2 ms·
The best thing about 95% of the users is that potentially no one is actually in that group. Because product features don't exist in isolation. 95% of your user
by XorNot 3y ago
The best thing about 95% of the users is that potentially no one is actually in that group.
Because product features don't exist in isolation. 95% of your users can share a pool of common features, but then every single one of them can have some divergent, extra feature as an utterly vital component of their workflow - without which the product does not fit.
Leading to the paradox: you eliminate features which aren't used by 95% of the user-base when looked at in isolation...and at the end of the day, your product isn't still suitable for 95% of the users, it's potentially usable for 0% of them.
- crabmusket 3y agoDoes anyone know what the appropriate type of statistical analysis would be if I wanted to try to discover groups of commonly used features? Say I have a spreadsheet where the rows are users and the columns are "has used feature X in the past 30 days". How do I go from that to "there are three clusters of users who tend to use these distinct subsets of features"?
- xapata 3y agoClusters make a nice story, but you're going about it backwards. What are you trying to predict? The scientific method suggests we create a hypothesis first, then design an experiment (or identify a natural experiment), then collect data, and finally perform a hypothesis test. Deviations from that process increase your risk of spurious results.