Questions for the C-C4H63-2411 were updated on : Dec 01 ,2025
What are some valid use cases for audience activation? Note: There are 3 correct answers to this
question.
A C E
Explanation:
Valid use cases for audience activation within the SAP Customer Data Platform include:
Running marketing campaigns on social media platforms: Marketers can activate audiences to export
data into external applications like social media platforms to run marketing campaigns1
.
Running targeted email campaigns based on customer activities and preferences: Audiences can be
used to run targeted email campaigns that are based on customer actions and choices1
.
Updating customer loyalty level in a loyalty system: While not explicitly stated in the provided
resources, updating customer loyalty levels is a common use case for audience activation, as it
involves using customer data to personalize and improve customer experience.
Reference = The use cases are supported by the SAP Customer Data Platform’s learning resources,
which detail the process of creating audiences and the purposes for which they can be activated12
.
What options are available to pass the processing purpose for inbound data in SAP Customer Data
Platform? Note: There are 2 correct answers to this question.
B D
Explanation:
In the SAP Customer Data Platform, the options available to pass the processing purpose for inbound
data include Static (B) and Dynamic (D) purposes. Static purposes are predefined and remain
constant, while Dynamic purposes are sent as data points in an event from a source, such as a sales
transaction sent with a signed agreement to the terms of service. This allows for the processing
purpose to be attached to an incoming event, ensuring that personal data processing activities follow
a concrete purpose which must be made transparent to the data subject.
Reference = The information is based on the SAP Help Portal documentation on Processing
Purposes1 and Enforce Inbound Data Governance2
.
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What are the three core pillars of SAP Customer Data Platform? Note: There are 3 correct answers to
this question.
C D E
Explanation:
The three core pillars of the SAP Customer Data Platform are designed to provide a comprehensive
framework for managing and leveraging customer data effectively. These pillars are:
C . Activate: This pillar emphasizes the platform's capability to utilize customer data to drive
personalized engagements across various channels. Activation involves leveraging the unified
customer profiles to trigger relevant actions, communications, and experiences tailored to individual
customer needs and preferences.
D . Respect: Central to the SAP Customer Data Platform, this pillar underscores the importance of
managing customer data with respect to privacy and consent. It involves ensuring that all customer
data is collected, stored, and used in compliance with data protection regulations and individual
consent preferences, fostering trust and transparency in customer relationships.
E . Unify: This pillar focuses on the platform's ability to consolidate data from multiple sources into a
cohesive and comprehensive view of the customer. Unification involves integrating disparate data
silos to create a single, unified customer profile that provides a 360-degree view of each customer,
enabling more informed decision-making and personalized customer experiences.
Together, these pillars form the foundation of the SAP Customer Data Platform's approach to
customer data management, supporting businesses in delivering personalized, respectful, and
cohesive customer experiences.
Reference:
SAP Customer Data Platform documentation on the platform's core capabilities and principles.
Best practices for leveraging the core pillars of the SAP Customer Data Platform to enhance customer
engagement and data management strategies.
You are importing primary customer residential address data into SAP Customer Data Platform.How
could you implement this feature using the console?
C
Explanation:
When importing primary customer residential address data into SAP Customer Data Platform using
the console, you should update the profile customer schema.
This involves defining a customer
schema to create a common data model for all incoming customer data, which allows for the
coherent view of customers by unifying data from various sources1
.
Reference = The procedure for updating the profile customer schema is detailed in the SAP Help
Portal documentation under the section 'Configuration Customer Schema’1
.
Which query syntax is correct when searching for users in SAP Customer Data Platform?
B
Explanation:
When searching for users in the SAP Customer Data Platform, the correct query syntax to use would
be:
B . select * from profile where profile.email = '[email protected]' This syntax is
designed to query the customer profiles based on a specific email address, where profile.email refers
to the email attribute within the customer profiles. This query retrieves all profiles where the email
address matches the specified value.
Using this syntax ensures that the query is correctly formatted and targeted, allowing for efficient
retrieval of customer information based on specific attributes within the platform.
