AD7-E601 Questions and Answers

This is the most suitable criteria to meet the requirement of sending 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 selecting hasUpgraded=false as an attribute, the company can filter out customers who have already upgraded to the latest smartphone device. By selecting emailOptln=true as an attribute, the company can filter out customers who have not opted in for email communications. References: : Create a Segment

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

Merge policy is a feature that allows users to define how data from different sources should be merged into a single profile. Users can specify the priority of data sources and the rules for resolving conflicts. This way, the company can use the unreliable data source as a backupsource only when the other sources do not provide the mobile number. References: : Merge Policy Overview : Merge Policy UI

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 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