozen Food Aisle' on the task.
Record types control page layouts and picklist values for types of tasks (e.g., Inventory Check, Planogram). They are not used to specify variable, store-specific physical locations for individual products.

C. Create a picklist field called 'location' to document the Frozen Food Aisle.
While functional, this is a custom, less scalable approach. CGC provides the dedicated In-Store Location object for this purpose, which supports hierarchies, associations to multiple stores, and integration with other features like planograms.

D. Nothing as Product2 captures that the product is frozen.
The Product2 record can indicate a product category (e.g., Frozen Food), but it does not specify the physical location within a specific store (e.g., Aisle 7). This store-level mapping is essential for execution tasks.

E. Create a record type called 'Frozen Food Aisle' on the retail store.
Record types on the Retail Store object could categorize store types (e.g., "Supercenter," "Express"). They cannot specify internal aisle locations for product lookup.

Reference:
Consumer Goods Cloud data model documentation emphasizes the In-Store Location object as the primary method for defining and managing physical store layouts to guide field representatives during store visits.

Explanation:
The Shipment object is the object used in Consumer Goods Cloud (CGC), primarily within the context of Direct Store Delivery (DSD) and Van Sales, that allows for the administrative setup of inventory transport from a warehouse or vehicle (Source Location) to a retail store (Destination Location). It defines what is being transported and where it is going, which is a key administrative step performed in the back-office Setup before the physical delivery execution.

Correct Option:

A. Shipment:
This object is a standard Salesforce object that is heavily utilized in CGC for DSD. It represents the actual consignment or transport of products to be delivered. In the setup phase, an administrator or back-office user associates a Shipment record with a Delivery Task to define the inventory (via the related ProductTransfer object) that the driver will be delivering during a specific store visit. It's the core object for setting up the inventory logistics.

Incorrect Option:

B. DeliveryTask:
While central to DSD, the DeliveryTask object is primarily the execution object. It is a type of task that field users (drivers/sales reps) see and complete on the mobile app during a store visit. It is usually created automatically via an Action Plan Template and then linked to the administrative Shipment record by a back-office user, but it's not the exclusive setup object.

C. Order:
The standard Order object is used to capture a customer's request for products. In DSD, an Order can be fulfilled by a delivery, but the Order itself is a sales object, not an object exclusively used in the setup of the delivery/shipment logistics. Orders can be placed, and then a shipment is created to fulfill it.

D. ProductTransfer:
This object is used to define the specific products and quantities within a Shipment or to track transfers between locations (like from the vehicle to the store). It is a detail object related to the Shipment object. The Shipment record itself is the higher-level object used in setup to initiate the transport.

Reference:
Consumer Goods Cloud Data Model for Direct Store Delivery (DSD), specifically the relationship between Shipment, Delivery Task, and Product Transfer objects.

Explanation:
This question checks knowledge of the standard Key Performance Indicator (KPI) types available for tracking retail store performance within Consumer Goods Cloud. Retail Store KPIs are quantitative measurements used in surveys and assessments. The platform provides a defined set of KPI Type picklist values that determine how the KPI's numeric data is categorized and interpreted.

Correct Option:

A. Units: This KPI type measures product volume, such as the number of items sold or in stock.

D. Facing: This KPI type measures shelf space, specifically the number of product facings on the shelf.

E. Revenue: This KPI type measures monetary sales value.

These three are standard, supported picklist values for the KPI Type field on the Retail Store KPI object, allowing field reps to record different quantitative aspects of in-store execution.

Incorrect Option:

B. Price:
While price is a critical metric, it is not a standard KPI Type for tracking performance data entered by field reps. Price is typically managed as a field on the Product or Pricebook entry, or as part of a promotion. KPIs focus on measurable outcomes like units sold or revenue generated from that price.

C. Promotion:
Promotion is a catalyst for performance, not a performance measurement type itself. The effectiveness of a promotion would be measured using supported KPI Types like Units or Revenue. Promotion is a separate object in CGC.

Reference:
The Salesforce Consumer Goods Cloud Object Reference for the Retail Store KPI object lists the standard picklist values for the KPI Type field, which includes Facing, Revenue, and Units (among others like Distribution). Price and Promotion are not included in this standard list.

