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Salesforce Marketing Cloud Intelligence Accredited Professional Sample Questions:

1. 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?

A)

B)

C)

D)

2. An implementation engineer is requested to extract the first three-letter segment of the Campaign Name values.
For example:
Campaign Name: AFD@Mulop-1290
Desired outcome: AFD
Other examples:

Which formula will return the desired values?

A) EXTRACT(EXTRACT(csv['campaign_name]]/@',1),-,0)
B) EXTRACT(csv[campaign_name!;@',1)
C) EXTRACT(csv[campaign_name'],-,0)
D) LEFT(EXTRACT(csy['campaign_name]],~',0),3)
E) LEFT(EXTRACT(csv[campaign_name'}/-',1),3)

3. An implementation engineer has been provided with the below dataset:

*Note: CPC = Cost per Click
Formula: Cost / Clicks
Which action should an engineer take to successfully integrate CPC?

A) Populate the logic within a custom measurement. Set Aggregation to SUM.
B) Populate the logic within a custom measurement. No need to change Aggregation.
C) Unmap it, as Datorama will calculate it automatically.
D) Populate the logic within a custom measurement. Set Aggregation to AVG.

4. A client wants to integrate their data within Marketing Cloud Intelligence to optimize their marketing insights and cross-channel marketing activity analysis. Below are details regarding the different data sources and the number of data streams required for each source.

What three advantages are gained when using Patterns & Data Classification as the harmonization method for creating the Objective field?

A) Use of code
B) Performance (Performance when loading a dashboard page)
C) Ease of Maintenance
D) Processing (processing time when loading relevant data streams)
E) Scalability

5. Which two statements are correct regarding variable Dimensions in marketing Cloud intelligence's data model?

A) These dimensions are stored at the workspace level
B) These are stand alone dimensions that pertain to the data set itself rather than to a specific entity
C) All variables exist in every data set type, hence are considered as overarching dimensions
D) Variable Dimensions hold a Many-to-Many relationship with its main entity

Solutions: