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Which consideration related to the way Data Cloud ingests CRM data is true?
A. CRM data cannot be manually refreshed and must wait for the next scheduled synchronization,
B. The CRM Connector's synchronization times can be customized to up to 15-minute intervals.
C. Formula fields are refreshed at regular sync intervals and are updated at the next full refresh.
D. The CRM Connector allows standard fields to stream into Data Cloud in real time.
A customer notices that their consolidation rate is low across their account unification. They have mapped Account to the Individual and Contact Point Email DMOs. What should they do to increase their consolidation rate?
A. Change reconciliation rules to Most Occurring.
B. Disable the individual identity ruleset.
C. Increase the number of matching rules.
D. Update their account address details in the data source
Explanation:
Consolidation Rate: The consolidation rate in Salesforce Data Cloud refers to the effectiveness of unifying records into a single profile. A low consolidation rate indicates that many records are not being successfully unified.
Matching Rules: Matching rules are critical in the identity resolution process. They define the criteria for identifying and merging duplicate records.
Solution:
Increase Matching Rules: Adding more matching rules improves the system's ability to identify duplicate records. This includes matching on additional fields or using more sophisticated matching algorithms.
Steps:
Access the Identity Resolution settings in Data Cloud.
Review the current matching rules.
Add new rules that consider more fields such as phone number, address, or other unique identifiers.
Benefits:
Improved Unification: Higher accuracy in matching and merging records, leading to a higher consolidation rate.
Comprehensive Profiles: Enhanced customer profiles with consolidated data from multiple sources.
Which two requirements must be met for a calculated insight to appear in the segmentation canvas? (Choose 2 answers)
A. The metrics of the calculated insights must only contain numeric values.
B. The primary key of the segmented table must be a metric in the calculated insight.
C. The calculated insight must contain a dimension including the Individual or Unified Individual Id.
D. The primary key of the segmented table must be a dimension in the calculated insight.
Explanation:
A calculated insight is a custom metric or measure that is derived from one or more data model objects or data lake objects in Data Cloud. A calculated insight can be used in segmentation to filter or group the data based on the calculated value. However, not all calculated insights can appear in the segmentation canvas. There are two requirements that must be met for a calculated insight to appear in the segmentation canvas:
The calculated insight must contain a dimension including the Individual or Unified Individual Id. A dimension is a field that can be used to categorize or group the data, such as name, gender, or location. The Individual or Unified Individual Id is a unique identifier for each individual profile in Data Cloud.
The calculated insight must include this dimension to link the calculated value to the individual profile and to enable segmentation based on the individual profile attributes. The primary key of the segmented table must be a dimension in the calculated insight. The primary key is a field that uniquely identifies each record in a table. The segmented table is the table that contains the data that is being segmented, such as the Customer or the Order table.
The calculated insight must include the primary key of the segmented table as a dimension to ensure that the calculated value is associated with the correct record in the segmented table and to avoid duplication or inconsistency in the segmentation results.
Northern Trail Outfitters wants to be able to calculate each customer's lifetime value (LTV) but also create breakdowns of the revenue sourced by website, mobile app, and retail channels. How should this use case be addressed in Data Cloud?
A. Nested segments
B. Flow orchestration
C. Streaming data transformations
D. Metrics on metrics
Explanation:
This feature can help Northern Trail Outfitters calculate each customer’s lifetime value (LTV) and create breakdowns of the revenue sourced by different channels. Streaming data transformations allow you to transform and enrich streaming data from different sources using formulas and operators.
Northern Trail Outfitters wants to use some of its Marketing Cloud data in Data Cloud. Which engagement channel data will require custom integration?
A. SMS
B. Email
C. CloudPage
D. Mobile push
Explanation:
CloudPage is a web page that can be personalized and hosted by Marketing Cloud. It is not one of the standard engagement channels that Data Cloud supports out of the box. To use CloudPage data in Data Cloud, a custom integration is required. The other engagement channels (SMS, email, and mobile push) are supported by Data Cloud and can be integrated using the Marketing Cloud Connector or the Marketing Cloud API.
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