Newsroom's challenges in using analytics and A/B testing



Many digital media companies start using analytics and A/B testing technique to see what will and will not appeal to online readers

Editors, equipped with insights from increasingly powerful computers, must make decision on their owns. Giving the analytics to journalists will require time since the latter needs necessary set of skills to translate the data sets into relevant leads. 

No wonder, editors should think about applied machine learning to help describe the condition, predict the outcome and prescribe necessary steps and strategies. 

The good news is most newsrooms have already been through the first stage. There is a new habit acquired by editors to collect data and therefore allows them to have insights into the past. Online analytical processing, OLAP, has become part of the routine in most large newsrooms. 

However, the challenge is to upgrade the newsroom capability to start peering into the crystal ball of prediction. Current technology allows us to predict behavior or outcome in the future and make better anticipatory efforts, based on, for example, analysis over the risks and hindrances. 

The only thing holding back from embarking on the prediction stage is the quality of the data analytics. Most insights often comprise incomplete and inaccurate data sets and become a challenge to structure them and still provide new yet relevant insights. 

The most advanced stage of the use of analytics is to prescribe actions to ensure the future. It is more than predicting what may happen in the future but more importantly, let the analytics and machine learning identifies patterns and with the help of human intelligence, interprets meaningful links between patterns to understand holistically the behavior and eventually come up with recommendations regarding a certain course of action. 

In the beginning, when the machine runs its processes taking over the jobs being done by humans, there is a mixture feeling of loss and fear. The loss of jobs and sense of relevance will intensify by the more machines encroach into the business lives. However, by the time they fully evolve, the machine learning will have faded into the background, the same as the innovations of the 20th century. 

At the end of the day, the collaboration between the machine and human will prevail as the eventual victors. 

By Damar Harsanto