Abstract
Audience analytics are an increasingly essential part of the modern newsroom as publishers seek to maximize the reach and commercial potential of their content. On top of a wealth of audience data collected, algorithmic approaches can then be applied with an eye towards predicting and optimizing the performance of content based on historical patterns. This work focuses specifically on content optimization practices surrounding the use of A/B headline testing in newsrooms. Using such approaches, digital newsrooms might audience-test as many as a dozen headlines per article, collecting data that allows an optimization algorithm to converge on the headline that is best with respect to some metric, such as the click-through rate. This article presents the results of an interview study which illuminate the ways in which A/B testing algorithms are changing workflow and headline writing practices, as well as the social dynamics shaping this process and its implementation within US newsrooms.
Highlights
To stay in business, digital publishers depend on capturing the attention of users
The second looks at the social dynamics surrounding headline testing, which play an important role in determining how effective the process can be in a newsroom
The goal of A/B headline testing in all cases was increased traffic to stories. Participants stressed that they wanted to accomplish this goal by improving the quality of headlines, as judged by how well they communicated the contents of the story and adhered to the publication’s style and tone
Summary
Digital publishers depend on capturing the attention of users. While often not as sophisticated, news organizations have started incorporating data and algorithmic systems into their editorial workflows to optimize stories and capture reader attention. Such approaches are used in a variety of ways to optimize attention and traffic, including predicting article shelf-life, selecting and timing postings to social channels, and integrating recommendation and personalization modules to make sites more sticky. With the shift to digital, the task of constructing an audience has become increasingly quantitative, with analytics systems collecting feedback in the form of data (Zamith, 2018)
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