SAP C_C4H63_2411 Exam Questions

The issue described could be due to incorrect permissions for the API authorization keys. When the permissions are not set up correctly, the search API may not return segment data tied to a customer profile, even though these segments are visible in the customer dashboard. Proper configuration of API authorization keys is essential to ensure that the search API has the necessary permissions to access and return all relevant data, including customer segments.

Reference= This explanation aligns with the information provided in the SAP Customer Data Platform documentation and resources12.

First-party customer data refers to the information that is collected directly from customers by the company itself. This includes data gathered through interactions with the company's own channels, such as websites, mobile apps, customer service interactions, and in-store visits.The SAP Customer Data Platform enables businesses to connect various types of customer data to deliver personalized experiences, and first-party data is crucial for creating a comprehensive view of the customer1.Reference= The explanation aligns with the functionalities and use cases of the SAP Customer Data Platform as described in the official SAP Help Portal1.

In the SAP Customer Data Platform, within the Unique Identifiers section of the Customer Profile view, a warning sign next to attributes typically indicates:

B . It indicates that the values of those attributes are shared with other customer profiles. This warning is used to highlight potential issues with data uniqueness, where the supposed unique identifiers are not exclusive to a single customer profile but are instead found across multiple profiles. This situation could lead to data integrity issues, as unique identifiers are meant to distinguish each customer profile distinctly.

Addressing these warnings is crucial for maintaining the reliability of the customer data, ensuring that each profile is uniquely and accurately identified within the platform.

SAP Customer Data Platform user documentation on managing customer profiles and understanding the significance of unique identifiers.

Best practices for data management within the SAP Customer Data Platform, with a focus on maintaining the uniqueness of customer identifiers.

In the SAP Customer Data Platform, you can create various types of indicators to measure and understand different aspects of customer data and behavior. The types of indicators that can be created are:

Calculated Indicators: These are metrics derived from calculations based on customer data.

Predictive Indicators: These models, also known as predictive indicators, are designed to make predictions based on data patterns and are used for forecasting customer behavior such as churn probabilities or customer lifetime value1.

Activity Indicators: These indicators are created to calculate metrics and gauge the performance of various business areas based on customer activities2.

Segmented and Profile indicators are not listed as types of indicators that can be created in the SAP Customer Data Platform according to the provided resources.

Reference= The information regarding the types of indicators is supported by the SAP Help Portal and SAP Learning resources, which detail the management of predictive models and the creation of activity indicators within the SAP Customer Data Platform12.

Within the SAP Customer Data Platform, predictive indicators are designed to make predictions based on customer profile or group and activity data. Specifically, you can select predictions forCustomer lifetime value (CLV)andCustomer churn.The CLV prediction is about forecasting the potential revenue a customer will generate over their lifetime, while the churn prediction estimates the likelihood of a customer ceasing to use a company's services or products1.

Reference= This information is derived from the SAP Help Portal documentation, which details the types of predictions you can configure for predictive indicators within the SAP Customer Data Platform, including churn probabilities for profiles and groups, as well as customer lifetime value for profiles and groups1.