Hi Jared, see below...
On Dec 4, 2007, at 2:56 PM, Jared Rhine wrote:
It seems like lots of the above is useful info for Hub users
too. Do you mean to collect the above specifically for Desktop
users, split off? I'm guessing it might wind up being difficult
to split the two categories even; for something like # of
editors, we might wind up with an aggregate of both Desktop and
Hub users making edits on an item.
I think it's important to distinguish between Desktop and Hub
users. I'd like to work towards understanding if there are any
qualitative differences between the way Desktop and Hub-only users
use Chandler.
Ok. I'm ok with trying to break Hub users up into these buckets of
"Desktop User" and "Hub User". We still need to get to a shared
understanding of what defines these buckets.
Top questions for me:
- Are there really 2 buckets or 3? Is every one of the 4,000 odd
users get tagged (somehow) as *either* a Desktop User *or* Hub
User? Or 3 buckets: "Desktop User", "Hub User", or "both"?
3 buckets would be good. By Hun User, you mean someone who's using
the web app. Not just someone who is syncing to the Hub Server?
_ If those are the only buckets, then what if the only client used
by a user if iCal or Lightning or Evolution?
We could also calculate Hub Service + iCal / Lighting / Evolution
users. Again, I think we'd want to know which of these users are
accessing the web app, versus just syncing to the server.
- What characterizes a Desktop user? Is it "if the user has ever
sent a request to the server which has their username via
Desktop"? (If they sync their Desktop to Hub, I'll see them with a
"user agent" of "Chandler/*" with their actual username, unless
they used a ticket (in which case I don't know who they are)).
Let's separate them then.
+ Desktop syncs that are associated with a particular account versus
+ Desktop syncs via anonymous ticket
In the future is there a way to dis-ambiguate the second metric?
I'm not (yet) saying there's a good, distinct way to sort each user
into these buckets. Without these buckets, answering a question
like "average number of edits per day of Desktop Users vs number of
edits per day of Hub-UI users" will be difficult. Once we
determine we can sort users into these buckets, then we face the
question of whether we can feasibly extract a metric like "number
of edits per day" now or need additional backend support.
-- Jared
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