This is the most effective workflow to send promotional discount offers to the target audience. By onboarding CRM data into AEP, the company can leverage the profile data and identity stitching features of AEP to create a unified view of their customers. By creating Adobe Analytics source connection in AEP, the company can ingest online behavior data from web and app into AEP dataset. By building and deploying a propensity score model in data science workspace, the company can use the machine learning capabilities of AEP to predict the likelihood of customers to purchase based on their profile and behavior data. By creating a segment in AEP using the propensity score, web visits, distance from store, and purchase order data attributes, 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 Adobe Campaign, the company can activate their segment across multiple channels, such as email, SMS, postcard, Google Display Ads, and Facebook. References: :  Onboard Data into Platform  :  Connect Adobe Analytics Data Sources  :  Data Science Workspace Overview  :  Create a Segment  :  Share Segments with Destinations

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. References: :  Schema Overview  :  Data Labels Overview

The correct answers are A, B, and C because they are valid options that can be added to modify the file name. The engineer can add date and time, counter variable, or custom text to make the file name more descriptive. The other options are not available or relevant for modifying the file name. References: https://experienceleague.adobe.com/docs/experience-platform/rtcdp/destinations/overview.html?lang=en

The correct answer is C because it matches the scenario given in the question. The user needs to use an aggregate of transaction events to create a segment based on the total amount spent on their credit card in the last 48 hours. The other options do not allow the user to specify the time frame or the amount spent. References: https://experienceleague.adobe.com/docs/experience-platform/rtcdp/segmentation/segment-builder-guide.html?lang=en

The correct answer is C because it matches the requirement given in the question. The engineer needs to create a segment that excludes customers who eat breakfast at their restaurants. The easiest way to do this is to use the existing segments and select “Must Not Exist in Breakfast Eaters”. The other options do not exclude all breakfast eaters or are too complicated. References: https://experienceleague.adobe.com/docs/experience-platform/rtcdp/segmentation/segment-builder-guide.html?lang=en

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. References: :  Onboard Data into Platform  :  Create a Segment  :  Share Segments with Destinations

The correct answer is D because it matches the scenario given in the question. The user can define time parameters for the segment in the attribute “Last_Website_Browse” or the event “Website_Browse”. The other options do not allow the user to specify the time frame of 30 days. References: https://experienceleague.adobe.com/docs/experience-platform/rtcdp/segmentation/segment-builder-guide.html?lang=en

The correct answer is B because it matches the requirement given in the question. The engineer needs to select “Enable Hashing” to hash the email address as part of the File export. The other options do not apply hashing or are not available for destination export. References: https://experienceleague.adobe.com/docs/experience-platform/rtcdp/destinations/overview.html?lang=en

This is the most suitable workflow to contact known prospects or customers who abandon before checking out. By importing customer data into the profile, the company can enrich their profile data with CRM information, such as email address. By setting up Adobe Analytics as a source, the company can ingest online behavior data from web and app into AEP dataset. By using segmentation to find profiles with email address and visited a product page and added to cart but did not complete checkout, 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 the segment of Abandon customers to Campaign and Target, the company can activate their segment across multiple channels, such as email, Google Display Ads, and personalization. References: :  Onboard Data into Platform  :  Connect Adobe Analytics Data Sources  :  Create a Segment  :  Share Segments with Destinations

The correct answer is A because it matches the requirement given in the question. The user needs to drag and drop email address and country attributes using ‘AND’ logic to ensure that the customers have an email address and are from the same country. Then, the user needs to create a container for painting and drawing and change the logic of that container to “OR” to ensure that the customers are interested in either painting or drawing or both. References: https://experienceleague.adobe.com/docs/experience-platform/rtcdp/segmentation/segment-builder-guide.html?lang=en