Getting the Most Out of Community Metrics

I was the community manager of the Catalyze Community – a B2B niche community for business analysts and usability professionals – from its inception in early 2007 and oversaw its growth to over 4,000 members in July 2008.  During the 18 months under my leadership, tracking and analyzing metrics was an important part of my job.

I tracked a number of metrics on a weekly basis.  Half of the stats came from Google Analytics and the other half were derived from a standard report from Mzinga, our community vendor.  Using Excel, I created a spreadsheet to track all of the stats on a weekly basis in one place.  It is critical to track these statistics on a weekly basis in order to have the necessary information to monitor the trends and health of your community.  Sometimes it felt like a pain to pull the numbers, but it really only took 15 minutes or so per week to pull the raw numbers and then some additional time to study what it all meant.

You should also keep in mind that the metrics you are tracking will change over time as a community evolves.  In our case, we were totally focused on member growth and pageviews in year 1 of the community and were starting to swing the importance to member engagement for year 2 of the community.

Here is a picture of the spreadsheet I used for the Catalyze stats:

Catalyze Community Metrics

Catalyze Community Metrics

From Mzinga, we tracked information on member growth, posts to blogs, forums and resources and resource downloads and views.  From Google Analytics, we tracked traditional website stats such as visits, pageviews, bounces, number of pages visited and average time on site.

I cannot say enough about Google Analytics.  First, its free.  Second, it allows you easily select the time period to analyze and the quality and ease of use for the interface is rare for Google.  Third, did I mention that Google Analytics is free?

I also calculated a couple of additional metrics from the existing statistics.  The most interesting one for us was “Visits as a % of Total Members”.  I used this as a proxy for what percentage of our membership was visiting the community on a weekly basis.  Our average % was 40%, but it ranged from 25% to 50%.  The weekly variance was definitely impacted by the frequency of the bi-weekly email updates and by the quality of our content.

On a quarterly basis, I also took a complete download of our member data and created a series of cross-tab reports to analyze additional information about our member base.  The data for this analysis was collected during our registration process, but most of it was clearly labeled as optional.  Still, more than 75% of our members voluntarily provided us with their data.  Using this data we were able to identify frequency of visits, geographic origin, size of company, interests, and membership in other groups.  Using this information, I was able to create a special email update for members who had not re-visited our site since they registered.

Based on my experience with the Catalyze Community, I would recommend that you:

  1. track key statistics on a weekly basis
  2. turn on Google Analytics for your community site
  3. never get too complacent with what you’re tracking

Of course, I was never satisfied with what we were doing with our community metrics and constantly pushed our vendor to make it easier to get to additional data.  I will devote a future blog post to discuss my Community Metrics Wish List.


3 thoughts on “Getting the Most Out of Community Metrics

  1. Pingback: More on Community Metrics « Musings by Tom Humbarger

  2. Great post… George – we’re struggling to get Harvest up and running, but hope to have it up soon. I’m using MS Ad Center (similar to Google Analytics) and am just now starting to flesh out a dashboard of sorts.

    Harvest, even when we get it running isn’t a complete solution because it’s missing some info like time spent on site.

    One thing I’m strugglng with is how to filter out traffic I don’t want to count (testers, other employee etc.). IP filteirng might work, but it’s a moving target at best.

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