analytics_trial
analytics

As a physicist, analysing data and recognising patterns is part of my DNA. Someone said that even when we – physicists – understand something in hindsight gives us valuable insights, so that we can learn and improve.

 

This concretely means at the Courier to answer the question what the CERN Courier community wants and at which points we can improve. The Courier’s Twitter and LinkedIn accounts reveal many insights about who is our audience. Here, I analyse measures such as the reach, the number of likes, the engagement rate. The latter is vital because these people connect very often on social media and are the Courier’s heart. That written,  the rate is just a percentage but I can see if the rate rises or falls. 

 

But this is not the only interesting question to answer: At which time should we post our messages? Is this the same time across all platforms or are there different times?

 

I therefore made use of my background as a data scientist at gluoNNet and so I quickly created a user interface that visualises the insights in seconds and I can easily modify the parameters.