Question 1
Which three menu options can be used to validate and monitor a destination? (Choose three.)
- A. Systems View
- B. Catalog
- C. Overview
- D. Browse
- E. Services
Answer:
A, C, D
Explanation:
These are three menu options that can be used to validate and monitor a destination. Systems View
allows users to see the status of dataflows between sources and destinations, as well as any errors or
warnings. Overview allows users to see the basic information and settings of a destination, such as
name, description, type, and activation status. Browse allows users to see the segments that have
been shared with a destination, as well as their size and export status. Reference: :
Systems
View
:
Overview
:
Browse
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Question 2
Which structure allows the engineer to apply usage labels to attributes?
- A. Schema
- B. Dataset
- C. Field groups
Answer:
A
Explanation:
Schema is the structure that allows the engineer to apply usage labels to attributes. Usage labels are
tags that indicate the sensitivity or classification of data, such as PII or opt-out. By applying usage
labels to attributes in a schema, the engineer can enable data usage governance for datasets that
use that schema. Reference: :
Schema Overview
:
Data Labels Overview
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Question 3
A marketer wants the ability to send win-back messaging to consumers through Instagram ads based
on their last purchase, whether it occurred on the organization's App, website, or in-store.
The marketer has the following data sources available to be imported:
• Member Hub
• Digital Order Line (DOL)
• Brick Mortar Order Line (BMOL)
• Clickstream
How should the Experience Platform be set up?
A.
1. Bring in member profile data from Member Hub into AEP
2. Bring in transaction data (order id, purchase date, purchase amount, transaction details) - From
DOL. BMOL, and Clickstream
3. Create segments in AEP based on channel - App, website, or in-store for customers who have
made purchases in the last 2 months
4. Send audiences to Facebook via s3 destination exports
B.
1. Bring in member profile information from Clickstream into AEP
2. Bring in transaction data (order id, purchase date, purchase amount, transaction details) - From
DOL, BMOL
3. Create segments in AEP based on channel - App. website, or in-store for customers who have not
made purchases in the last 2 months
4. Send audiences to Facebook via s3 destination exports
C.
1. Bring in member profile data from Member Hub into AEP
2. Bring in transaction data (order id, purchase date, purchase amount, transaction details) - From
DOL, BMOL, and Clickstream
3. Create segments in AEP based on channel - App, website, or in-store for customers who have
made purchases in the last 2 months
4. Send audiences to Facebook
D.
1. Bring in member profile information from Clickstream into AEP
2. Bring in transaction data (order id, purchase date, purchase amount, transaction details) - From
DOL, BMOL
3. Create segments in AEP based on channel - App. website, or in-store for customers who have not
made purchases in the last 2 months
4. Send audiences to Facebook
Answer:
C
Explanation:
This is the most effective workflow to send win-back messaging to consumers through Instagram ads
based on their last purchase, whether it occurred on the organization’s App, website, or in-store. By
bringing in member profile data from Member Hub into AEP, the company can leverage the profile
data and identity stitching features of AEP to create a unified view of their customers. By bringing in
transaction data (order id, purchase date, purchase amount, transaction details) - From DOL, BMOL,
and Clickstream into AEP dataset, the company can ingest online and offline purchase data from
different sources into AEP. By creating segments in AEP based on channel - App, website, or in-store
for customers who have made purchases in the last 2 months, the company can use the
segmentation service and UI of AEP to define and evaluate their target audience based on profile
attributes and behaviors. By sending audiences to Facebook via s3 destination exports, the company
can activate their segment across multiple channels, such as Instagram ads. Reference: :
Onboard
Data into Platform
:
Create a Segment
:
Share Segments with Destinations
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Question 4
A company wants to create a new segment of current customers to advertise to them through
Google's Display Network to encourage them to download an exclusive white paper. The company
wants to limit this segment to only include customers after they have watched one video from the
company's gated knowledge center, and who have contracts that expire in 3 months.
The company has mar-tech tools and services with which they track and communicate with clients:
• Adobe Analytics
• Adobe Experience Platform
• Adobe Campaign Standard
• Adobe Experience Manager
• CRM
• Google Adwords Account
Which steps should the company take to advertise?
- A. Onboard the CRM data into the AEP dataset Create a segment in Analytics that matches the business requirements and send to AEP dataset Share the segment with Google Adwords
- B. Onboard the CRM data Into the AEP dataset Create a segment in AEP-CDP that matches the business requirements Share the segment with Google Adwords
- C. Onboard the CRM data into Adobe Analytics Create a segment in AEP-CDP that matches the business requirements Share the segment with Google Adwords
Answer:
B
Explanation:
This is the most effective workflow to create a new segment of current customers to advertise to
them through Google’s Display Network to encourage them to download an exclusive white paper.
By onboarding CRM data into AEP dataset, the company can leverage the profile data and identity
stitching features of AEP to create a unified view of their customers. By creating a segment in AEP-
CDP that matches the business requirements, the company can use the segmentation service and UI
of AEP to define and evaluate their target audience based on profile attributes and behaviors. By
sharing the segment with Google Adwords, the company can activate their segment across multiple
channels, such as Google’s Display Network. Reference: :
Onboard Data into Platform
:
Create a
Segment
:
Share Segments with Destinations
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Question 5
A retailer wants to create a segment of existing customers who have browsed the website in the past
hour. The web activity is being sourced from Adobe Analytics in real-time streaming, and the
customer list comes daily as batch from the CRM system.
Which segment should the engineer create to evaluate streaming?
