Data Science

Health Factor 1: Traffic

CHR2.jpgWelcome back. I hope everyone had a relaxing Fourth of July holiday. Last week, Lithium delivered a new report, the community health report, to our clients. This report contains two important pieces of new information: 

  1. The community health index (CHI): a score that reflects the "health" of your community.
  2. The community health compass: a radar chart that shows the relative value of the six health factors (traffic, content, members, liveliness, interaction, and responsiveness) that went into the computation of CHI.

Earlier this year we published a whitepaper on CHI. Since then, however, we've refined the CHI algorithm based on data from real-world use cases along with customer feedback. So for this post, I'd like to talk about the current state and future direction of CHI.


The Traffic Health Factor

Let me begin with the health factor you are most familiar with: Traffic. This health factor is most important when you are launching a community. If no one comes to your new community, the community will fail. As the community matures and acquires a large core of active users, the effect of traffic may become less important. This is because traffic reflects only the passive engagement of the visitors with the community. In a public community, visitors can accomplish quite a bit without any active contribution. For example, they can read messages, search for answers, navigate the community, checkout other members' public profiles, etc. These activities are considered "passive" because the visitors merely consume existing community content, but do not add content of their own. 


Measuring Human Traffic is Not That Simple

In short, the traffic health factor is intended to measure the amount of human visits to the community. However, traditional page-view metrics also counts non-human visits by web robots and crawlers. Moreover, counting page views on a modern AJAX-filled website is not trivial. Because Web 2.0 technology furnishes users with a wide variety of interactions on a very dynamic webpage, users can potentially visit many places and perform many activities without refreshing the page. As a result, behind-the-scene REST API calls, RSS feeds, or any server-rendered pages go unnoticed to conventional page-view trackers such as Google Analytics.


The Current and Future of Traffic

In the current formulation of CHI, traffic is measured by Lithium's own PageView metric, which includes REST calls and any server-rendered pages. Although our preliminary study suggested that robots and crawlers do not significantly affect the final CHI score of the community, we intend to remove their contribution to our PageView metric in our next formulation of CHI. However, since robots do not always declare their identity (in fact some crawlers may even intentionally disguise themselves as human visitors), it is not possible to completely remove the effect of robots and crawlers. Despite this, through iterative reformulation, we hope to derive a traffic health factor that can track the passive engagement of human visitors more accurately.


I hope this post gave you a better understanding of the traffic health factor. Next time, let's talk about the content health factor. In the meantime, feel free to continue this conversation in the comments section below.





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