World Association of Newspapers and News Publishers

How newsrooms can apply big data

World News Publishing Focus

World News Publishing Focus
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How newsrooms can apply big data

For Steffen Damborg, WAN-IFRA Global Advisory consultant and former Digital Director and Chief Development Officer at JP/Politikens Hus in Denmark, the analysis of big and small data allows publishers to improve their business models, maximise audience engagement, personalise user experiences, and drive cultural change within the newsroom.

Don't miss the opportunity to meet Steffen Damborg during WAN-IFRA's Digital Media Asia conference, taking place from October 31 to November 2, where he will teach a masterclass on Paid Content Business Models, and give a presentation on Big Data and AI in newsrooms.

“We have a long history of what is engaging people on the printed platform but you really have to gain insights into what is working in digital,” Damborg said during the WAN-IFRA webinar Big Data in the Newsroom on the 6th of September (click to replay the webinar).

Gaining new insights through the combination of big and small data

Given that replicating the business models of global newsbrands can be difficult for most publishers, Damborg drew from his own experience at JP to highlight how new data insights helped the publisher better understand user behaviour, and improve its approach to its paid content business model.

After JP introduced a paid content offer a few years ago, journalists were given access to real-time usage dashboard, allowing them to monitor engagement time, social media engagement, and traffic sources. Additionally, editors used heat maps to decide where to put advertisements, allocate pixels between paid and free content, and used dashboards for the space management of the newspaper.

“Nowadays, these are all very mature technologies that build on big data. You can buy them from a lot of vendors, and they’re easy to implement,” Damborg said.

Despite the introduction of these new tools, however, JP’s conversion rates still lagged behind those of peers in other markets.

“So we tried to look deeper into how our users and visitors were consuming our content,” Damborg said.

To do that, they introduced a peer learning approach in the newsroom, with online specialists educating offline journalists about producing content for online, and prioritising content on the homepage as opposed to a printed publication.

Additionally, JP put together user focus groups to discuss topics such as willingness to pay for content, what constituted premium content in their eyes, and tasked them with navigating the website while tracking their eye and mouse movements.

“We gained lots of insights into user experience and user interface of the website, and where people were bouncing,” Damborg said.

“With all of this information, we built a new model where we looked at the product and customer satisfaction, and how we could increase loyalty and reduce churn on the digital platforms. It’s a more customer-centric approach to news production than what you traditionally see in the newspaper industry.”

Using predictive modelling to improve curation

He also pointed to the EngageReaders project from Belgium, a collaborative effort between Mediahuis, Twipe, the University of Leuven, and the Google Digital News Initiative, which aimed to identify a new approach to engagement based on scientific research.

“Their theory was that it’s not just the time span, the number of pageviews per session, and the number of minutes spent per session that equal engagement, but that you also have to look at where the people have a positive affect towards the content you’re producing and presenting to them,” Damborg said.

“Engagement affects loyalty. The higher the engagement the higher the probability that you will see people return to your website or your e-paper. And we know that high-frequency visitors are the ones with the highest propensity to become a paying customer.”

As part of the project, the team behind EngageReaders put together a panel of 60 people, measuring and tracking their pulse, skin conductance, body temperature, and eye movements while they were reading through the tablet versions of Belgian dailies De Standaard and Het Nieuwsblad. Additionally, the participants  were asked to provide direct feedback on the content of the e-papers.

Using the collected data, they team built a predictive model, which allowed them to see the Net Promoter Score of tomorrow’s edition of the newspaper, as well as gather information on reading time and engagement.

“This gives the editorial newsroom insights on how to curate tomorrow’s newspaper, how to curate the e-paper, and actually allows you to predict pretty accurately how much time people will spend consuming tomorrow’s product,” Damborg said.

Creating a more personalised user experience

The use of data, algorithms, and machine-learning processes can also help newsrooms create more personalised user experiences, as Damborg demonstrated with examples from the Washington Post and Swedish publisher Svenska Dagbladet.

After Jeff Bezos acquired the Washington Post, the media outlet built a new tool, called Clavis, based on Amazon’s predictive e-commerce recommendation engine to power the “Post Recommends” section at the bottom of article pages. As a result, click through rates went from 3 percent to 18 percent within a period of just two years.

Similarly, Svenska Dagbladet implemented Schibsted’s “Creation Suite” CMS to edit the frontpage of the website using a machine-learning algorithm, which ended up outperforming human editors. SvD also started sending out computer-curated newsletters, based on the individual user’s previous interaction history, which consistently achieved higher opening rates than manually curated newsletters.


Simone Flueckiger's picture

Simone Flueckiger


2017-09-08 13:33

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