On Mon, Jun 9, 2014 at 11:20 AM, Aaron Halfaker <[email protected]> wrote:
> Hmm... It's hard to evaluate your strategy without more context. Why are > you limiting your query to users with more than 10k lifetime edits? Are > your trying to generate a proportion of a subset of users? If so, what's > the denominator? > I ran the query with various editcount limits (0, 1K, 10K, 100K, 1M); the goal was to see whether power users are affected differently. (They are, users with 100K+ edits have the highest opt-out rates.) I am basically taking the ratio of ( <users with more than X total edits who have been active since the rollout and disabled MediaViewer> / <users with more than X total edits who have been active since the rollout> ) which in this case should be ( <count(*) for up_value = ' ' group> / ( <count(*) for up_value = ' ' group> + <count(*) for up_value is NULL ' group>) ) > Also, opt-out rates tend to be low no matter how obvious and desired they > are. If the goal of this analysis is to find out if opt-out rates are high > (or low), then I'd recommend comparing them with opt-out rates for another > feature. > Any tip for what that feature should be? Are there features for which opt-out rates have been recorded a few days after they have been deployed? (I imagine one problem is that opt-out happens slowly - although in the past two days our opt-out count grew about 20%, but the ratio to active users has been remarkably stable.)
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