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Optimizing Content with A/B Headline Testing: Changing Newsroom Practices
[journal article]
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... view more
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.... view less
Keywords
digital media; news; content; optimization; editorial department; readership; coverage
Classification
Interactive, electronic Media
Communicator Research, Journalism
Free Keywords
audience metrics; content optimization; digital media; headline testing; headlines
Document language
English
Publication Year
2019
Page/Pages
p. 117-127
Journal
Media and Communication, 7 (2019) 1
Issue topic
Emerging Technologies in Journalism and Media: International Perspectives on Their Nature and Impact
ISSN
2183-2439
Status
Published Version; peer reviewed