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NEW QUESTION # 27
An outdoor retailer and Adobe Real-Time CDP customer tries to create a segment that identifies females who browsed camping supplies on its website. The retailer first selected experience events of users who have visited campaign supply product pages in the past 30 days. The initial size of the segment was 450,000 profiles. However, when the retailer AND'd the gender attribute from its loyalty system, the size of the segment dropped to only 7;000 profiles.
What is the most likely explanation for this dramatic drop in segment size?
- A. The majority of browsers on the website are not authenticated.
- B. The recency needs to be expanded to include 90 days of activity.
- C. Women are less interested in the brand's camping supplies than men.
- D. The segment logic should include an OR statement instead of an AND.
Answer: A
Explanation:
The most likely explanation for the dramatic drop in segment size is that the majority of browsers on the website are not authenticated. This means that they do not have a loyalty account or a unique identifier that can be matched with the gender attribute from the loyalty system. Therefore, they are excluded from the segment that ANDs the gender attribute with the browsing behavior. To increase the segment size, the retailer could use other methods to identify or infer the gender of anonymous browsers, such as cookies, device IDs, or third-party data.
NEW QUESTION # 28
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. Union Schema
- B. Merge Policies
- C. Identity Graph
Answer: B
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. Reference: https://experienceleague.adobe.com/docs/experience-platform/profile/merge-policies/overview.html?lang=en#merge-policies-overview
NEW QUESTION # 29
A financial services start-up implements Adobe Real-Time CDP and ingests third-party data with lead information. The start-up provides credit cards with crypto currency bonus offers.
Which two attributes could be used to understand high-value prospects? (Choose two.)
- A. Credit score
- B. Number of bank accounts
- C. Household income
- D. Bitcoin price
Answer: A,C
Explanation:
Two attributes that could be used to understand high-value prospects are household income and credit score. Household income indicates the financial capacity and spending power of a prospect, which could affect their interest in credit cards with crypto currency bonus offers. Credit score indicates the creditworthiness and risk level of a prospect, which could affect their eligibility and approval for credit cards with crypto currency bonus offers.
NEW QUESTION # 30
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. Source's dataflow activity
- B. Segments detail
- C. Dataset activity
- D. Profile details
Answer: A,C
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. Reference: 1 https://experienceleague.adobe.com/docs/experience-platform/sources/ui/monitor.html?lang=en#viewing-ingestion-errors
NEW QUESTION # 31
A Real-time CDP Business Practitioner set up a profile segment using Experience Event data on a Profile-enabled dataset on January 1, 2022. The segment size at creation was 25,000. When revisiting the segment at the end of February, the segment size decreased to 10,000.
What explains this decrease in segment size?
- A. More profiles met the segment criteria during the time difference.
- B. The created segment was activated to a destination.
- C. The dataset had a 30-day TTL set.
Answer: C
Explanation:
According to the Adobe documentation1, TTL (time-to-live) is a setting that determines how long data is retained in a dataset before it is deleted. If the dataset had a 30-day TTL set, then any data that was older than 30 days would be removed from the dataset, which could explain the decrease in segment size over time. Reference: 1 https://experienceleague.adobe.com/docs/experience-platform/ingestion/home.html?lang=en#time-to-live
NEW QUESTION # 32
A Real-time CDP Business Practitioner is working to apply data labels according to DULE labeling.
At which level would should the business practitioner apply labels to propagate to chosen datasets and fields?
- A. Dataset
- B. Schema
- C. Table
- D. Connection
Answer: B
Explanation:
According to the Adobe documentation, DULE labeling is a framework that allows applying data usage labels (DULs) to data fields based on their usage category (Descriptive, Underlying, Linked, or Extracted). DULs can be applied at the schema level, which means they will propagate to all datasets and fields that use that schema. Reference: https://experienceleague.adobe.com/docs/experience-platform/data-governance/dule/dule-overview.html?lang=en#dule-overview
NEW QUESTION # 33
A Real-Time CDP customer wants to share a customer segment using the identity namespace personalEmail.address across marketing channels.
For which destinations must these email addresses be transformed into the SHA256 format as the target identity?
- A. Linkedin Matched Audiences connection
Google Customer Match connection
Facebook connection - B. Amazon S3 connection
Salesforce Marketing Cloud connection - C. Facebook connection
Salesforce Marketing Cloud connection
Linkedin Matched Audiences connection
Answer: C
Explanation:
Google Customer Match connection
Explanation:
According to the Adobe documentation, some destinations require email addresses to be hashed using SHA256 algorithm before they can be used as target identities. These destinations include Facebook, Salesforce Marketing Cloud, Linkedin Matched Audiences, and Google Customer Match. Reference: https://experienceleague.adobe.com/docs/experience-platform/destinations/ui/destination-actions.html?lang=en#hashing-email-addresses
NEW QUESTION # 34
A Real-Time CDP Business Practitioner must create a new destination. As the final step in creating the new destination, they are unable to indicate the intent for which data will be exported to the destination.
