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Considering the restrictions that you’re running into, one solution could be to consider tagging users as “new” when they first join, and keeping that tag over time, even when they no longer satisfy that condition. It might demand some workaround in your system’s setup, but it could be worth a try. For retrospect analysis, try digging into the historical data where you have initial capture point of the user (their sign-up or first interaction date for instance).
If a unique identifier exists, it could be easier to track a cohort of new users and their progression. If such options are not present in your analytics platform, you might want to consider external tools or even custom setups where users are tagged with their start date. Large scale data platforms often have tools for cohort analysis which allows you to exactly do that.
Remember, you’re trying to change your user data categorization into a permanent attribute, rather than a fluid state. This allows you to track the behaviour of this group over time, despite the changes they undergo.
