How does Mashable use Big Data to create more compelling content from the editorial operation? 

Big Data is essential to the operation, Jim Roberts, the company’s executive editor and chief content officer, told delegates at INMA’s Big Data for Media conference at Google London on Thursday. Mashable has a small staff and relies on data to enable it to find stories, as well as to understand audience behaviour.

Data allows Mashable, which employs 60 reporters globally, to successfully compete with news organisations that employ thousands of reporters, such as The New York Times, which employs around 1,100. 

Roberts, a former editor at The New York Times, said that in the past journalists, including himself, did not understand the role of data.

“For decades, newsrooms weren’t on good terms with data. Editors paid more attention to their budgets. Most of us had no clue about what our audiences were consuming and … for the most part we didn’t care,” Roberts said. “Our attitude was we know what news is. We are the people trained to do that.”

He said the only thing that mattered was that readers kept buying the newspaper.

“In fact, most of us thought that if we only published what the audience were interested in, we would end up publishing fluff,” he said.

But Roberts said that since arriving at Mashable, his attitude towards data has changed: “Many people in the news business fear data because it will tell them they are doing something wrong. But I can assure you that data is our friend — in fact it is our lifeblood at Mashable.”

The Mashable Web site, which has 42 million unique monthly visitors and 21 million social media followers, uses its own Velocity software to aggregate news and reveal trends on social media, Roberts said: “It is a multi-purpose predictive tool and it helps us find good stories.”

Roberts added that Velocity also promotes cooperation between Mashable’s data experts and its editorial team, which work together to understand audience behaviour. 

Velocity allows Mashable to maintain an automated home page. An algorithm places stories on the home page according to the number of shares they have received on social media. 

It is essential to understand how the Web site’s content is shared, he said: “We are constantly asking ourselves what data science can tell us about audience behaviours.”

“People are looking for different things at different times of day. It’s very likely that someone at 11 p.m. is looking for a bit more entertainment. So we wonder if we are differentiating our content enough. We are starting to think what types of stories we should be sharing at different times of day. This is where data is essential to us.”

Mashable also uses other data tools, such as Geofeedia and Dataminr, to help find and break stories before  the competition.