Hello everyone, and welcome to Building Community, Lithium's blog about the platform. Just as in the past, I will continue to cover analytic science and research here at Lithium. Today, I will talk about a refinement in the community health report that slightly altered the information displayed on the CHI compass that many community managers are receiving today.
However, some health factors have very different ranges of values, for example, weekly values for members may range in the hundreds, where as content (posts weighted by views) and traffic (views) may have values over 10K or 100K. On the other hand, liveliness, interaction and responsiveness, have much smaller values in the tens or, in some cases, less than one. With such large variation in the scale of the data, it means we have to normalize these values before we display the CHI compass. Otherwise the small weekly variations in the smaller values would not be visible against the large variations in the diagnostic health factors.
Here is an example that I've generated with Excel. In this example, liveliness had a very significant 100% weekly increase (from 1 to 2, 2 to 3, then 3 to 4) during the first 4 weeks. But it is relatively unnoticeable when plotted in the radar chart against the other diagnostic health factors, which have much higher un-normalized values.
One of the insights that came out of Lithium's research was that even though you may launch a community with a specific purpose (such as key benefits like Innovate, Promote, or Support,) depending on the interaction at any particular period in time, you will find that a community can adopt the multiple traits, and these traits can change over time. For example, support communities often behave like enthusiast communities after product launches. Likewise marketing and sales oriented community can also behave like a support community and answer technical questions from the enthusiasts.
The shape of the CHI compass was designed to actually show what type community behavior is taking place. Thus, the shape can tell you whether your community is trending towards an innovation, promotion, or support community. However, this design requires a particular normalization scheme that normalizes the predictive health factors as a group. Because the liveliness factor generally has a smaller range of values than interaction, it appears much smaller when normalized and put on the same scale as interaction. People often interpret this low value as the community not being healthy whereas the community might be perfectly fine. The relative position on the compass is purely an artifact of trying to show the typology information on the CHI compass.
Under this normalization, the same community would look like the following. The outward bulge in interaction is the characteristic signature of an promotion community.
Rethinking the Visualization
So, on to the changes. After hearing many inquiries about how to interpret the CHI compass, we've decided to go with a simpler and more intuitive normalization scheme and remove the community typology information from the CHI compass.
We simply normalize each health factor to its best previous performance (over a 6 month window). If you outperformed the 6 month best score, your health factor will be 100% that week. This will redefine the new standard for which to normalize your future scores. So a growing community should hit 100% periodically, which indicates improvements over the last 6 months.
With the new normalization, the very same community would look as follow.
Some of you may ask..., if the shape of the compass doesn't indicate the community type anymore, where do we get that information? Don't worry, the community typology information is not lost, we will design another widget specifically for displaying that data!
I hope that gives you an insight into the changes in the CHI compass, and why we thought it is important. As always please let me know if you have any questions or would like me to cover particular topics.