Web Analytics

This entry focuses on web analytics and how it is used in journalism. It begins with a discussion of what web analytics is. It then describes the extent to which newsrooms across the world are using web analytics and what they are using it for. It discusses factors that influence the use of web analytics as well as criticism of its use. The entry also provides insights into the implications using web analytics has on journalistic practices as well as traditional journalism norms.

Web analytics by definition work as the collection of measurements, analyses, and the reporting of data from the internet in order to understand and optimize web usage. Since the first web analytics companies were founded in the mid-1990s, web analytics have been widely used in marketing communications as part of strategies to boost sales through a stronger understanding of audience behaviors toward online advertising and marketing content.

As news began to move online in the latter half of the 1990s and in the context of dwindling resources, rising audience fragmentation as well as increasingly competitive markets, news organizations have gradually embraced web analytics, in an attempt to retain audience attention. Popular ways to track audience data to news sites include the use of free programs such as Google Analytics that are preferred by smaller news organizations with a limited budget. Larger news sites, despite some initial hesitance, have jumped on the bandwagon by turning to more sophisticated web analytics services such as Omniture, Chartbeat, and Stela, hoping to get the best insights about readers. Those insights to a news site can include numbers of hits, views, unique visitors, the geographical locations where users access the page from, what time they visit, how many comments there are on a story, how many times it is shared via email or social media, most used search terms, and amounts of time each user spends on a news item, among others.

Newsrooms’ desire to learn about the audience is not new. In the traditional media environment, information on audience interests was pulled from several types of sources including market research, ratings, telephone calls, letters to editors, or simply from casual conversations with people at informal or formal gatherings. Even with these different ways of getting audience feedback, such information was provided sporadically, hence it did not help news producers and editors very much in adjusting their daily editorial decision making. In many cases, audience information only reached newsroom managers and not individual newsroom members. News, therefore, continued to be identified, produced, and published using a top-down, centralized approach, with stories being put together based on the assumption that whatever journalists find interesting will also be interesting to the audience. Research (e.g., Wendelin, Engelmann, & Neubarth, 2017) has demonstrated that journalists’ news selection did not align well with audience interests and journalists were often accused of being aloof from their audiences. The Internet and digital technologies have offered news organizations unprecedented mechanisms to learn about the audience. [Page 1755]Nowadays, new digital tools can track every click and scroll and turn them into data to provide newsroom members in real time with myriad types of information on audience insights. At The New York Times, for example, the news analytics team has worked closely with the newsroom to use these insights in strategic content planning since 2013. The aim is for journalists at The Times to gain a better understanding of audiences in order to align their editorial decision making toward them. The team has helped newsroom members with tasks ranging from identifying potential readers and their interests and reading habits to planning for how a story should be covered in order to make it relevant to target groups.

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