The transition from the print to the digital age has been a difficult one for many in the media business. The news media in particular has struggled to find new, sustainable business models to replace the print advertising-based revenue model that allowed hundreds of news dailies and magazines to thrive across the country for most of the last century.
A handful of innovative media companies – both “old school” news operations such as the Associated Press & the New York Times and new media companies including Prismatic and Zite – are leveraging Big Data to deliver timely, relevant content to users and derive new lines of revenue.
In the case of the Associated Press, the company is using a NoSQL, document-oriented database to store and process news content going back to the 1970s. Developers at the 167-year-old company have created a content analysis application that uses Boolean logic to search against this data to deliver custom collections of AP news content for corporate clients. A pharmaceutical company, for example, might use the service to aggregate AP news content to identify historical trends or insights around a particular drug or compound being considered for development.
At the New York Times, the company uses Big Data tools and technologies to make its voluminous catalog of news content available to readers in a variety of formats. In one particular case, developers used a 100-node Hadoop cluster running on Amazon’s EC2 to convert all New York Times articles and other content going back to 1852 into searchable PDF files. Tthe Times monetizes this content by making it available to paid subscribers.
New media organizations, those that don’t have legacy infrastructure or business models to overcome, are also using Big Data to create innovative services that both serve readers and drive revenue. One example is Prismatic. Founded in 2010 by Bradford Cross and Aria Haghighi, Prismatic uses machine-learning algorithms combined with an elegant user interface to deliver personalized news content to readers. As readers use the service and provide feedback on their content preferences, Prismatic delivers ever more targeted content. The company is now experimenting with multiple ways to derive revenue from the service, including delivering targeted service offerings to users based on their reading preferences.
Another example is Zite. The mobile application, like Prismatic, uses Big Data to fine-tune content for its readers. In the case of Zite, the company’s Data Scientists are constantly refining its algorithms to deliver tailored content from hundreds of sources. After developing a new algorithm to better weed out “sensationalistic celebrity gossip stories,” for example, the company increased reader click-through rates by over 10 percent. Again, like Prismatic, the company continues to experiment with these and other innovative ways to both deliver content to readers and derive sustainable revenue streams.
Action Item: While the digital age has been hard on the news media business, it also offers significant opportunities for forward-thinking news organizations. Readers and viewers, thanks to social media, are freely providing news organizations with treasure troves of personal data that, if leveraged, can result in new forms of revenue for news media organizations. To do so, however, news organizations must embrace a culture of data-driven decision-making and an experimental mindset when it comes to analyzing the vast trove of reader data now available.
Footnotes: For a list of Wikibon clients, click here.