Explanation:
The requirement is to check the compliance of high-value assets and, if non-compliant, automatically trigger an action plan. The most low-code/no-code approach in Consumer Goods Cloud (CGC) is to leverage the standard Retail Execution assessment task types (like Inventory Check, Planogram Check) combined with a Salesforce Flow for automation. An Inventory Check task is the most appropriate standard task for auditing physical items like assets, and Flow can handle the logic to determine compliance and trigger the follow-up action plan.

Correct Option:

A. Use an inventory check task with flow:
This is the recommended approach for minimal custom code. CGC's Inventory Check task type can be configured to include specific questions about an asset's status or condition using an Assessment Indicator Definition that captures a Boolean (Yes/No or Compliant/Non-Compliant) value. A Flow can then be configured to run immediately after the task is completed, checking that Boolean value. If the value is 'Non-Compliant' (False), the Flow can easily create a new record (like an Asset Repair task or a follow-up Visit) to trigger the correction action plan.

Incorrect Option:

B. Use a custom task with flow:
While a custom task can be used, it's generally best practice to utilize an out-of-the-box (OOTB) task type when a suitable one exists, such as the Inventory Check. Creating a Custom Task is typically reserved for activities that don't fit any of the standard types (Inventory, Promotion, Planogram, Survey). Using the standard Inventory Check task provides OOTB mobile app features and data model structure, making it more efficient than creating a custom task, thus this option is less optimal.

C. Use a promotion check task with apex:
Promotion Check tasks are specifically designed for auditing the placement and execution of sales promotions, such as display materials, pricing, and shelf presence. This is not the correct standard task type for checking the physical status and compliance of a high-value asset like a cooler or display unit. Furthermore, using Apex introduces custom code, which the requirement explicitly seeks to limit in favor of declarative tools like Flow.

D. Use a custom task with apex:
This option involves two unnecessary customizations: creating a Custom Task when a standard one (Inventory Check) would suffice, and using Apex (code) when the powerful, low-code Flow automation tool is more appropriate for a simple compliance check and record creation trigger. This approach violates the principle of limiting custom code and using OOTB features.

Reference:
Consumer Goods Cloud Retail Execution: Assessment Task Definitions (Inventory Check) and Salesforce Flow for Automation.

Explanation:
Store Action Plan Templates allow managers to pre-define recommended tasks for store visits, ensuring consistency and focus. In CGC, these templates must be associated with a specific context to determine where they are applicable. The platform supports defining these templates at three hierarchical levels, from broad groups down to specific store sections.

Correct Option:

B. Retail Store Group: Templates can be defined for a group of stores (e.g., "All Premium Tier Stores") to apply a standard set of recommendations across that segment.

C. Retail Store: Templates can be defined for a single, specific store to provide highly tailored recommendations for that individual location.

D. In-Store Location:Templates can be defined for a specific area within a store (e.g., "Checkout Aisles"), allowing for micro-level task recommendations focused on a particular section, regardless of the overall store.

Incorrect Option:

A. Location:
While "Location" might sound similar to In-Store Location, it is not a standard object in the CGC hierarchy for associating Action Plan Templates. The precise term is In-Store Location (D).

E. Account:
The CGC model uses the Retail Store object as the primary point of interaction for field execution, not the generic Salesforce Account object. Action Plan Templates are specifically designed for the retail execution layer (Store, Store Group, In-Store Location), not the generic account layer.

Reference:
Salesforce Help Article: "Create a Store Action Plan Template" explicitly states that when creating a template, you "select the scope: a retail store, retail store group, or in-store location." This confirms the three supported association levels.

Explanation:
This question focuses on the prerequisite setup steps to enable and use Einstein Vision's automated product detection for shelf audits within CGC. The process involves activating the AI service, preparing the visual recognition model with the right product images, and then creating the specific field task type that utilizes this technology.

Correct Option:

B. Enable Einstein Object Detection:
This is the fundamental administrative step. An admin must enable the Einstein Object Detection permission and set up the connected app in the Salesforce setup to make the AI service available for use within CGC.

