I'm looking at identifying trends within my data, particularly wondering if usage of my app on new sign ups is increasing over a week to week basis.  As we are constantly improving our product, I'd love to be able to identify a correlation between app usage & new feature releases.   The data I have is split into weekly cohorts.  Each week I have the number of new sign ups, and how many of those accounts are still active (e.g. users are logging into the system).Let's say I have the following dataWeek 1 - 10 new trials, 3 accounts activeWeek 2 - 15 new trials, 5 accounts activeweek 3 - 4 new trials, 3 accounts activeweek 4 - 20 new trials, 12 accounts activeweek 5 - 17 new trials, 9 accounts activeIn my current approach of analysis, week 3 looks amazing because 75% of accounts are still active ... In reality though, the number of new trials is extremely small compared to other weeks.  As a result, I don't feel like I'm accurately comparing apples to apples in a week to week comparison.Is there a way I can normalize the weekly data so that I am performing accurate analysis - or is percentage based really the best way to look at this data?      I am pretty new to this, so any help is much appreciated.  Cheers
normalize usage data
correlation;normalization