Archive for February, 2014

Today, Upworthy introduced a metric they’re using on their content, which they’re calling Attention Minutes. As we’ve done with our friends at Medium and the good folks at YouTube when they’ve introduced ways to understand how their audience is engaging with content beyond clicks and pageviews, we’re extending a giant virtual high five.

It’s another big win for people, like us, who care about making sure awesome, quality content is the backbone of the media industry.  We’ve all been pushing in this direction for a few years now, and the flywheel is starting to spin faster and faster—Upworthy’s announcement is further proof of that.

You guys know us, and know we’ve spent just about every day of our company’s history working with thousands of publishers across the globe to solve the problems of where the click and pageview leave off and how we can actually quantify what and how people read. We introduced one of our key metrics, Engaged Time, a couple of years back, and it’s quickly become how lots of folks measure the quality of their content across the web. It tells them not just if people are clicking, but also if they’re actually reading—there’s a big difference.


How Do We Measure Engaged Time?

We silently ping every single visitor’s browser every few seconds to check what they’re doing. First, we look to see if a browser tab is active or inactive—are they there or grabbing a cup of coffee in the kitchen?—and then we look for a few key triggers, such as moving or clicking a mouse, typing on a keyboard, or watching an on-page video. It’s pretty different from traditional time on page, which estimates how long users keep pages open, rather than how long they actually engage with pages.

Why Is Measuring Time So Incredibly Seriously Must-Do-It Important?

Well, not only does it go beyond surface clicks and page loads to tell you what happens between those clicks, but we’ve done a lot research that says it’s a huge indicator of the core goals most every publisher has: Building a loyal audience and monetizing that audience. Our data team found that users’ Engaged Time is strongly correlated with their loyalty to your site. Below is a figure showing the relationship between the maximum amount of time visitors spent reading articles one day and whether they returned to the site across the rest of the week.


Visitors who read an article for three minutes returned twice as often as those who read for one minute. If you get them to read your stuff, like your stuff, and come back again to read more of the stuff they like, you’ve done your job. Why? Because that’s the kind of content and audience insights your marketing team can use to target the right audience with paywall upgrades or newsletter signups. And most importantly, it’s information your ad sales teams can take to your brand advertising partners and sell. They can use this information to prove that your best content is read by your best audience and should be sold at a premium.

It proves your content is worth more than the headline that someone clicked on it. It’s worth the value of someone actually reading that. Because when they read more, as this study on brand recall below shows, they’re more apt to recall the brand that advertises next to that content they just consumed. That’s pretty damn valuable, we’re told.

Correlation between brand recall and engaged time

But don’t just take our word for it. Exposure time as it correlates with recall has been supported by the work of the biggest advertising companies out there from Microsoft to Yahoo and Google, as shown in their research here:

Yahoo Recognition & Recall


Google CTR Ads Views


So let’s go! Let’s all—tech and analytics nerds, editors, ad sales teams, agency planners, brand advertisers—keep this momentum going. Let’s stop letting the metrics of what we could measure in the past get in the way of what matters to our audience.

Current estimates are that nearly 100 million viewers tuned in to watch Seattle’s 43-8 win against Denver last night. Of course, there’ll be many reports that dissect the ways we watched the game, but for us, one particular area of interest is the prevalence of multi-device viewing. The concept of the “second screen”—people consuming media on multiple devices simultaneously—gets a lot of discussion these days, and sports sites are perhaps the best study in second screens. Sports fans still consume the vast majority of games on TVs but, while watching, they might also scan stats, highlights, and commentary on their phones, tablets, and computers.

That’s why I found myself flipping back and forth last night between a livestream of the game, my Chartbeat Publishing Dashboard, and an Emacs window, trying to figure out how online traffic varied throughout the night. Whereas on a typical night it’s hard to collate real-world events with online behavior, last night’s game was different. Whether you were watching online or on television, the commercials and game events happened at the exact same moment, which gave us the opportunity to watch second-by-second shifts in web traffic.

One of the most interesting observations was how much online traffic fluctuated before and after commercial breaks. Across sports sites, we saw upticks of 5% to 15% in traffic just as the game went to a commercial break, and that traffic drained off just as quickly when the game resumed play. That trend was present across every commercial break during the game. Perhaps unsurprisingly, the vast majority of those upticks were on mobile devices.

After watching that trend for the first half, I expected a similar increase in traffic during halftime. But, interestingly, halftime elicited exactly the opposite response; sports traffic dropped by 15% to 50% during the break, and the majority of that drop was on mobile.

Because it’s so difficult to know for certain that the same person is using multiple devices, most analyses of second-screen behavior have measured device usage via surveys. In this case, though, because we saw behavior that was so tightly coupled to events taking place on TV screens, we can start to get a sense of the scale of multi-device usage across the web. And, with patterns in usage as strong as we saw, it’s clear that a large portion of people tuning in were actively engaged on second screens in response to game events.