Assuming I have a definition of a user I can calculate sum of all daily users and all monthly users.
customEvents
| where timestamp > ago(30d)
| where <condition>
| summarize by <user>, bin(timestamp, 1d)
| summarize count() by bin(timestamp, 1d)
| summarize DAU=sum(count_)
customEvents
| where timestamp > ago(30d)
| where <condition>
| summarize by <user>
| MAU=30*count
The question is how to calculate DAU/MAU? Some join magic?
Edit:
There is a much easier way to calculate usage metrics now - "evaluate activity_engagement":
union *
| where timestamp > ago(90d)
| evaluate activity_engagement(user_Id, timestamp, 1d, 28d)
| project timestamp, Dau_Mau=activity_ratio*100
| render timechart
The DAU is really stright forward in Analytics - just use a dcount.
The tricky part of course is calculating the 28-day rolling MAU.
I wrote a post detailing exactly how to calculate stickiness in app analytics a few weeks back - The trick is that you have to use hll() and hll_merge() to calculate the intermediate dcount results for each day, and then merge them together.
The end result looks like this:
let start=ago(60d);
let period=1d;
let RollingDcount = (rolling:timespan)
{
pageViews
| where timestamp > start
| summarize hll(user_Id) by bin(timestamp, period)
| extend periodKey = range(bin(timestamp, period), timestamp+rolling, period)
| mvexpand periodKey
| summarize rollingUsers = dcount_hll(hll_merge(hll_user_Id)) by todatetime(periodKey)
};
RollingDcount(28d)
| join RollingDcount(0d) on periodKey
| where periodKey < now() and periodKey > start + 28d
| project Stickiness = rollingUsers1 *1.0/rollingUsers, periodKey
| render timechart