Reference:
SAP Customer Data Platform documentation on query syntax and searching for customer profiles.
Technical guides and reference materials on constructing and executing queries within the SAP
Customer Data Platform.
What kinds of prediction can you select for a predictive indicator? Note: There are 2 correct answers
to this question.
A B
Explanation:
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
for Customer lifetime value (CLV) and Customer 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
.
What kinds of indicators can you create in SAP Customer Data Platform? Note: There are 3 correct
answers to this question.
B C E
Explanation:
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
.
What does the warning sign next to the attributes indicate in the Unique Identifiers section of the
Customer Profile view?
B
Explanation:
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.
Reference:
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.
Which of the following is an example of first-party customer data?
D
Explanation:
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
.
The search API for a single customer record does not show any segments tied to the profile, but you
can see the segments in the customer dashboard. What could be the reason for this?
C
Explanation:
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
.
Which of the following are functionalities of the Event Playground? Note: There are 2 correct
answers to this question.
C D
Explanation:
The Event Playground in the SAP Customer Data Platform includes functionalities that allow for the
ingestion of a test event with test values provided via a dedicated form. It also shows logs and errors
at each step of the pipeline, presented in both table format and JSON.
This enables users to track and
understand results and failures, locate data processing issues, and identify connector
problems1
. Reference =
Event Playground | SAP Help Portal
What actions can you perform on a segment? Note: There are 2 correct answers to this question.
A D
Explanation:
Within the SAP Customer Data Platform, you can perform various actions on a segment. Specifically,
you can activate a segment to make it available for use in campaigns and other marketing activities.
Additionally, you have the option to delete a segment if it is no longer needed or relevant. Activation
is a crucial step to ensure that the segment is operational, while deletion helps maintain the
organization and efficiency of your segment management by removing obsolete or unused
segments.
Reference = This response is based on the official SAP Customer Data Platform documentation, which
provides detailed guidance on managing segments, including the ability to activate and delete
them12
.
What are some valid concerns that can be solved by a customer data platform (CDP) solution? Note:
There are 2 correct answers to this question.
A B
Explanation:
Customer Data Platforms (CDPs) are designed to address a variety of challenges related to customer
data management and utilization. Some valid concerns that CDPs aim to solve include:
A . Missing enterprise consent and preference management system: CDPs provide robust
mechanisms for managing customer consents and preferences across multiple channels and
touchpoints. This capability ensures that customer data is used in compliance with privacy
regulations and in alignment with individual customer preferences, enhancing trust and
engagement.
B . Too many data silos: One of the core functions of a CDP is to break down data silos by aggregating
customer data from various sources into a unified customer profile. This consolidation enables a
more comprehensive and actionable view of the customer, supporting personalized engagement and
more effective data analytics.
CDPs address these concerns by providing a centralized platform for managing customer data,
enabling businesses to deliver more personalized and compliant customer experiences while gaining
deeper insights into customer behaviors.
Reference:
SAP Customer Data Platform documentation on consent management and data integration
capabilities.
Industry best practices on utilizing CDPs to overcome challenges related to data silos and consent
management.
What can you do with the Audit Search API?
B
Explanation:
The Audit Search API in the SAP Customer Data Platform offers functionalities centered around
auditing and oversight of platform activities. One of the capabilities of this API is:
B . Query Single Activity: This function allows users to retrieve detailed information about specific
activities or actions taken within the platform. This can include user interactions, data processing
operations, or system events. The ability to query single activities is crucial for compliance,
monitoring, and troubleshooting purposes, enabling administrators to track and audit individual
actions for security, compliance, and operational insights.
The Audit Search API's ability to delve into specific activities helps maintain transparency and
accountability within the platform, supporting robust governance and compliance strategies.
Reference:
SAP Customer Data Platform API documentation, specifically focusing on audit and search
functionalities.
Technical guides on utilizing the Audit Search API for monitoring and compliance purposes within the
SAP Customer Data Platform.
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.
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.