Saving local news by building an audience-supported business model: Findings from clickstream and subscription data

Local newspapers play a crucial role in helping citizens be informed of local issues and foster a sense of belonging, but the U.S. society has witnessed the expansion of news deserts in many local communities. With the decline of advertising revenue, local newspapers must shift their focus to revenue sources other than advertising such as subscription fees. One of the ways in which news publishers can find ways to build or expand their audience base is through the analysis of their subscribers’ reading and payment behaviors. By harnessing large-scale clickstream data on news websites and linking them with subscription records, we can understand audiences’ revealed preferences and needs, which helps news organizations develop strategies to attract new subscribers and retain existing subscribers.

This talk presents two studies that came out of my collaboration with the Local News Initiative, led by the Medill School and Spiegel Research Center at Northwestern University, which aims to help the news industry regain financial sustainability by building an audience-supported business model. The first study proposes an analytical framework that identifies sources of negative experiences on local news sites – namely, commoditized content, advertising interference, and information overload - and investigates how these sources of negative news experiences influence news reading behaviors and subscription cancellations. The second paper examines how creating better news reading experiences with a tablet device and improved user interface contributes to reading habits, subscriber retention, and customer lifetime value. This study focuses on one particular case of the Arkansas Democratic Gazette (ADG), which gave its subscribers free iPad tablets with training and tech support during its transition from print to digital. Put together, these studies demonstrate the importance of building news reading habits and providing experiences that news readers find worth paying for. 

Su Jung Kim (PhD, Northwestern University) is an assistant professor at USC Annenberg. She is interested in how audience behavior takes shape in the digital media environment, especially the formation, patterns, and impacts of audience engagement behaviors. Her research has examined cross-platform media repertoires and information sharing behaviors (e.g., eWOM, online reviews, and news sharing), as well as persuasive effects of audience engagement, for example, technology adoption, purchase decisions, and civic/political participation. Methodologically, she employs the tools of computational social science to trace, collect and analyze individuals’ digital footprints along with other quantitative research methods.