Hey there, I wanted to share with you an experiment from one of our startups, Storily. It’s called MinuteRead— its exploring how Estimated Read Time (ERT) can empower readers. For now it only runs on Twitter, but we are looking at ways to extend the experiment to other platforms.
If you visit the MinuteRead Twitter account you’ll notice an ERT hashtag added to each of the tweets. The idea is simple: enable people to choose articles that interest them based on how much time they have available. To that end, we are appending a hashtag with an estimated read time — for instance, #5minread — to tweets for news articles from 40 or so publishers.
“Lost time is never found again.” — Benjamin Franklin
We want to be clear that this experiment is by no means an attempt to devalue the stories being told, but rather to place value on the time people have in their lives. We believe an estimated read time can serve as a signal for readers to know the time needed to digest a story. This way they can self-curate their consumption of news based on the time at hand.
We believe a portion of bounce rates publishers see can be attributed to readers who click through and then realize they don’t have the time needed to consume that piece of content. By providing an ERT, readers are given greater control over their reading experiences, so now not only when and where, but also how much time is needed to invest in reading a particular story.
A few notes about the experiment:
We’re scanning each story and determining an estimated read time. Since we’ve been running this experiment for a few weeks we’ve learned a lot as it comes to the diversity of how media companies code their pages and how various content types impact read time. We are constantly looking at ways to more accurately accommodate the time needed to digest photos and videos into our calculations. Again, these are just estimates.
We need to determine how best to control the volume of the feed. Right now we’re just passing through news articles as soon as a publisher posts them to their website. It’s a pretty rapid pace, so we are committed to finding ways in which we are adding value to the ecosystem, and not simply flooding it with more tweets. We are considering adding category specific accounts (e.g., politics, sports, health, etc.) to help spread out the volume.
We’re auto-tagging the tweets with hashtags and Twitter handles. We’re running a secondary experiment to see how accurately we can auto-tag stories with relevant hashtags and the author’s Twitter handle to increase visibility of the tweets. As with any experiment, some times we get it right and other times we don’t. But it’s pretty interesting to see what we can do with machine learning as it relates to this effort.
Up to this point we’ve just been focused on Twitter, but are exploring ways to expand the experiment of using data, design, and technology to empower readers. So keep an eye out. In the meantime, we would love to hear from you so feel free to tweet us @MinuteRead or leave a comment here with your thoughts.
Thank you to those who inspired us to start this experiment: Mark Armstrong (#LongReads), the team at Medium (Read Time and You), Arienne Holland ( How Estimated Reading Times Increase Engagement With Content), Frank Chimero (This Should Only Take a Minute or Four, Probably), and for Stephen Colbert for mocking the idea.