Which are valid covariates in CausalImpact?

I am working lately with CausalImpact developed by Google. The paper described it is this one Inferring Causal Impact Using Bayesian Structural Time-Series Models

In short, what you can do with CausalImpact is study the effect of a specific event in your time series. In the above paper, they mention the importance of covariates or control groups where you use together with your time series.

The first is the time-series behaviour of the response itself, prior to the intervention. The second is the behaviour of other time series that were predictive of the target series prior to the intervention. Such control series can be based, for example, on the same product in a different region that did not receive the intervention or on a metric that reflects activity in the industry as a whole.

However, I have seen a couple of blog posts around the web using totally unrelated time series as covariates. One of those is a study on the Daily Active Users in World Of Warcraft using page views of Wikipedia articles. This is the link www.datascience.com

Comparing to the original CausalImpact paper, it looks totally wrong, but taking into account the resource of the post (datascience.com from Oracle) and also other related examples confused me on what is exactly the right and wrong.