I don't think that achieves quite the same thing. I think the simplest solution is to have two datasets, one without any kind of identifiers for the general public and one with (secure) identifiers which we would only make available to data researchers who want to specifically do a cohort analysis if they get in touch with us.
What would be the limitation? Unless you actually want to model the relationships between the influencers and their audiences, I don't see how you actually need to track personally identifiable information to track trends in demographics...
If we want to track how cohorts evolve over time then we should just track that in a secure manner; or not track it at all if we can't do it right. It just seems like a simpler approach than finding some other more "fuzzy" metric to use as a proxy.
The question is if it's really necessary to track 'cohorts' per se? With the security risk and disfavored UX it entails. If you can get a decent enough statistic from other more aggregate means.
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I don't think that achieves quite the same thing. I think the simplest solution is to have two datasets, one without any kind of identifiers for the general public and one with (secure) identifiers which we would only make available to data researchers who want to specifically do a cohort analysis if they get in touch with us.
What would be the limitation? Unless you actually want to model the relationships between the influencers and their audiences, I don't see how you actually need to track personally identifiable information to track trends in demographics...
If we want to track how cohorts evolve over time then we should just track that in a secure manner; or not track it at all if we can't do it right. It just seems like a simpler approach than finding some other more "fuzzy" metric to use as a proxy.
The question is if it's really necessary to track 'cohorts' per se? With the security risk and disfavored UX it entails. If you can get a decent enough statistic from other more aggregate means.