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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Integrations | 6% | - System connectivity
|
| Topic 2: Platform | 10% | - Core platform configuration
|
| Topic 3: Visit Planning | 6% | - Territory and route management
|
| Topic 4: Data Setup | 36% | - Consumer Goods Cloud data model
|
| Topic 5: Analytics | 6% | - Reporting and KPIs
|
| Topic 6: Visit Execution | 36% | - In-store process management
|
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NEW QUESTION # 37
Northern Trail Outfitters (NTO) places a high value on understanding how their endcaps are performing.
What should be recommended to NTO to ensure they can capture this data?
Answer: B
Explanation:
Endcaps should be represented as In-Store Locations and In-Store Location Categories, with Retail Store KPIs specifically configured for that merchandising context. This allows NTO to measure endcap performance independently from primary shelves, checkout counters, backrooms, or other store areas.
Salesforce ' s Agentforce Consumer Goods data model supports In-Store Location categories precisely for this purpose. Similar physical locations across stores can be categorized-for example, Endcap Displays-and Retail Store KPIs can then use that category to define the measurements and targets applicable to those locations.
Salesforce ' s own Retail Execution configuration examples demonstrate creating Retail Store KPIs specifically for the Endcap Displays category. A promotion-compliance KPI can include the Retail Store Group, Endcap Displays as the In-Store Location Category, the relevant Assessment Indicator Definition, Promotion, Product Category, and a Boolean target value. This allows field representatives to capture endcap- specific performance during visits while managers analyze the resulting Retail Visit KPI data separately.
Creating Retail Store record types or unrelated custom objects would not provide the appropriate KPI granularity. Dedicated KPI configuration for the endcap context uses the standard Consumer Goods data model and provides targeted merchandising measurement.
Study Guide Topics:Data Setup - > In-Store Locations - > Endcap Displays - > Retail Store KPI - > Assessment Indicators
NEW QUESTION # 38
A company called Alpine is running a ' buy one get one free ' (BOGO) promotion for all energy bars and sending out merchandisers to ensure that their retail customers are running it correctly. At what level should Retail Store KPIs be defined for a promotional end cap audit and also to minimize records created?
Answer: B
Explanation:
Because the promotion applies to all energy bars, the Retail Store KPI should be configured at the Product Category level. Salesforce supports promotion checks at the Product Category, individual Product, and General Promotion levels. Product Category is the appropriate level when a promotional activity applies uniformly to a group of related products.
A category-level configuration minimizes administrative overhead because a single KPI configuration can represent the target for the complete energy-bar category rather than requiring individual KPI records for every SKU. Salesforce allows the administrator to associate a Product Category with a Retail Store KPI together with the Assessment Indicator Definition, Retail Store Group, In-Store Location Category, promotion, KPI type, and target value.
An SKU-level configuration would be appropriate when each individual product requires separate measurement or targets. In this scenario, however, the same BOGO promotion applies across the full energy- bar category, so SKU-specific records would unnecessarily increase data volume and maintenance.
Custom Context applies primarily to custom assessment tasks rather than standard promotion-check configuration. Consequently, Product Category provides the correct granularity while supporting scalable and maintainable Retail Store KPI administration.
Study Guide Topics:Data Setup - > Promotions - > Product Categories - > Retail Store KPI - > Promotion Checks
NEW QUESTION # 39
Which statement is correct about Consumer Goods- Einstein Visit Recommendations?
Answer: D
Explanation:
Einstein Visit Recommendations take into account factors like store operating hours to ensure that suggested visits are feasible and practical.
NEW QUESTION # 40
Which three Consumer Goods Cloud(CGC) objects are linked to the product2 object in the CGC data model?
Answer: B,C,D
Explanation:
In the Consumer Goods Cloud data model, several objects are linked to the Product2 object. These include Assortment Product, Assessment Task Product, and Promotion Product. This linkage is essential for comprehensive product management within the Consumer Goods Cloud.
NEW QUESTION # 41
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: D
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 # 42
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