The Publishing Industry has always had two goals, to have content purchased and consumed. Achieving these goals has become objectively harder in the age of the Internet. However, the Publishing Industry has found new and creative ways to use Big Data in order to improve consumer engagement. Big Data has made it easier for publishers to personalize content and target particular consumer segments. Big Data gives publishers the ability to optimize revenue streams, by tracking ad impressions and providing insight into different revenue streams. That’s not all Big Data is doing for publishers. It’s also being used to track which content sells, and which content is read vs. unread.

Publishing User Stories

Only a few short years ago, the Publishing Industry was in a downward spiral. Consumers had moved to the Internet for their content, and many struggled to leverage the new technology. Since then, publishers have found new revenue streams with the help of Big Data. For instance, customer segmentation gives publishers the ability to sell ad space to companies particular segments find relevant. Big Data analytics also provides retailers with insight into their best revenue streams. A publisher can identify which content to keep free vs. which content to require a paid subscription. Tracking impressions on advertisements shows which content is the most likely to lead to conversions for advertisements, providing valuable leverage when selling ad space. Big Data has given publishers unprecedented insight into how their content is received by consumers, and in turn provided them with unique new ways to increase revenue.

Personalized content is crucial to a publisher’s success in the modern era. Targeting the right content to the right audience is the difference between the most successful publishers and those who find themselves going out of business. With modern Big Data tools, publishers can extract information from those reading their content to gain further insight into their target audience. Publishers couple this information with social media analysis to build brand loyalty and further readership. Once a user is viewing content, a publisher can further engage them by recommending similar content, further increasing revenue. Publisher’s can also monetize their data by selling the data they have collected from their audience to other companies. There are numerous ways to monetize data online, and publishers have found it is possible to survive the shift from physical content to web-based content.

Big Data has done more than improve revenue streams for the Publishing Industry. It’s also being used to improve operations and reduce risk. As books continue to be formatted online, publishers have begun to track what’s selling the best and why. With Big Data analytics, a publisher can track what’s selling the most and how much of what’s selling is being read. Maybe a book is selling quite well, but consumers typically stop reading halfway through. Or a book has low sales numbers but has raving reviews and limited consumer drop-off. With this information, a publisher can correct a problem with the content of a book, and improve marketing efforts for a highly rated, yet largely unknown book. This insight would never be gained without Big Data. Big Data analytics give publisher’s better understanding of which authors or franchisees to invest in, which in turn limits risk and improves profit margins.

Publishing Use Cases

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