Data intelligence is the future of journalism — even a 162-year-old publication knows that — which is why when the New York Times hired a data scientist, no one flinched.
Data intelligence is the future of journalism — even a 162-year-old publication knows that — which is why when the New York Times hired a data scientist, no one flinched. Startups like PolicyMic and UpWorthy have been using data analytics and — yes — data scientists to beef up their headlines, only putting out there what the numbers show their audiences are most likely to click on.
Doing so has gotten PolicyMic, a 3-year-old digital publication aimed at millennials, founders on the Forbes 30 Under 30 list in 2014, and a combined Facebook and Twitter following of nearly 150K. For UpWorthy, the use of click-baiting, as you may know it colloquially, has put the 2-year-old “mission-based” digital publication on the up-and-up, beating out Mashable, The Huffington Post and even Buzzfeed on Facebook. Only Mashable outwits the publication on Twitter — though that may soon change.
Digital publications like these claim that their articles concern what people online want to see, which is what truly drives their traffic — but BuzzFeed easily proves pictures of cats can do just as well as an educated listicle about this year’s rising feminists on PolicyMic.
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In truth, conversion from social media to the startup publishers is what drives their success — and using data points to find those who will most likely convert is what has made the industry look twice.
The New York Times, though, is not one to be outdone and their new data scientist has decades of experience unraveling the most difficult data sequence humanity has ever faced — that of our own DNA. In an interview with Fast Company, Times new hire Chris Wiggins, a biology researcher with a PHD in Theoretical Physics, said, “The pain that many fields are experiencing by becoming data driven is a pain that was experienced in biology 15 years ago when whole genomes started being sequenced.”
So, what does Wiggins plan on doing with the Times‘ data to bridge that 15-year gap? Feed it to machines as machine learning tasks. In other words, he’s looking to create algorithms that predict your behavior, the same way Netflix recommends a movie, Amazon a book or biology a new evolutionary trait.
Fortunately for publications or companies without a New York Times budget, you don’t need a biology researcher as your data scientist to target your users based on machine learned algorithms. All you need is in-depth audience intelligence — and Digital Genome technology provides just that.
“Anytime anyone does anything on a website, that is an event and that person leaves a trail of data,” Wiggins told Fast Company. “Putting all of that data together is definitely a non-trivial task. It gives so much immediate insight into the way people use your product, how your products can be improved, what new products you should be thinking about.
I think that’s a real transformation for anybody in any business.”