D. Define planogram check task:
The field execution mechanism for using this technology is the "Planogram Check" assessment task. This task type is configured to use the trained Einstein Vision model to compare a photo taken in-store against a reference planogram image.

E. Train Einstein Vision Models with marketing images of products to yield optimal results:
For accurate automated detection, the Einstein Vision model must be trained. This involves creating a dataset and labeling it with clear, high-quality product images (typically marketing or studio shots) to teach the model what each product looks like.

Incorrect Option:

A. Setup in store location and associate planogram:
While important for overall store layout and task organization, setting up In-Store Locations is not a required step for enabling the core Einstein Vision detection functionality. It is more related to task routing and reporting.

C. Upload the training pictures as attachments to the planogram for Einstein Object Detection to work:
This is incorrect on two points. First, training images are uploaded to a Dataset in Einstein Vision, not as simple attachments to a planogram. Second, the reference image attached to a planogram task is for visual comparison during a check, not for training the core AI model.

Reference:
Salesforce Help Article: "Set Up Einstein Object Detection for Consumer Goods Cloud" outlines the key steps: 1. Enable the feature, 2. Train a model with product images in Einstein Vision, and 3. Create a Planogram Check task that uses the trained model.

Explanation:
When building custom pages in the Consumer Goods Cloud mobile app using the CG Mobile Designer (Lightning App Builder for mobile), administrators can add specific CG-supported Lightning components to the Visit and Retail Store pages. As of the current release, the officially supported and natively available components for CG Mobile custom pages are Quip Documents, Einstein Predictions, and Custom Object Task List. These components are explicitly listed in the CG Mobile Designer component panel

Correct Option:

B. Quip Documents, Einstein Predictions, and Custom Object Task List

Quip Documents: Allows reps to view and edit live Quip docs (e.g., planograms, sell sheets) directly in the mobile visit.

Einstein Predictions: Displays AI-driven recommendations such as next best action or no-visit predictions on the visit record.

Custom Object Task List: Enables display of tasks from custom objects related to the visit or store (e.g., maintenance tasks, competitor tasks).

Incorrect Options:

A. Quip Documents, Einstein Predictions, and Price Optimization
Price Optimization is not an available Lightning component in CG Mobile Designer; pricing analytics exist in Tableau CRM but cannot be embedded as a component on mobile pages.

C. DEX Electronic Data Interchange (EDI), Custom Object Task List, and Customer Onboarding
DEX (Data Exchange) and EDI are back-end integration features, not mobile page components. Customer Onboarding is not a component in CG Mobile.

D. DEX Electronic Data Interchange (EDI), Price Optimization, and Customer Onboarding
None of these three are actual Lightning components available in the Consumer Goods Mobile Designer palette.

Reference:
Salesforce Help: “Customize Consumer Goods Mobile Pages” → Available Components section (Winter ’25 & Spring ’26 releases)

Trailhead: “Extend Consumer Goods Cloud Mobile Experience” – CG Mobile Designer component list

CG Cloud Release Notes (v16.0+): Supported Lightning components for CG Mobile

Explanation:
Planogram Detection leverages image recognition technology (like Einstein Vision) to analyze pictures of store shelves taken by field reps. By comparing the actual shelf image (the realogram) to the ideal layout (the planogram), the system can automatically and objectively calculate key metrics related to product availability, placement, and space allocation. This automation significantly reduces the time and subjectivity associated with manual shelf audits.

Correct Option:

A. Out of Stock, Share of Shelf, SKU Facings: These are the three most critical and frequently cited metrics derived from automated planogram detection:
Out of Stock (OOS): The system detects empty shelf space where a product is expected to be, or a missing product's label, indicating a stock-out situation. This is often a Boolean or a percentage of missing products.

Share of Shelf: The system calculates the percentage of total visible shelf space (linear or volumetric) occupied by a specific brand, category, or product group compared to competitors.

SKU Facings: The system counts the actual number of individual product items (SKUs) visible from the front on the shelf, which is a direct measure of product visibility and compliance.

