Analytical functions are functions that allow users to perform complex calculations on data within a segment definition. For example, users can use analytical functions to calculate averages, sums, counts, ranks, percentiles, and more. Analytical functions can help users create more advanced segments based on derived metrics or attributes. References: : Analytical Functions Overview

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

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

This is the most suitable workflow to send personalized offers to existing customers who are within 50 miles of their nearest store, have made one of the following: visits to the website more than 3 times in the last 2 weeks, purchase of items worth more than $200 in the last 2 months,or have high propensity to purchase. 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 a segment in Adobe Target for visitors with high propensity score to purchase, the company can use the personalization capabilities of Adobe Target to predict the likelihood of customers to purchase based on their profile and behavior data. By importing the segment in AEP and combining it with 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 across Adobe Experience Cloud, the company can activate their segment across multiple channels, such as email, Google Display Ads, Facebook, and personalization. References: : Onboard Data into Platform : Create a Segment in Adobe Target : Create a Segment : Share Segments with Destinations

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

This is the most suitable criteria to create a segment based on all customers who currently have a home loan with the credit union, pay through auto pay, and have logged in within the last 2 weeks but do not have a credit card issued through the credit union. By selecting customer exists within the client dataset as an attribute, the company can filter out non-customers from the segment. By selecting customer has logged in within the last 14 days as an attribute, the company can capture customers who have shown recent activity on their account. By selecting customer has a home loan with the credit union and customer has auto pay set up for paying the home loan as attributes, the company can identify customers who have a specific product and payment method with the credit union. By selecting customer has not acquired a credit card as an attribute, the company can exclude customers who already have a credit card issued through the credit union. References: : Create a Segment

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