Health Factor 6: Responsiveness

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After more than two months, we have finally reached the 6th and final blog on the current and future development of the community health index (CHI) and its health factors. I want to thank all of you readers out there for all the feedback; the analytics team at Lithium takes them seriously in prioritizing what we deliver. I guess this mini-series is getting too long and you are probably a little tired of it by now. So, let's nail it this time! Alright! On with the final health factor: Responsiveness. If you missed any of the previous blog in this series, they are: Traffic, Content, Members, Liveliness, and Interaction.

The Responsiveness Health Factor

In this era of information, there is no shortage of quality information, and because this information lives on the internet, it is nearly free to the end users. However, if this information is not delivered in a timely manner, it will lose its value. Therefore, time is a critical resource that is going to influence a user's experience when he/she is engaging with your community. A community that responds promptly will give the visitors a much better user experience than one that takes a long time to respond.

The responsiveness health factor is a measure of the average elapsed time between responses. It is very similar to the traditional time-to-response metric, which is generally defined as the elapsed time between the first message in a thread and the first response to that message. However, this traditional metric does not take into account the elapsed time between subsequent responses. So, you can think of this health factor as a more accurate version of the time-to-response metric.

Responsiveness also has a significant impact on user retention because visitors will abandon an irresponsive community altogether and spend their valuable time elsewhere. Therefore, this health factor can be interpreted as the perceived quality of engagement for potential visitors.

The Current and Future of Responsiveness

The current formula for computing responsiveness ignores threads that have no response, and the fraction of responded threads (or the response ratio) has no effect on this health factor. The response ratio was originally part of the responsiveness calculation, but it was removed when I found that it is highly correlated to the interaction health factor for the community. Since threads that have no responses will have zero interactions, these unresponsive threads are already penalized by their interaction health factor. However, people seem to inherently expect the response ratio to affect the community's responsiveness. To make CHI and the health factors accessible to a wider audience, I may need to formulate the responsiveness calculation in the future. Besides this minor point, we have not received much troubling feedback concerning this health factor.

Finally, I like to draw your attention to an important point about the three predictive health factors: Liveliness, Interaction, and Responsiveness. Recall that these health factors are predictive because they describe the intrinsic social dynamics within the community, and they tend to be leading indicators of community health. In practice, this means the predictive factors can often serve as an early warning sign to imminent problems. By analyzing these predictive health factors, you can take corrective actions against potential problems before they occur. So the predictive factors are also called actionable analytics.

Well, this concludes our coverage on all the health factors of CHI. Next time we will talk a bit more about how these health factors are combined. Stay tuned at mich8elwu.