- A. A segment that includes all customers and any customer whose last web activity Is older than 1 hour ago
- B. A segment that only looks at the Adobe Analytics data source
- C. A segment based on the Adobe Analytics data source and using membership in a Customer segment
Answer:
C
Explanation:
This is the most suitable segment to evaluate streaming data from Adobe Analytics in real-time and
filter out customers who are not in the CRM system. By basing the segment on the Adobe Analytics
data source, the company can use the streaming ingestion feature of AEP to capture web activity
data in near real-time. By using membership in a Customer segment, the company can use an
existing segment that contains customers from the CRM system as a filter criterion to exclude non-
customers from the segment. Reference: :
Streaming Ingestion Overview
:
Create a Segment
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Question 6
A customer is bringing in data through the following AEP Source Connectors:
• HTTP Sink Connector via streaming for transaction data
• S3 Connector for their batch Profile data coming from a Data Lake
Which segmentation evaluation is allowed9
- A. Batch evaluation for all segment definitions
- B. Streaming evaluation for all segment definitions
- C. Combination of Batch segments evaluation depending on the segment definition
- D. Streaming or Batch evaluation depending on the segment definition
Answer:
D
Explanation:
This is the correct answer because AEP allows users to choose between streaming or batch
evaluation for their segments depending on their segment definition and data sources. Streaming
evaluation is available for segments that use streaming data sources, such as HTTP Sink Connector or
Adobe Analytics Connector, and do not use any batch-only features, such as time windows or derived
attributes. Batch evaluation is available for segments that use batch data sources, such as S3
Connector or FTP Connector, or use any batch-only features. Users can also switch between
streaming and batch evaluation modes for their segments if they meet certain criteria. Reference:
:
Segment Evaluation
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Question 7
A company launches a Facebook campaign with a custom landing page that was supposed to give a
$50 voucher to customers who order within 2 hours of clicking on the link. The web developers
forgot to add the tracking code to the checkout process, so the company does not know who ordered
from the Facebook campaign-How should an engineer create the segment?
A)
B)
C)
D)
- A. Option A
- B. Option B
- C. Option C
- D. Option D
Answer:
B
Explanation:
This is the most appropriate workflow to launch a summer sale email campaign to target customers
who have browsed for any summer clothing in the last 90 days. By selecting email opt in = YES as an
attribute, the company can filter out customers who have not consented to receive email
communications. By selecting product.browse = last 90 days and product.category = Sandals,
Swimwear, Tshirts, Shorts as events, the company can capture customers who have shown interest in
summer products recently. By saving the segment and scheduling the export for 7/31, the company
can ensure that the segment is up to date and ready to be sent out on August 1. Reference: :
Create a
Segment
:
Schedule Segment Export
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Question 8
A company launches a Facebook campaign with a custom landing page that was supposed to give a
$50 voucher to customers who order within 2 hours of clicking on the link. The web developers
forgot to add the tracking code to the checkout process, so the company does not know who ordered
from the Facebook campaign-How should an engineer create the segment?
- A. Aggregation functions
- B. Analytical functions
- C. Count functions
Answer:
B
Explanation:
Analytical functions are functions that allow users to perform complex calculations on data within a
segment definition. For example, users can use analytical functions to calculate averages, sums,
counts, ranks, percentiles, and more. Analytical functions can help users create more advanced
segments based on derived metrics or attributes. Reference: :
Analytical Functions Overview
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Question 9
A customer brings in their data from CRM and Data Lake sources daily through Adobe Experience
Platform Sources. Which Segmentation(s) evaluation is allowed?
- A. Batch Evaluation
- B. Streaming Evaluation
- C. Batch and Streaming Evaluation
Answer:
A
Explanation:
Batch evaluation is the only segmentation evaluation mode that is allowed for a customer who
brings in their data from CRM and Data Lake sources daily through Adobe Experience Platform
Sources. Batch evaluation is available for segments that use batch data sources, such as S3 Connector
or FTP Connector, or use any batch-only features, such as time windows or derived attributes. Batch
evaluation runs periodically based on the segment refresh interval. Reference: :
Segment Evaluation
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Question 10
A credit union wants to create a segment based on all customers who currently have a home loan
with the credit union, pay through auto pay, and have logged in within the last 2 weeks but do not
have a credit card issued through the credit union.
Which criteria does the engineer need to create this segment?
A.
• Customer exists within the client dataset
• Customer has logged in within the last 30 days
• Customer has a home loan with the credit union
• Customer has auto pay set up for paying the home loan
• Customer acquired a credit card in the last 30 days
B.
• Customer exists within the client dataset
• Customer has logged in within the last 30 days
• Customer has a home loan with the credit union
• Customer pays by check for their home loan
• Customer acquired a credit card in the last 30 days
C.
• Customer exists within the client dataset
• Customer has logged in within the last 14 days
• Customer has a home loan with the credit union
• Customer has auto pay set up for paying the home loan
• Customer has not acquired a credit card
D.
• Customer exists within the client dataset
• Customer has logged in within the last 14 days
• Customer has a home loan with the credit union
• Customer pays by check for their home loan
• Customer has not acquired a credit card
Answer:
C
Explanation:
This is the most suitable criteria to create a segment based on all customers who currently have a
home loan with the credit union, pay through auto pay, and have logged in within the last 2 weeks
but do not have a credit card issued through the credit union. By selecting customer exists within the
client dataset as an attribute, the company can filter out non-customers from the segment. By
selecting customer has logged in within the last 14 days as an attribute, the company can capture
customers who have shown recent activity on their account. By selecting customer has a home loan
with the credit union and customer has auto pay set up for paying the home loan as attributes, the
company can identify customers who have a specific product and payment method with the credit
union. By selecting customer has not acquired a credit card as an attribute, the company can exclude
customers who already have a credit card issued through the credit union. Reference: :
Create a
Segment
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