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Salesforce Marketing-Cloud-Intelligence Exam Syllabus Topics:

Topic
Details

Topic 1

Design Feasibility: This area evaluates the ability to identify valid and invalid solutions from solution design diagrams, ensuring effective and scalable platform designs.

Topic 2

Harmonization Center (Patterns
Data Classification
Validation): Salesforce marketing professionals will learn about the Harmonization Center’s capabilities, including classification rules, validation lists, patterns, and harmonized dimensions to ensure data reliability.

Topic 3

Data Integration Code Ability: This section evaluates proficiency with common Marketing Cloud Intelligence functions, enabling Salesforce marketing professionals to integrate diverse data sources effectively for comprehensive marketing intelligence.

Topic 4

General Functionalities: In this topic, Salesforce marketing professionals will explore core functionalities of Marketing Cloud Intelligence. It measures understanding of platform features critical to data-driven marketing strategies and insights.

Topic 5

Data Fusion: This topic focuses on the use cases and properties of Data Fusion, equipping marketing professionals to merge datasets effectively for comprehensive marketing insights.

Topic 6

CRM: This topic tests knowledge of CRM properties and their behavior within Marketing Cloud Intelligence. This knowledge is crucial for syncing customer relationship data with marketing campaigns.

Topic 7

Calculated Dimensions & Measurements: This section measures skills in using calculated objects, recognizing aggregation types, and employing these tools for tailored marketing analytics.

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Salesforce Marketing Cloud Intelligence Accredited Professional Exam Sample Questions (Q44-Q49):

NEW QUESTION # 44
A client created a new KPI: CPS (Cost per Sign-up).
The new KIP is mapped within the data stream mapping, and is populated with the following logic: (Media Cost) / Sign-ups) As can be seen in the table below, CPS was created twice and was set with two different aggregations:

From looking at the table, what are the aggregation settings for each one of the newly created KPIs?

Answer: D

Explanation:
The KPI CPS (Cost per Sign-up) would be calculated by dividing the 'Media Cost' by 'Sign-ups'. The table indicates that CPS is set with two different aggregations. In option C, CPS #1 is set to 'AUTO', which allows the system to decide the best aggregation method based on the context. CPS #2 is set to 'SUM', which indicates that the individual costs per sign-up are summed up across multiple records to provide a total cost per sign-up.

NEW QUESTION # 45
A technical architect is provided with the logic and Opportunity file shown below:
The opportunity status logic is as follows:
For the opportunity stages "Interest", "Confirmed Interest" and "Registered", the status should be "Open".
For the opportunity stage "Closed", the opportunity status should be closed Otherwise, return null for the opportunity status

Given the above file and logic and assuming that the file is mapped in a GENERIC data stream type with the following mapping:
"Day" - Standard "Day" field
"Opportunity Key" > Main Generic Entity Key
"Opportunity Stage" - Main Generic Entity Attribute
"Opportunity Count" - Generic Custom Metric
A pivot table was created to present the count of opportunities in each stage. The pivot table is filtered on Jan
11th. What is the number of opportunities in the Interest stage?

A. 0
B. 1
C. 2
D. 3

Answer: C

Explanation:
Since the pivot table is filtered on January 11th and the provided Opportunity file does not show any records dated January 11th, there are zero opportunities in the Interest stage for that date. Salesforce Marketing Cloud Intelligence allows users to create pivot tables and filter data basedon specific criteria, such as dates. In this case, the filter would exclude all rows that do not match the specified date, resulting in a count of zero for the Interest stage. This would apply to any stage since there are no records for January 11th. Reference can be made to Salesforce Marketing Cloud Intelligence documentation on filtering and pivot tables.

NEW QUESTION # 46
A technical architect is provided with the logic and Opportunity file shown below:
The opportunity status logic is as follows:
For the opportunity stages "Interest", "Confirmed Interest" and "Registered", the status should be "Open".
For the opportunity stage "Closed", the opportunity status should be closed.
Otherwise, return null for the opportunity status.

Given the above file and logic and assuming that the file is mapped in a GENERIC data stream type with the following mapping:
"Day" - Standard "Day" field
"Opportunity Key" > Main Generic Entity Key
"Opportunity Stage" - Generic Entity key 2
A pivot table was created to present the count of opportunities in each stage. The pivot table is filtered on Jan 7th -11th.Which option reflects the stage(s) the opportunity key 123AA01 is associated with?

A. Confirmed interest
B. Interest & Registered
C. interest
D. Confirmed Interest & Registered

Answer: B

Explanation:
Filtering the pivot table on January 7th-11th, we see that the Opportunity Key 123AA01 appears on January 6th with the stage 'Interest' and then on January 10th with the stage 'Registered'. Even though the 'Interest' stage is not within the filtered dates, it is the initial stage of the opportunity, so it should be counted along with the 'Registered' stage which falls within the filter range.

NEW QUESTION # 47
What is the relationship between "Media Buy Key" and "Campaign Key"?

A. One-to-one
B. One-to-many (one Media Buy Key has many Campaign Keys)
C. Many-to-many
D. Many-to-one (one Campaign Key has many Media Buy Keys)

Answer: D

Explanation:
Typically, 'Campaign Key' is a unique identifier for a specific marketing campaign, while 'Media Buy Key' refers to the purchases of advertising space associated with that campaign. A campaign can have multiple media buys, so the relationship is many-to-one, with many media buys (Media Buy Keys) associated with a single campaign (Campaign Key).

NEW QUESTION # 48
What areunstable measurements?

A. Measurements for which Aggregation Settings are set as 'Auto' and Granularity is set as 'None'.
B. Measurements that are set with the LIFETIME aggregation function
C. Measurements for which Aggregation Settings are set as 'Not Auto' and Granularity is set as 'Not Empty'.
D. Measurements for which Aggregation Settings are set as 'Not Auto' and Granularity is set as 'None'.

Answer: D

Explanation:
Unstable measurements refer to metrics that are not aggregated in a standard manner across different grains of data, which can result in inconsistent or unpredictable results when reporting across different dimensions or time frames.
* Option C describes a scenario where measurements have manual (Not Auto) aggregation settings, meaning they do not automatically adjust to theaggregation level of the report. Combined with a Granularity setting of 'None', this can lead to instability because the metric isn't bound to a specific granularity, which can cause data inconsistencies or misinterpretations when analyzed at varying levels of detail.

NEW QUESTION # 49
......

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