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NEW QUESTION # 16
You want to match the outbound data to the destination platform's format.Which normalization rules can be applied? Note: There are 3 correct answers to this question.
Answer: B,C,D
Explanation:
The SAP Customer Data Platform allows for the application of normalization rules to outbound data to ensure it matches the destination platform's format. The normalization options include:
Remove punctuation: This rule removes all punctuation marks from the data, which can be necessary for formats that do not accept such characters.
Find and replace: This rule replaces an expression (text, numerical sequence, etc.) with a different expression, allowing for customization of data to fit the destination's requirements.
Remove spaces: This rule removes all spaces from the data, which is useful for platforms that require data without spaces, such as in certain phone number formats.
These rules help in transforming the data to meet the specific format requirements of various destination platforms.
Reference = The information provided here is based on the SAP Customer Data Platform's official documentation regarding action normalization1.
NEW QUESTION # 17
Which of the following merge rules must be defined at attribute level?
Note: There are 2 correct answers to this question.
Answer: C,D
NEW QUESTION # 18
What would you use activity indicators as building blocks for?
Note: There are 3 correct answers to this question.
Answer: B,C,D
NEW QUESTION # 19
You want to create a calculated indicator.
What attributes from the customer schema can you use? Note: There are 3 correct answers to this question.
Answer: B,C,D
Explanation:
When creating a calculated indicator within the SAP Customer Data Platform, you can utilize attributes from the customer schema such as Events (B), Profile , and Activity indicators (D). These attributes can be combined in a mathematical equation to create a new indicator that reflects complex calculations. For example, you can use numeric profile attributes, activity indicators, or activities from the CDP schema to calculate the new indicator, and you can also apply conditions to narrow down the customer profiles to which the calculation will be applied.
Reference = This information is supported by the SAP Help Portal documentation on creating a calculated activity indicator1 and activity indicator calculation2.
In the SAP Customer Data Platform, when creating a calculated indicator, certain attributes from the customer schema are pivotal for defining complex metrics that provide deeper insights into customer behaviors and preferences. The attributes you can use include:
B . Events: These attributes encompass various customer interactions and behaviors captured as events, such as purchases, website visits, or engagement with marketing campaigns. Events can be used to calculate indicators that reflect customer activity levels, preferences, or engagement patterns.
C . Profile: Profile attributes contain demographic and personal information about the customer, such as age, location, preferences, and more. These attributes can be used in calculated indicators to segment customers, personalize experiences, or predict customer behaviors based on their profiles.
D . Activity indicators: These are metrics or flags derived from customer activities and behaviors, such as frequency of purchases, average transaction value, or recent engagement. Using activity indicators to create calculated indicators allows for the synthesis of complex metrics that can measure customer loyalty, lifetime value, or risk of churn.
By leveraging these attributes, calculated indicators can provide multifaceted insights into customer behavior, preferences, and value, driving more informed business decisions and personalized customer experiences.
Reference:
SAP Customer Data Platform documentation on creating calculated indicators and using customer schema attributes.
Best practices for leveraging customer data attributes in the SAP Customer Data Platform for advanced analytics and segmentation.
NEW QUESTION # 20
Which of the following statements describe merge rule functionality?
Note: There are 2 correct answers to this question.
Answer: B,D
NEW QUESTION # 21
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