Salesforce Marketing Cloud Intelligence Exam Practice Test Instant Access

Question 1

Source 3:

Via the harmonization Center, the Client has created Patterns and applied a classification rule using source 2.

While performing QA, you have spotted that the final value of clicks for Product Group Ais 10, where it should've been i5.

How can an implementation engineer fix this discrepancy?

AUncheck the 'Case Sensitive'' checkbox in the data classification

BLeave the 'Case Sensitive'' checkbox in the data classification unchecked

CToggle the 'Structure Compliant' OFF.

DUpload both source 1 and 3 to the same data stream type in order to be able to generate Patterns from them.

Answer : A

Case Sensitivity Issue:

The discrepancy in the 'Clicks' value for Product Group A (10 instead of 15) likely arises from a mismatch caused by case sensitivity in the classification rules. If some data entries use different capitalization (e.g., 'Product Group A' vs. 'product group a'), the system might treat them as distinct entries, leading to incorrect aggregations.

Solution:

By unchecking the 'Case Sensitive' checkbox, the harmonization process will treat entries with different capitalization as the same value. This ensures consistent classification and resolves discrepancies in aggregated metrics like 'Clicks.'

Question 2

A client has integrated the following files:

File A:

File B:

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 A is 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?

AOption A

BOption B

COption C

DOption D

Answer : C

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 Updates Permissions' 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

A client would like to integrate the following two sources:

Google Campaign Manager:

IAS:

After configuring a Parent-Child relationship between the files, which query should an implementation engineer run in order to QA the setup?

AMedia Buy Type, Media Buy Name, Impressions, Analyzed Impressions

BCreative Name, Impressions, Analyzed Impressions

CMedia Buy Name, Impressions

DMedia Buy Type, Analyzed Impressions

Answer : A

To QA the Parent-Child relationship setup between Google Campaign Manager and IAS data sources, it is essential to query fields that are common to both sources and that are relevant to the relationship. 'Media Buy Type' and 'Media Buy Name' are common identifiers between the two datasets. 'Impressions' from the Google Campaign Manager and 'Analyzed Impressions' from the IAS data are the metrics that should be compared to ensure they match or correlate as expected due to the Parent-Child relationship. The QA process involves checking that the data is correctly aligned and that the metrics from the parent source (Google Campaign Manager) are properly related to the metrics from the child source (IAS). Reference: Salesforce Marketing Cloud Intelligence documentation on data integration, Parent-Child relationships, and QA procedures for data setup.

Question 4

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?

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

BUnmap it, as Datorama will calculate it automatically.

CPopulate the logic within a custom measurement. Set Aggregation to AVG.

DPopulate the logic within a custom measurement. Set Aggregation to SUM.

Answer : A

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. Reference: Salesforce Marketing Cloud Intelligence documentation on creating custom measurements and calculated metrics.

Question 5

An implementation engineer has been asked by a client for assistance with the following problem:

The below dataset was ingested:

However, when performing QA and querying a pivot table with Campaign Category and Clicks, the value for Type' is 4.

What could be the reason for this discrepancy?

AThe measurement 'Clicks' is set as a percentage.

BA mapping formula was populated, indicating not to bring Type! values.

CThe aggregation function is set as AVG

DThe aggregation function is set as LIFETIME

Answer : C

The discrepancy of 'Clicks' being reported as 4 for 'Type1' when the sum of clicks in the dataset for 'Type1' is 8 (2 on 02/02/2021 and 6 on 03/02/2021) suggests that the aggregation function used in the pivot table is set to average (AVG) rather than sum. Salesforce Marketing Cloud Intelligence allows setting different aggregation functions for metrics, and setting it to average would result in such a discrepancy when more than one entry for the same type exists. Reference: Salesforce Marketing Cloud Intelligence documentation on custom measurements and data aggregations explains how to set and understand different aggregation functions.

Question 6

An implementation engineer has been asked to perform a QA for a newly created harmonization field, Color, implemented by a client.

The source file that was ingested can be seen below:

The client performed the below standard mapping:

As a final step, the client had created the field 'Color'. As can be seen, it is extracted from the Creative Name (after the '#' sign).

For QA purposes, you have queried a pivot table, with the following fields:

* Media Buy Key

* Media Buy Name

* In View Impressions

The final pivot is presented below:

AA Harmonized dimension was created via a pattern over the Creative Name.

BA calculated dimension was created with the formula: EXTRACT([Creative_Namel, #1)

CAn EXTRACT formula (for Color) was written and mapped to a Media Buy custom attribute.

DAn EXTRACT formula (for Color) was written and mapped to a Creative custom attribute.

Answer : D

Given that the 'Color' field is extracted from the 'Creative Name' field and appears to be part of the creative-level data, the most logical method would be to create an EXTRACT formula and map it to a Creative custom attribute. This allows the 'Color' value to be associated directly with each creative entry. In Salesforce Marketing Cloud Intelligence, the EXTRACT formula can be used to parse and segment text strings within a field, and this process is used for harmonizing data by creating new dimensions or attributes based on existing data, which is what's described here. This answer is consistent with Salesforce Marketing Cloud Intelligence features that enable data transformation and harmonization through formulaic mapping, as per the official Salesforce documentation on data harmonization and transformation.

Question 7

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?

ARegistered

BInterest & Registered

CConfirmed Interest & Registered

DInterest

EConfirmed Interest

Answer : B

Analyzing the Opportunity file with a filter set from January 7th to 11th, Opportunity Key '123AA01' appears under 'Interest' on January 6th and 8th, and under 'Registered' on January 10th. Therefore, during the specified date range, Opportunity Key '123AA01' is associated with both 'Interest' and 'Registered' stages. Salesforce Marketing Cloud Intelligence provides the capability to map and track opportunity stages over time, allowing for historical stage tracking and reporting. This answer aligns with the ability to use pivot tables to filter and display data by specific attributes and timeframes, as outlined in the Salesforce Marketing Cloud Intelligence documentation.

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