Your measurement strategy will change over time.
Sometimes it changes because your objectives for the community, your goals,
have changed based on the stage of maturity of your community.
In the first hour, day, week, month, generally,
you're just trying to get the engine running.
So the kinds of metrics that you're measuring are very basic, right?
Are people who are coming to the community registering?
A simple ratio of visits to registered members.
Are people who are registering participating, right?
A simple ratio of members at any given time and posts, for
example, in the system.
Are people getting an answer to their question if it's a forum
discussion, right?
A ratio of initial posts or topics to replies.
And so in the early days you're building that just to understand,
gosh are most people getting an answer?
Are most people who are coming here at least exploring
the process of measuring it?
And in the early days you're simply, again,
trying to get those to a certain level of health, let's just say.
But then once you've got your community healthy and growing,
then you're going to move on to basically say, okay,
where do I want to direct this community for its benefit and for ours?
So this is a really good, I think,
overview of what's happening in the analytics environment at the moment.
Where do you see all of this heading towards within the next five to ten years?
I've been doing this for almost 20 years, since the mid-90s.
And one of the things that's always frustrated me about all these platforms
is, I always joke, and developers always hate when I say this, but I say,
your social platform can answer any question you have.
As long as that question is not, who are my users and what are they saying, right?
[LAUGH] Because you could never tell who my users were because
it was largely pseudonymous.
Because it wasn't linked to a database of users we could validate, right?
I mean online interaction is often you don't know who you're dealing with, right?
So, that's one analytic challenge, is to better understand,
even if you know their identity, you might not know their needs and
their preferences and their interests and their expertise.
All of those things you really need to know, I think as a community manager.
But there 's another aspect of that as well, which is the, what are they saying?
And you might say, well, wait a minute, can't you tell what people are saying,
isn't it all public out there?
But it's the big data problem.
Yeah, you can find out what they're saying
if you have a week to spend getting everybody's opinion, right?
But how will the platform helping us understand?
How are they teasing out hot topics?
Things that are exciting people, things that are making people angry, you know.
Valuable content that when people read helps them solve problems or
move on to the next level of proficiency.
And for most people creating communities, we want to be respectful of their privacy.
And we want to create profiles, but allow them to manage those profiles so
that they can control what they reveal to us.
And then on the content side, it's just the text analytics challenge.
It's taking a vast amount of unstructured data and creating meaning from that.
And that's a hard computer science problem.
And anybody who tells you that that's solved [LAUGH] is wrong.
It's a work in progress.
So, those are the two things to me, those are the questions to me, right?
[LAUGH] These are the ones you must answer.
Joe makes some great points about how data can enable us to identify fundamental
issues with online communities, such as how many people are logging on,
what do they click on, and where do they go when they're on the site?
But Joe also notes this may indicate broader concepts.
Like are they happy with the community, if they're successful using the site,
and if the users are accomplishing their goals.