What must they do in order to complete the new destination creation?
- A. Select an audience
- B. Create their own marketing action
- C. Move to the activation flow
Answer: B
Explanation:
According to the Adobe documentation, if none of the predefined marketing actions match the intent for which data will be exported to the destination, the practitioner can create their own marketing action by selecting "Other" and providing a name and description for it. Reference: https://experienceleague.adobe.com/docs/experience-platform/destinations/ui/destination-actions.html?lang=en#creating-a-new-marketing-action
NEW QUESTION # 35
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. Extension
- B. Connection
- C. Streaming Profile Export Destination
Answer: C
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. Reference: https://experienceleague.adobe.com/docs/experience-platform/destinations/catalog/profile-export.html?lang=en
NEW QUESTION # 36
A Real-Time CDP Business Practitioner is working on a case where there is a data governance policy violation on activating a segment to email targeting destination using a data field from dataset labeled as C4.
Which two are recommended resolutions for this situation to maintain existing data governance policy? (Choose two.)
- A. Remove or modify data usage policy
- B. Remove segment from destination
- C. Remove or modify labels of the dataset
- D. Modify segment attribute or merge policy
Answer: B,D
Explanation:
According to the Adobe documentation, C4 is a type of contract label that indicates data that cannot be used for off-site targeting purposes, such as email targeting destination. To resolve the policy violation, the practitioner can either modify the segment attribute or merge policy to exclude the C4 data field from the segment definition, or remove the segment from the destination altogether. Reference: https://experienceleague.adobe.com/docs/experience-platform/data-governance/dule/dule-overview.html?lang=en#contract-labels
NEW QUESTION # 37
A Real-Time CDP Business Practitioner needs to analyze a segment's profile count. The business practitioner is interested in the number of new profiles that are part of the segment and the number of profiles that are getting removed from the segment.
Which profile status types can the practitioner use for this scenario?
- A. Realized and Exiting
- B. Qualified and Existing
- C. Realized and Leaving
Answer: A
Explanation:
According to the Adobe documentation, realized profiles are those that have newly qualified for a segment, while exiting profiles are those that have been removed from a segment due to no longer meeting the segment definition. These profile status types can be used to analyze the segment's profile count over time. Reference: https://experienceleague.adobe.com/docs/experience-platform/segmentation/ui/segment-profile-count.html?lang=en#profile-status-types
NEW QUESTION # 38
A Data Steward is asked to create a Data Governance framework.
Which two items must the steward consider during set up within AEP? (Choose two.)
- A. Communication
- B. Labels
- C. Permissions
- D. Policies
Answer: B,D
Explanation:
According to the Adobe documentation, policies and labels are two key components of the Data Governance framework within AEP. Policies are rules that define how data can be used based on data usage labels and destination labels. Labels are metadata tags that indicate the type, purpose, and usage of data and destinations. The Data Steward must consider these items during set up within AEP to ensure data quality, compliance, and governance. Reference: https://experienceleague.adobe.com/docs/experience-platform/data-governance/home.html?lang=en#data-governance-framework
NEW QUESTION # 39
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. Divide the size of each age group segment into the total sum of all purchaser events to get percentage splits for analysis
- B. Divide the size of each age group segment into the total sum of athletic shoe purchaser events to get percentage splits for analysis
- C. Create multiple segments which AND each age group attribute with athletic shoe purchaser events
- D. Create multiple segments which OR each age group attribute with athletic shoe purchaser events
Answer: B,C
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.
NEW QUESTION # 40
An Adobe Real-Time CDP Business Practitioner wants to create a batch segment of users for a financial services client who opened account in the last rolling 30 days. The analytics team needs an updated segment count prior to a campaign launch.
What would the practitioner need to do to achieve this task?
- A. Streaming segment
- B. Segment job
- C. Re-create the segment
Answer: B
Explanation:
According to the Adobe documentation, segment job is a feature that allows running an on-demand evaluation of segments using batch datasets and getting an updated segment count within minutes. Segment job can be used to achieve this task by selecting the segment and clicking on "Run segment job" from the action bar. Reference: https://experienceleague.adobe.com/docs/experience-platform/segmentation/ui/segment-job.html?lang=en
NEW QUESTION # 41
A Data Steward was recently hired to ensure data governance for a large insurance company. Which two roles will be part of their main job assignment? (Choose two.)
