People generally have the expectation that such surveys are anonymous and that results are only gathered in aggregate. It is also safer. It looks like you have realized the value of these propositions.
So: Wouldn't you still be able to achieve your intention by survey respondents revealing their previous framework exposure? Like checking "I have mostly experience with..." React / Vue / Angular, etc. Then you could see the influence of audience shifts.
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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Thanks for the quick reply. Two concerns:
People generally have the expectation that such surveys are anonymous and that results are only gathered in aggregate. It is also safer. It looks like you have realized the value of these propositions.
So: Wouldn't you still be able to achieve your intention by survey respondents revealing their previous framework exposure? Like checking "I have mostly experience with..." React / Vue / Angular, etc. Then you could see the influence of audience shifts.
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.