Based on the given description, I understand that you want to remove users from traits/segments at a specified interval.
With AAM, you can do so with the help of recency/frequency settings. TTL is also one way to remove users from Traits.
These settings work at day level and not at time, so setting users to expire from trait/segment at 8:00AM is not possible right now but you can do the same with the help of above settings.
Also, we have offline method as well using which you can onboard data with d_unsid parameter in it which can remove users from a given trait but this will take 48hours of time to reflect in the reporting. For more details, please follow this link.
I hope this helps! Please feel free to reach us back for any additional question.
We are using onboarded traits and looks we cannot use 'recency/frequency' settings for these traits.
Below is our use case, can you suggest better way to manage these segments?
Use-case: To manage lifecycle segments of customer, and these lifecycle status gets generated in our data lake and gets pumped to AAM. The life cycle status looks like, 1) lead 2) subscriber 3) cancelled 4) churned and we want to mange relevant segments in AAM.
But the issue is, there is no easy way to remove user from 'lead' segment in AAM once he disqualified for lead.
1) Cannot use Recency/Frequency since these are onboarded traits
2) Cannot use d_unsid parameter, since they might take 2-3 days to process and remove the user from that segment.
2) Cannot use TTL, since they might take 2-3 days to process and remove the user from that segment, as its onboarded file.
Is there any efficient solution, atleast where we can get correct segment in one day lag (atleast)? Ideally we want real-time but looks AAM cannot do it.