AD7-E601 Sample Questions Answers

On-demand evaluation is a feature that allows users to manually trigger segment evaluation and see the updated segment size immediately. Waiting for the next scheduled evaluation is another option, as segment evaluation runs periodically based on the segment refresh interval. References: : On-demand Segment Evaluation : Segment Evaluation

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. References: : Streaming Ingestion Overview : Create a Segment

Governance policy is a feature that allows users to define how data can be used for different destinations based on data labels and marketing actions. Data labels are tags that indicate the sensitivity or classification of data, such as PII or opt-out. Marketing actions are categories of activities that describe how data is used for a destination, such as personalization or analytics. By creating a governance policy, users can connect policies with data labels and enable data usage enforcement for that destination. References: : Governance Policy Overview : Data Labels Overview : Marketing Actions Overview : Create a Governance Policy

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

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. References: : Create a Segment : Schedule Segment Export

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