Incorrect Option:

B. Out of Stock, Share of Shelf, Brand Facings:
While Brand Facings can be derived by summing the SKU facings for all products belonging to a particular brand, SKU Facings (Option A) is the more granular, fundamental metric that the object detection model directly counts. In the context of a multiple-choice question on the core capabilities of the technology, SKU Facings is considered the primary, most accurate, and most common KPI.

C. Out of Stock, Shelf Size, SKU Facings:
Shelf Size (e.g., linear feet or square area) is a static piece of master data associated with the In-Store Location and Planogram setup. It is not a KPI derived by the visual detection process itself; it is the input context used to calculate metrics like Share of Shelf.

D. Out of Stock, Shelf Size, Brand Facings:
This option includes the incorrect item Shelf Size (a static setup attribute) and the less granular metric Brand Facings, making it a less accurate representation of the core detection KPIs than Option A.

Reference:
Consumer Goods Cloud Retail Execution: Planogram Checks, Assessment Indicator Definitions (for KPI types like Facing, Share of Shelf, and Out of Stock), and Einstein Vision for Retail Execution.

Explanation:
This question addresses designing a mobile-first user experience (UX) for field teams who need simultaneous access to their task list and communication feed. The optimal solution should provide persistent, at-a-glance visibility of messages without requiring constant navigation away from the primary work context (visits/tasks), especially on a tablet's larger screen which can support multi-pane layouts.

Correct Option:

B. Extend the visit List by leveraging the two column layout where one column is the visit list and the second is messages.
This provides the optimal tablet UX. It utilizes the available screen real estate to display both core functions side-by-side. Field reps can monitor real-time messages in a dedicated pane while simultaneously viewing and acting on their visit list, eliminating disruptive context switching.

Incorrect Option:

A. Extend every Consumer Goods Cloud mobile page to add a link to navigate to Chatter.
Adding a link to every page creates clutter and forces repetitive navigation. The rep must leave their current page to check messages and then navigate back, disrupting workflow. It's an inefficient, non-persistent solution.

C. Create a quick action to create a note addressed to a team member.
This is a functional action for sending a message, but it does not address the core requirement to monitor incoming team messages throughout the day. It offers no visibility into the message feed.

D. Display a notification for every message that a team member sends while the Field Rep is on the app.
This would create excessive and disruptive alert fatigue, constantly pulling focus from tasks. Notifications are for critical alerts, not for providing a continuous, browsable message stream, which is what monitoring requires.

Reference:
Salesforce Mobile App Design best practices advocate for context-aware, streamlined interfaces. The Lightning App Builder supports creating dynamic, multi-column layouts for tablets. The described two-column layout is a standard pattern for combining a primary list view with a related, live feed (like Chatter) to enhance productivity without navigation overhead.

Explanation:
In Salesforce Consumer Goods Cloud, when a field rep captures a photo of a defective in-store asset (e.g., cooler, display, or shelf unit) during a visit, the photo is automatically attached as a ContentDocument/ContentVersion record and linked directly to the Visit object. Field Sales Managers can instantly view all photos taken during the visit from the Visit record’s Related tab (Files or Notes & Attachments) or via the CG Mobile photo gallery, regardless of whether an asset check or assessment task was used.

Correct Option:

A. The photo is linked to the visit record
All photos taken in CG Mobile during a store visit are automatically associated with the active Visit record as Files (ContentDocumentLink).

Managers access them from the Visit detail page in Lightning Experience or via standard Salesforce Files related lists.

This is the native out-of-box behavior and does not require additional configuration.

Incorrect Options:

B. The photos linked to the asset record
Standard CG Cloud does not automatically link visit photos to the Asset object. A custom automation (Flow or Apex) would be required, which is not the default behavior.

C. The photo is sent directly to the manager's email
CG Cloud does not automatically email photos to managers upon capture. Email notifications are possible only via custom Flow or Process Builder, not natively.

D. The photo is linked to the asset check task
While photos can be manually attached to an Assessment Task (e.g., asset check task), this is not the automatic default behavior. Out-of-box, photos are always linked to the Visit, not the task.