- A. Use data to design new customer experiences.
- B. Creating data policies and applying them to datasets and fields.
- C. Creating batch integrations and data schemas.
- D. Reviewing data, datasets, and data samples to apply and manage metadata usage labeling.
Answer: B,D
Explanation:
According to the Adobe documentation, a Data Steward is a role that is responsible for ensuring data quality, compliance, and governance across the organization. Some of the main tasks of a Data Steward include creating data policies and applying them to datasets and fields, reviewing data, datasets, and data samples to apply and manage metadata usage labeling, monitoring data quality issues and resolving them, etc. Reference: https://experienceleague.adobe.com/docs/experience-platform/data-governance/home.html?lang=en#roles
NEW QUESTION # 42
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. Desktop browsers
- B. Frequent Purchasers
- C. Past Purchase >30 Days
- D. In-store Purchasers
Answer: B,D
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). Reference: https://experienceleague.adobe.com/docs/experience-platform/segmentation/home.html?lang=en#segmentation
NEW QUESTION # 43
An Adobe Real-Time CDP Business Practitioner wants to create a segment of users who have purchased an item in the last 90 days and then purchased another item 5 days later.
What type of segmentation could be used?
- A. Frequency Segmentation
- B. Recency Segmentation
- C. Sequential Segmentation
Answer: C
Explanation:
According to the Adobe documentation, sequential segmentation is a type of segmentation that allows defining a sequence of events or attributes that must occur in a specific order for a profile to qualify for a segment. This type of segmentation can be used to create a segment of users who have purchased an item in the last 90 days and then purchased another item 5 days later. Reference: https://experienceleague.adobe.com/docs/experience-platform/segmentation/ui/sequential-segments.html?lang=en
NEW QUESTION # 44
A Real-Time CDP Business Practitioner wants to make Privacy Service requests for Experience Cloud applications. Which two categories of applications can they use? (Choose two.)
- A. On-prem applications
- B. Real-time applications
- C. Applications integrated with Privacy Service
- D. Self-serve applications
Answer: C,D
Explanation:
According to the Adobe documentation, self-serve applications are applications that allow users to create and manage their own Privacy Service requests, such as Adobe Experience Platform, Adobe Campaign Standard, and Adobe Target. Applications integrated with Privacy Service are applications that have built-in integrations with Privacy Service and can automatically process requests, such as Adobe Audience Manager, Adobe Analytics, and Adobe Experience Manager. Reference: https://experienceleague.adobe.com/docs/experience-platform/privacy/home.html?lang=en#applications
NEW QUESTION # 45
A publication who is an Adobe Real-Time CDP customer wants to reach users who filled out different forms to subscribe to newsletters on their site. When they create one segment of form 1 the size is 5,000 profiles. When they create a second segment of people who filled out form 2 the size is 10,000 profiles. However, when they create a segment that includes form 1 OR form 2, the number of subscribers is 12,000.
What explains why the segment size which includes both forms is 12,000?
- A. 3,000 people filled out both form 1 and form 2
- B. 12,000 people out both form 1 and form 2
- C. 3,000 people filled out form 1 or form 2
Answer: A
Explanation:
The explanation for why the segment size which includes both forms is 12,000 is that 3,000 people filled out both form 1 and form 2. This can be derived from the following formula:
Segment size of form 1 OR form 2 = Segment size of form 1 + Segment size of form 2 - Segment size of form 1 AND form 2 Plugging in the given numbers, we get:
12,000 = 5,000 + 10,000 - Segment size of form 1 AND form 2
Solving for Segment size of form 1 AND form 2, we get:
Segment size of form 1 AND form 2 = 3,000
NEW QUESTION # 46
A Real-time CDP business practitioner wants to fetch merged profile data of a customer across multiple data sources. Which two elements must match in the data sources for the profile to merge? (Choose two.)
- A. People identifier
- B. Identity value
- C. Namespace
- D. Profile ID
Answer: B,C
Explanation:
According to the Adobe documentation3, identity value and namespace are two elements that must match in the data sources for the profile to merge. Identity value is the unique identifier for a customer, such as an email address or a phone number. Namespace is the type or source of the identity value, such as Email or Phone Number. When two data sources have the same identity value and namespace, they can be stitched together to form a unified profile. Reference: 3 https://experienceleague.adobe.com/docs/experience-platform/profile/identity-service/overview.html?lang=en#identity-service-overview
NEW QUESTION # 47
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