I’m looking at ways to measure community in a qualitative way.
In some senses, quantitative data is much easier to collate,
Some examples may be:
- Traffic, showing up
- Event attendance
- Are members referring other members
- Inbound links referencing community work published
- Number of discussions / comments
- Community content published (articles, videos, podcasts, etc)
Qualitative can be harder, or more manual to capture:
- Thank you’s
- Feedback
- Member wins
- Collaborations
- High quality discussions
- Members helping each other out
- Deep community/product insights
I’m curious as to what qualitative data you find helpful to capture.
And also, do you capture it in any way?
The CHAOSS community is a fantastic resource here, but ultimately I STRONGLY recommend using Grounded Theory Analysis and structuring your journal information around a very clear theory - I prefer doing Social Currency Theory 
Here’s a presentation where I spoke about using social science to present ^^
and although it’s pretty old, here’s an introduction to the SCMS
In short, however, here’s how I recommend going about this:
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Start with a field journal of 6 columns in a spreadsheet. don’t be fancy: (date/time, journal entry, category for the entry, disposition (positive/negative), and notes
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Start building that journal to include user sentiment. Start by copy/pasting but eventually bring data in using a Community Intelligence Platform or API to a BI tool.
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Start building a social-scientific structure to identify, analyze, structure, and understand the results consistently over time. Truth is in the trend, power is in the pattern.
