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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?
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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?
Correct : D
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.
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An Adobe Real-Time CDP Business Practitioner needs to exclude certain opt-out events from all segments used in off-site targeting by a company data governance policy enforcer.
Which type of data usage label should be applied to this data?
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A Real-Time CDP Business Practitioner has composed a schema and a dataset has been created that references that schem
a. Data is then ingested and stored in the Data Lake.
Which Platform service is the best place to analyze the data to support different use cases?
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Where would a Real-Time CDP Business Practitioner go to search for Profiles by Merge Policy in the Ul?
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Total 50 questions