Technological Transformation in Journalism: Bringing about a Digital Revolution in the News Media Industry
Technology has proven to transcend industry-specific boundaries, and it’s not too much of a surprise to see longtime users of legacy hardware; such as hospitals and their pagers; turn to better, more efficient technologies. News media and journalism in particular, are among the long list of industries that have started to bring about an internal digital transformation, taking age-old procedures and tactics into the digital realm, all in an effort to reach their customer and engage for longer.
Popular Brazilian newspaper house Correio Braziliense experienced the digital revolution last year, when they revamped their entire approach to reader analysis and internal operation strategy. Theirs was a more direct approach, being driven from a grassroots level, backed by the already techno-centric mindset of the young employees. Once again, not difficult to imagine, since according to a Pew Research survey, around two-thirds of adults based in the US received the majority of their news from social media.
This ‘sharing economy’, which is centered around the horizontal distribution of news, and supported by an overwhelming influx of citizen journalism, is the basis for the digital transformation we are seeing in journalism and news media. And, the one key ingredient of said digital transformation, the one that news organizations across the world are leveraging in order to ‘break the story’ first; is Data Science.
In a climate when the reader decides what they see and hear in terms of news, news media organizations have shifted their focus from maximizing distribution to reader analysis and platform optimization. Today, metrics such as views from regular visitors, total engaged time and general views are far more important, in cross-channel reader analysis, and cloud-based multi-functional platforms are the foundation on which a news agency can build their digital presence.
Data Science fundamentals, which comprise visualization basics and software-centric training, can instill valuable working knowledge in terms of reader analysis and forming data measuring and sifting systems. For practical application of data science concepts, Applied Data Science training is needed; to leverage AI and machine learning, as well as platform-specific data science, and develop a working data analysis and insight-management framework. And finally, Data Engineering training delivers a high-level understanding of complex data-based constructs and platform strategies, all through software primed for the purpose.
For any news media company looking to bask in the digital glow; it is necessary to look beyond the platform and into the reader base, in an effort to better understand what a reader wants to read, when they want to read it, and how best to keep them reading!