Reference:
Salesforce Help: “Capture and View Photos in Consumer Goods Cloud Mobile” (Winter ’25–Summer ’26)

Trailhead: “Execute Store Visits with Consumer Goods Cloud Mobile” → Photo Capture section

CG Cloud Known Behavior: Photos are stored as ContentVersion records linked to the Visit via ContentDocumentLink

Explanation:
The Einstein Vision model used for object detection in Consumer Goods Cloud (CGC) for tasks like Planogram Checks and Inventory Checks is a custom-trained deep learning model. It is not automatically functional out-of-the-box for a company's specific products. The model must be explicitly developed and trained by a system administrator or consultant using a collection of high-quality, labeled images of the company's products as they appear on the shelf. This training process is a crucial setup step within the project's development phase.

Correct Option:

D. The model needs to be created as part of the development process using a base set of images:
This is accurate. To correctly identify a client's unique Stock Keeping Units (SKUs) and brands on the shelf, the model must undergo a custom training phase. This involves:

Gathering a base set of images (training data) of the products in various real-world conditions.

Annotating these images with bounding boxes to tell the AI exactly where each product (object) is located in the image and what its label is.

Training the model on this dataset using the Einstein Platform Services (APIs) or the Einstein Playground. This entire process is a structured setup task performed before the solution is rolled out to field reps.

Incorrect Option:

A. The model is created automatically by Einstein based on uploading the perfect image:
This is incorrect. While image quality is important, a single "perfect" image is insufficient. Deep learning models require a large, diverse dataset of images (hundreds or thousands) taken from multiple angles, lighting conditions, and display types to learn to generalize and accurately detect objects in the real world. The model creation is a manual, programmatic training process, not an automatic one.

B. The model is created via crowdsourcing of images available via public copyright licenses:
This is incorrect. The model must be trained on the specific products the client is selling (e.g., NTO backpacks, specific soda cans). Using public domain or crowdsourced images would not allow the model to accurately identify the unique SKUs, branding, and packaging of the client's products, rendering it useless for compliance checks.

C. The model is created in store as reps perform their daily tasks during phase 1 rollout:
This is incorrect. While images captured by reps can be used for model refinement (a feedback loop), the initial, functional model must be pre-trained and deployed before the rollout. Relying on field reps' initial images for the creation of the model would mean the detection capabilities are non-existent or unreliable during Phase 1, crippling the core retail execution functionality.

Reference:
Salesforce Einstein Vision documentation, focusing on Custom Model Training and Object Detection API requirements.

Explanation:
This question tests knowledge of the purpose and data focus of different pre-built Tableau CRM dashboards in CGC. A Field Sales Manager needs to analyze store-level execution metrics (KPIs like Facing, Share of Shelf, etc.) to identify underperforming locations. The correct dashboard must aggregate and visualize these specific Retail Store KPI trends at the store level.

Correct Option:

A. Store Performance Dashboard:
This dashboard is specifically designed to analyze the performance of individual retail stores. It visualizes key Retail Execution KPIs (e.g., Planogram Compliance, Out-of-Stock) over time, allowing a manager to easily spot trends, compare stores, and identify which ones have a decline in KPIs and thus need attention.

Incorrect Option:

B. Team Performance Dashboard:
This dashboard focuses on the productivity and activity metrics of the field team members or reps (e.g., visits completed, tasks per day). It is used to manage rep performance, not to diagnose store-level KPI problems.

C. Lost Visit Store Performance Dashboard:
This dashboard analyzes the impact of missed store visits (Lost Visits) on sales and KPIs. While it involves store data, its primary lens is understanding the consequence of visit coverage gaps, not providing a general analysis of all stores' KPI trends.

D. Product Performance Dashboard:
This dashboard focuses on the performance of products across stores or regions (e.g., sales velocity, distribution). It is used for brand or category management, not for assessing the execution health of specific retail store locations.

Reference:
The Consumer Goods Cloud Tableau CRM dashboard descriptions identify the Store Performance Dashboard as the tool for managers to monitor and compare store-level execution metrics and compliance over time, directly fulfilling the need to identify stores with declining KPIs.