Audience engagement data: How Parse.ly is ‘Real time anthropology’

In the pre-internet era, when a reporter turned in an article, their responsibilities for that content would be finished.

They would not have to worry about if people were reading it, and the only time they would hear from angry readers was if they were upset enough to go through the trouble of calling — or writing — to them.

But with articles posted online, and shared on social media, journalists now have to think about audience response. That’s why Parse.ly was created; to help newsrooms collect better data about interaction with their content.

What is Parse.ly?

Parse.ly is an audience data platform. The service allows media companies, such as The Wall Street Journal and The Huffington Post, to see what their audience is doing on their site. This includes what articles audiences are reading, how long they are reading them, and where they are going on the site next.

A tweet from WSJ News Editor Henry Williams shows the newsroom using Parse.ly to track analytics on Election Night.

What makes Parse.ly unique from other similar services, is that they collect a significant amount of data which is delivered to journalists in a simple, easy to use, platform. This allows newsrooms to gain a better understanding of their audience to help them know how to get people to read their content.

A Reuters Institute for the Study of Journalism report explains how media companies are using analytics to get their content read, make strategic content decisions, and stay relevant even when the way that media is consumed is constantly changing.

The Parse.ly dashboard from www.parse.ly.com

What the Data is Saying

Parse.ly Customer Success Manager Kelsey Arendt calls the data that Parse.ly collects, “real time anthropology.”

The data, Arendt told us, is the audience speaking to the newsroom, and journalists need to listen to what the data is saying.

Parse.ly explains on their website the types of interactive data they collect, such as: when someone visits your website, when they read your content, when they use your mobile app, when they view your advertisement, when they sign up for your newsletter, and when they buy a product on your website.

There are different ways to determine audience engagement.

According to Arendt, many analytics services often face a problem of not being able to determine when a user becomes inactive (they have the article open but are not actually reading it). Parse.ly can work around this by determining when a page loses engagement, based on user activity. This allows companies to have a better sense of how long people are staying on their website.

From Clicks to Engagement

Arendt says the future of online journalism is steering away from “clicks” and moving toward audience engagement. While clicks are still a tangible way to see the popularity of an article, it is not the most effective way to see how an article is doing, because there are many other important factors.

Focusing on clicks is what leads to clickbait, which can cause negligent journalism. In a The Washington Post article from 2016, reporter Terrence McCoy even called clickbait the new “yellow journalism.”

Arendt also points out that this is not a fair way of looking at articles. A daily sports article is quicker to produce and will get more clicks per day than a long, investigative piece that takes months to report and write. Both are important, but one has the advantage in a click-incentive system.

However, headlines that draw attention to an article can increase engagement.

In a BBC article, Peter Preston former editor of the Guardian and a columnist for the Observer says there needs to be a balance between drawing in an audience and click-bate headlines: “It’s a means of getting journalists to concentrate on [ensuring] whatever story they are doing is presented in the best way.”

Many newsrooms are moving away from the era of clicks and are focusing on engagement of specific audiences. In doing this, they are looking for new forms of data to validate and inform their work; and many of them are using Parse.ly to help them do it.

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