Solving journalism’s hidden problem: Terrible analytics

Tom Rosenstiel for the Brookings Center for Effective Public Management: “The path toward sustainable journalism, already challenged by a disrupted advertising business model, is also being undermined by something more unexpected—terrible data.

Analytics—another word for audience data or metrics—was supposed to offer the promise that journalists would be able to understand consumers at a deeper level. Journalism would be more connected and relevant as news people could see what audiences really wanted. Handled well, this should have helped journalists pursue what is at its core their fundamental challenge: learning how to make the significant interesting and the interesting more significant.

But a generation into the digital age, the problem associated with analytics isn’t the one that some feared—the discovery that audiences only care to be entertained and distracted. The bigger problem is that most web analytics are a mess. Designed for other purposes, the metrics used to understand publishing today offer too little information that is useful to journalists or to publishers on the business side. They mostly measure the wrong things. They also to a large extent measure things that are false or illusory.

As an example, the metric we have taken to call “unique visitors” is not what it sounds. Unique visitors are not different people. Instead, this metric measures devices; the same person who visits a publication on a phone, a tablet, and a computer is counted as three unique visitors. If they clean their cookies they are counted all over again. The traffic to most websites is probably over counted by more than double, perhaps more than triple

Time spent per article, in contrast, might offer a sense of depth of interest in a particular piece. But by itself it might also mean that someone stopped reading and walked away from the computer. Page views can tell a publisher how many times an individual piece of content was viewed. But views cannot tell the publisher why. Using conventional analytics, every story is an anecdote. Publishers may look at popular stories and say let’s do more like those. But they are largely inferring what “like those” means….(More)”