Summary:

Mining terabytes of data isn’t just for service providers — media companies are also trying to make use of the oceans of information they have about their users to come up with better ways of recommending news to them, says Bloomberg Digital head Kevin Krim.

Kevin Krim, Bloomberg, at Structure Big Data 2011

Kevin Krim, Bloomberg, at Structure Big Data 2011Mining through terabytes and zettabytes of data isn’t just for hardware companies and database-service providers — media companies like Bloomberg are also trying to make use of the oceans of information they have about their users to come up with better ways of recommending news to them, Bloomberg Digital head Kevin Krim told the Structure Big Data conference in New York City today.

In an interview with Stacey Higginbotham, the Bloomberg executive described how he built a predictive-analytics team within the media conglomerate that could use the behavior patterns and usage patterns of the 20 million users who visit Bloomberg.com or BusinessWeek.com (which Bloomberg acquired last year) to make better recommendations about what topics or articles they might be interested in.

The approach that most traditional news services take, Krim said — in which editors select and present the news that they think matters most to a generic reader — “doesn’t really scale very well.” But by using analytical tools on the data about those web visitors and their reading patterns and usage, Krim said that Bloomberg can “present 20 million different views of that information.” The company is also trying to take into account the differences in how users want to receive their news during the day, including whether they want content as text they can read on their laptop or mobile, or video they can watch, and so on.

The company now collects over 100 data points for every page a reader loads, based on what they interact with, what time of day it is, etc. — more than a terabyte of data every day in aggregate, Krim said — and the team has 15 different algorithms running in parallel to make recommendations for what that reader might want to see next.

“We started studying the behavior of decision makers who come to our site,” Krim said, “and we noticed that there are a number of different usage curves of news… TV is kind of a U-shape during the day, web usage is like an arc, mobile is like an oscillating curve, magazines ramp up during the day, and newspapers obviously ramp down during the day.” What Bloomberg Digital is trying to do, he said, is to understand how people move from one to the other, and then present information to them in the way that they want.

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