How IEEE Spectrum is Using Analytics to Transition to Daily Digital Content

Shifting from monthly issues to daily digital news at a legacy publishing company requires significant organizational changes. Not least of those changes is the editorial team’s relationship with data. At IEEE Spectrum, the 51-year-old flagship magazine of the Institute of Electrical and Electronics Engineers, editors are learning to embrace data in two ways, explained editorial director Harry Goldstein during the November Publishing Executive webinar, “How Publishers are Using Content Analytics to Drive Strategy.”

First, Goldstein is educating the editorial team on how to target topics for editorial development by analyzing search trends and engagement data. Second, Goldstein is using data to drive cultural change as IEEE Spectrum evolves into a daily, digital news site. “We’re transitioning from looking at letters to the editors and bi-annual reader feedback to viewing data,” said Goldstein.

During the webinar, Goldstein explained that IEEE Spectrum utilizes long-term and short-term reader data. Goldstein primarily turns to Google Analytics to gather long-term data and track trends. In particular he and his team collect search term data to see what topics were most searched by IEEE Spectrum readers. For example, in 2014, 14 of the top 100 search terms were related to top programming languages, said Goldstein. “This traffic was going to a 2011 infographic we did on programming languages, so we decided to create a new piece of editorial around that,” explained Goldstein. This led to IEEE Spectrum’s Top Programming Language app. The goal of this app, which ranks programming languages by use in different platforms annually, was to engage loyal IEEE Spectrum readers and attract new visitors. Since July 2015, the app has garnered 90,000 search referrals, 60,000 social referrals, and 21,000 social shares.

The second way IEEE Spectrum looks at data is through real-time data provided by Parse.ly. This allows editors to quickly react to popular stories, boosting them through additional social media posts or creating follow-up pieces. IEEE Spectrum is also using this quick data feedback loop to test the effectiveness of their messaging. “Old school print editors make assumptions based on their own preferences and make editorial decisions on subjective judgments,” said Goldstein. “We want to use Parse.ly and Google Analytics to put some data behind their decision making.”

Goldstein added that the transition to a data-led content strategy is ongoing and requires a cultural shift on the part of the editors and organization. “Many fear the ‘tyranny of the click,’ that the popularity of topics may trump journalistic worthiness.” Goldstein is trying to combat this thinking by training editorial staff regularly to use these tools and making the data more visible to everyone on the team. Since adopting a data-driven content strategy, IEEE has added public displays of analytics at the office and Goldstein takes an hour out of every week to personally train an editor and field his or her questions.

To learn more about IEEE’s transition towards data-driven content, watch the complete webinar, on-demand here.