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New Adobe Experience Platform AD0-E602 Exam Practice Questions

Total 50 Questions

Last Updated On: 16-Jan-2025

Question # 1

A marketer sets up a new Amazon S3 source in real-time CDR A few days later, the marketer wants to check for any errors with ingestion. In which two places should the marketer look for ingestion errors? (Choose two.)
A. Dataset activity
B. Source's dataflow activity
C. Segments detail
D. Profile details

Dataset activity

Source's dataflow activity

Explanation: According to the Adobe documentation1, dataset activity and source’s dataflow activity are two places where ingestion errors can be viewed. Dataset activity shows the status of each batch that is ingested into a dataset, including any errors or warnings. Source’s dataflow activity shows the status of each source connection run, including any errors or warnings.

Question # 2

An Adobe Real-Time CDP Business Practitioner wants to forward raw website events to an analytics destination in real-time rather than sending a segment using a cookie identifier. Which type of destination should the practitioner use?
A. Streaming Profile Export Destination
B. Connection
C. Extension

Streaming Profile Export Destination

Explanation: According to the Adobe documentation, streaming profile export is a type of destination that allows sending raw events or attributes associated with profiles in real-time to an external system or service. This type of destination does not require creating or activating segments, and can use any identity namespace as the target identity.

Question # 3

A retailer who is an Adobe Real-Time CDP (RTCDP) customer wants to understand the percentage split of different age groups who buy their athletic shoes to help inform which age group to reach in their next shoe marketing campaign. Which two steps should the retailer take to analyze their shoe segment in this way using RTCDP? (Choose two.)
A. Create multiple segments which OR each age group attribute with athletic shoe purchaser events
B. Divide the size of each age group segment into the total sum of all purchaser events to get percentage splits for analysis
C. Divide the size of each age group segment into the total sum of athletic shoe purchaser events to get percentage splits for analysis
D. Create multiple segments which AND each age group attribute with athletic shoe purchaser events

Divide the size of each age group segment into the total sum of athletic shoe purchaser events to get percentage splits for analysis

Create multiple segments which AND each age group attribute with athletic shoe purchaser events

Explanation: Two steps that the retailer should take to analyze their shoe segment in this way using RTCDP are to divide the size of each age group segment into the total sum of athletic shoe purchaser events to get percentage splits for analysis and to create multiple segments which AND each age group attribute with athletic shoe purchaser events. The first step allows the retailer to calculate the proportion of each age group among the shoe buyers, while the second step allows the retailer to create segments that include only the shoe buyers who belong to a specific age group.

Question # 4

A Real-time CDP business practitioner needs to determine how data will be prioritized and what data will be combined to create that unified view of a customer profile. Which feature should be used?
A. Merge Policies
B. Union Schema
C. Identity Graph

Merge Policies

Explanation: According to the Adobe documentation, merge policies are a feature of Real-Time CDP that can be used to determine how data will be prioritized and what data will be combined to create a unified view of a customer profile. Merge policies define the rules and logic for merging profile attributes from different data sources into a single profile. Merge policies can be either predefined or custom, and they can be applied at the dataset level or the tenant level.

Question # 5

Before using Adobe Real-Time CDR a telecommunications company was directly uploading a segment of likely-to-churn customers from SalesForce Marketing Cloud into Facebook for its social campaigns every 7 days. Now, the company can stream this data into RTCDP for segmentation and share with the Facebook connector in near real-time. Which two metrics can be tracked to calculate the value of RTCDP for this customer? (Choose two.)
A. CPM
B. Time-to-market
C. CPA
D. AOV

Time-to-market

CPA

Explanation: Two metrics that can be tracked to calculate the value of RTCDP for this customer are time-to-market and CPA. Time-to-market measures how quickly the customer can reach their target audience with relevant offers and messages using RTCDP’s near real-time segmentation and activation capabilities. CPA (cost per acquisition) measures how much it costs the customer to acquire a new customer or retain an existing one using RTCDP’s data-driven optimization and personalization features.

Question # 6

Which two standard widgets are available in a Profiles overview dashboard of Real-time CDP? (Choose two.)
A. Profiles added
B. Profile source
C. Identity graph
D. Identity overlap

Profiles added

Profile source

Explanation: According to the Adobe documentation, profiles added and profile source are two standard widgets that are available in a Profiles overview dashboard of Real-time CDP. Profiles added widget shows the number of profiles that have been added to the platform
over time. Profile source widget shows the breakdown of profiles by their source type, such as batch or streaming.

Question # 7

A retailer implements Adobe real-time CDP and is able to combine in-store purchase data with purchase data from their website using a phone number as the primary key. Which two data segments targeted in paid campaigns will become more accurate and result in CPA uplift? (Choose two.)
A. In-store Purchasers
B. Past Purchase >30 Days
C. Frequent Purchasers
D. Desktop browsers

In-store Purchasers

Frequent Purchasers

Explanation: According to the Adobe documentation, by combining in-store purchase data with online purchase data using a phone number as the primary key, the retailer can create more accurate segments of customers based on their purchase behavior across channels.
For example, the retailer can target in-store purchasers who have not bought online yet, or frequent purchasers who have bought both online and offline multiple times. These segments can be targeted in paid campaigns to increase conversion rates and reduce cost per acquisition (CPA).

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