Northern Trail Outfitters wants to implement Data Cloud and has several use cases in mind.
Which two use cases are considered a good fit for Data Cloud? Choose 2 answers
Correct Answer:AC
Data Cloud is a data platform that can help customers connect, prepare, harmonize, unify, query, analyze, and act on their data across various Salesforce and external sources. Some of the use cases that are considered a good fit for Data Cloud are:
✑ To ingest and unify data from various sources to reconcile customer identity. Data Cloud can help customers bring all their data, whether streaming or batch, into Salesforce and map it to a common data model. Data Cloud can also help customers resolve identities across different channels and sources and create unified profiles of their customers.
✑ To use harmonized data to more accurately understand the customer and business impact. Data Cloud can help customers transform and cleanse their data before using it, and enrich it with calculated insights and related attributes. Data Cloud can also help customers create segments and audiences based on their
data and activate them in any channel. Data Cloud can also help customers use AI to predict customer behavior and outcomes.
The other two options are not use cases that are considered a good fit for Data Cloud. Data Cloud does not provide features to create and orchestrate cross-channel marketing messages, as this is typically handled by other Salesforce solutions such as Marketing Cloud. Data Cloud also does not eliminate the need for separate business intelligence and IT data management tools, as it is designed to work with them and complement their capabilities.
References:
✑ Learn How Data Cloud Works
✑ About Salesforce Data Cloud
✑ Discover Use Cases for the Platform
✑ Understand Common Data Analysis Use Cases
An organization wants to enable users with the ability to identify and select text attributes from a picklist of options.
Which Data Cloud feature should help with this use case?
Correct Answer:A
Value suggestion is a Data Cloud feature that allows users to see and select the possible values for a text field when creating segment filters. Value suggestion can be enabled or disabled for each data model object (DMO) field in the DMO record home. Value suggestion can help users to identify and select text attributes from a picklist of options, without having to type or remember the exact values. Value suggestion can also reduce errors and improve data quality by ensuring consistent and valid values for the
segment filters. References: Use Value Suggestions in Segmentation, Considerations for Selecting Related Attributes
Luxury Retailers created a segment targeting high value customers that it activates through
Marketing Cloud for email communication. The company notices that the activated count is smaller
than the segment count. What is a reason for this?
Correct Answer:B
Data Cloud requires a Contact Point for Marketing Cloud activations, which is
a record that links an individual to an email address. This ensures that the individual has given consent to receive email communications and that the email address is valid. If the individual does not have a related Contact Point, they will not be activated in Marketing Cloud. This may result in a lower activated count than the segment count. References: Data Cloud Activation, Contact Point for Marketing Cloud
Cumulus Financial created a segment called High Investment Balance Customers. This is a foundational segment that includes several segmentation criteria the marketing team should consistently use.
Which feature should the consultant suggest the marketing team use to ensure this consistency when creating future, more refined segments?
Correct Answer:A
Nested segments are segments that include or exclude one or more existing segments. They allow the marketing team to reuse filters and maintain consistency in their data by using an existing segment to build a new one. For example, the marketing team can create a nested segment that includes High Investment Balance Customers and excludes customers who have opted out of email marketing. This way, they can leverage the foundational segment and apply additional criteria without duplicating the rules. The other options are not the best features to ensure consistency because:
✑ B. A calculated insight is a data object that performs calculations on data lake objects or CRM data and returns a result. It is not a segment and cannot be used for activation or personalization.
✑ C. A data kit is a bundle of packageable metadata that can be exported and imported across Data Cloud orgs. It is not a feature for creating segments, but rather for sharing components.
✑ D. Cloning a segment creates a copy of the segment with the same rules and filters. It does not allow the marketing team to add or remove criteria from the original segment, and it may create confusion and
redundancy. References: Create a Nested Segment - Salesforce, Save Time with Nested Segments (Generally Available) - Salesforce, Calculated Insights - Salesforce, Create and Publish a Data Kit Unit | Salesforce Trailhead, Create a Segment in Data Cloud - Salesforce
Northern Trail Outfitters (NTO) wants to send a promotional campaign for customers that have purchased within the past 6 months. The consultant created a segment to meet this requirement.
Now, NTO brings an additional requirement to suppress customers who have made purchases within
the last week.
What should the consultant use to remove the recent customers?
Correct Answer:B
The consultant should use B. Segmentation exclude rules to remove the recent customers. Segmentation exclude rules are filters that can be applied to a segment to exclude records that meet certain criteria. The consultant can use segmentation exclude rules to exclude customers who have made purchases within the last week from the segment that contains customers who have purchased within the past 6 months. This way, the segment will only include customers who are eligible for the promotional campaign. The other options are not correct. Option A is incorrect because batch transforms are data
processing tasks that can be applied to data streams or data lake objects to modify or enrich the data. Batch transforms are not used for segmentation or activation. Option C is incorrect because related attributes are attributes that are derived from the relationships between data model objects. Related attributes are not used for excluding records from a segment. Option D is incorrect because streaming insights are derived attributes that are calculated at the time of data ingestion. Streaming insights are not used for excluding records from a segment. References: Salesforce Data Cloud Consultant Exam
Guide, Segmentation, Segmentation Exclude Rules
Luxury Retailers created a segment targeting high value customers that it activates through Marketing Cloud for email communication. The company notices that the activated count is smaller than the segment count.
What is a reason for this?
Correct Answer:A
The reason for the activated count being smaller than the segment count is A. Data Cloud enforces the presence of Contact Point for Marketing Cloud activations. If the individual does not have a related Contact Point, it will not be activated. A Contact Point is a data model object that represents a channel or method of communication with an individual, such as email, phone, or social media. For Marketing Cloud activations, Data Cloud requires that the individual has a related Contact Point of type Email, which contains a valid email address. If the individual does not have such a Contact Point, or if the Contact Point is missing or invalid, the individual will not be activated and will not receive the email communication. Therefore, the activated count may be lower than the segment count, depending on how many individuals in the segment have a valid email Contact Point. References: Salesforce Data Cloud Consultant Exam Guide, Contact Point, Marketing Cloud Activation