Marketing-Cloud-Intelligence Dumps Collection - Marketing-Cloud-Intelligence Online Training Materials
Marketing-Cloud-Intelligence Dumps Collection - Marketing-Cloud-Intelligence Online Training Materials
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Salesforce Marketing-Cloud-Intelligence Exam Syllabus Topics:
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Salesforce Marketing Cloud Intelligence Accredited Professional Exam Sample Questions (Q44-Q49):
NEW QUESTION # 44
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. Interest
- B. Interest & Registered
- C. Confirmed Interest & Registered
- D. Registered
- E. Confirmed Interest
Answer: B
Explanation:
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.
NEW QUESTION # 45
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?
- A. A mapping formula was populated, indicating not to bring Type! values.
- B. The aggregation function is set as AVG
- C. The aggregation function is set as LIFETIME
- D. The measurement 'Clicks' is set as a percentage.
Answer: B
Explanation:
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.
NEW QUESTION # 46
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.
Which three advantages does a client gain from using Calculated Dimensions as the harmonization method for creating the Objective field?
- A. Scalability - future data streams that will follow similar logic will be automatically harmonized.
- B. Processing - creation of Calculated Dimensions will ease the processing time of the data streams it relates to
- C. Data model restrictions - Calculated Dimensions do not need to adhere to Marketing Cloud Intelligence's data model
- D. Performance (Performance when loading a dashboard page) should be optimized as the values of calculated dimensions are stored within the database.
- E. Ease of Maintenance - the logic is written and populated in one centralized place
Answer: A,D,E
Explanation:
Scalability: Using Calculated Dimensions allows the client to apply the same harmonization logic to future data streams, ensuring consistency and reducing the need for individual adjustments.
Ease of Maintenance: With the logic centralized in Calculated Dimensions, any adjustments or updates are applied in one place, simplifying ongoing management.
Performance: Calculated Dimensions can improve dashboard performance because their values are pre-computed and stored, reducing the need for real-time calculations when loading dashboards.
NEW QUESTION # 47
What is the relationship between "Media Buy Key" and "Campaign Key"?
- A. Many-to-many
- B. One-to-many (one Media Buy Key has many Campaign Keys)
- C. Many-to-one (one Campaign Key has many Media Buy Keys)
- D. One-to-one
Answer: C
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
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. 0
- B. 1
- C. 2
- D. 3
Answer: D
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 Cloud Intelligence 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.
NEW QUESTION # 49
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