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Marketing-Cloud-Intelligence Practice Questions

Question # 1
A client provides the following three files:



Which proposed solution would cause a false connection between the two files?
A. Custom classification
B. Data Classification
C. VLOOKUP in Data Stream B. Vlookup will return “Day” and “Installs”
D. VLOOKUP in Data Stream C. Vlookup will return "MB Name”


C. VLOOKUP in Data Stream B. Vlookup will return “Day” and “Installs”

Explanation: With File A uploaded using the Ads data stream type, the client wishes to create a view incorporating data from Files B & C. A false connection would occur if VLOOKUP in Data Stream B is used incorrectly to return “Day” and “Installs”. In this scenario, VLOOKUP might inaccurately link data based on MB Name between File B and File A or File C, which do not have a "Day" field to correctly join on. Moreover, "Installs" data in File B doesn't exist, soVLOOKUP cannot correctly return this information. The correct method would be to use the "Media Buy New Name" to link File B and File C since they both have this field, ensuring accurate connection and avoiding data mismatches or false connections.

Question # 2
A client has integrated the following files:



The client would like to link the two files in order to view the two KPIs (‘Tasks Completed’ and ‘Tasks Assigned) alongside ‘Employee Name’ and/or ‘Squad’.

The client set the following properties:

+ File Ais set as the Parent data stream

* Both files were uploaded to a generic data stream type.
* Override Media Buy Hierarchies is checked for file A.
* The ‘Data Updates Permissions’ set for file B is ‘Update Attributes and Hierarchy’.

When filtering on the entire date range (1-30/8), and querying employee ID, Name and Squad with the two measurements - what will the result look like?

A. Option A
B. Option B
C. Option C
D. Option D


C. Option C

Explanation: In Marketing Cloud Intelligence, when linking two data streams, the parent data stream (File A) provides the main structure. Since 'Override Media Buy Hierarchies' is checked for File A, the hierarchies from File B will be aligned with File A. Given 'Data UpdatesPermissions' set for file B as 'Update Attributes and Hierarchy', this means that attributes and hierarchy will be updated in the parent file based on the child file (File B), but the child file’s metrics won’t be associated with the parent file’s date.
Hence, when filtering on the entire date range (1-30/8), the resulting view will align with the structure of the parent data stream, showing the KPIs (‘Tasks Completed’ from File A and ‘Tasks Assigned’ from File B) alongside the employee names and squads from the respective files. Since the employee IDs align, the data can be linked properly. However, since the dates do not align (File A data is from 01/08/2019 and File B from 15/08/2019), only attributes from File B will be updated without date association.
The result will look like Option C, where the employee names are corrected based on File B's data, the squads are added from File B, and the tasks_completed and tasks_assigned are displayed from their respective files. The tasks_assigned from File B are shown without date association as File B's date doesn't match with File A's.

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


A. Populate the logic within a custom measurement. No need to change Aggregation.

Explanation: CPC (Cost per Click) is a calculated metric that should be created using a custom measurement based on the formula provided (Cost / Clicks). This calculation does not require a change in the aggregation setting because it is derived from other base metrics that are already aggregated appropriately. In Salesforce Marketing Cloud Intelligence, custom measurements are used to create new metrics from existing data points, and the system will use the underlying data's aggregation to perform the calculation. References: Salesforce Marketing Cloud Intelligence documentation on creating custom measurements and calculated metrics.

Question # 4
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 “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 7th - 10th. How many different stages are presented in the table?
A. 2
B. 1
C. 3
D. 0


C. 3

Explanation: Based on the Opportunity file and considering the filter dates from January 7th to 10th, the different stages presented are 'Interest', 'Confirmed Interest', and 'Registered'. This makes a total of 3 different stages that would be presented in the pivot table. Salesforce Marketing CloudIntelligence allows for the creation of pivot tables that can display counts of entities across different dimensions, in this case, Opportunity Stages.
Reference to Salesforce Marketing Cloud Intelligence documentation that covers data mapping and pivot table creation would support this conclusion.

Question # 5
Client has provided sample flies of their data from the following data sources:
Google Campaign Manager



Please note: • All other measurements were mapped as well to the appropriate fields. • No other mapping manipulations or formulas were implemented. How many records will the merged table hold?
A. 4
B. 8
C. 3
D. Depends on the Data Updates Permissions


A. 4

Explanation: Since the data sources are linked by shared Media Buy names and all other measurements are mapped to appropriate fields without additional manipulations, each unique Media Buy Name from Google DV360 will pair with its corresponding Media Buy Name in Google Campaign Manager. The number of records in the merged table will equal the number of unique Media Buy Names in Google DV360, provided there is a matching name in Google Campaign Manager. The sample shows 4 unique Media Buy Names in Google DV360, thus resulting in 4 records.

Question # 6
A client has integrated data from Facebook Ads, Twitter Ads, and Google Ads in Marketing Cloud Intelligence. For each data source, the data follows a naming convention as shown below:

Facebook Ads Naming Convention - Campaign Name:
Camp|D_CampName#Market_Objective#TargetAge_TargetGender Twitter Ads Naming Convention - Media Buy Name:
Market|TargetAge|Objective|OrderID

' Google Ads Naming Convention - Media Buy Name:

Buying Type_Market_Objective

The client wants to harmonize their data on the common fields between these two platforms (i.e. Market and Objective) using the Harmonization ‘Center.
In addition to the previous details, the client provides the following data sample:



Logic specification:
If a value is not present in the Validation List, return “Not Valid”
If a value is not present in the Classification File, return “Unclassified”.
If the Harmonization center is used to harmonize the above data and files, what table will show the final output?

A. Option A
B. Option B
C. Option C
D. Option D


B. Option B

Explanation: The correct table would be Option B. The harmonization process would identify the 'Market' from the campaign or media buy name based on the delimiter and position rules specified in the naming conventions. The harmonized 'Market' would then be matched against the classification file and validation list. If a value does not match the validation list, it would return 'Not Valid', and if it's not present in the classification file, it would return 'Unclassified'. Option B is the only table showing the 'Not Valid' category which aligns with the logic specification provided.

Question # 7
An implementation engineer is requested to apply the following logic:



To apply the above logic, the engineer used only the Harmonization Center, without any mapping manipulations. What is the minimum amount of Patterns creating both ‘Platform’ and ‘Line of Business’?"
A. 2
B. 3
C. 5
D. 4


B. 3

Explanation: To create both 'Platform' and 'Line of Business' fields using Patterns in the Harmonization Center without mapping manipulations, the engineer would need to create separate patterns for each data source mentioned. According to the provided images:
One pattern for LinkedIn Ads, to extract the 'Campaign Name' at position 4 for the Platform and 'Media Buy Name' at position 7 for Line of Business.
One pattern for AdRoll, to extract 'Media Buy Name' at position 3 for Platform and at position 2 for Line of Business.
One pattern for Google Analytics, which seems not required for the Platform but could apply if the Line of Business extraction is necessary, although it states N/A.
Hence, a minimum of 3 patterns would be necessary to create the fields required.

Question # 8
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:

A. Option A
B. Option B
C. Option C
D. Option D


C. Option C

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 signup.

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Salesforce Marketing-Cloud-Intelligence Exam Dumps

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