In what it’s calling the “world’s first smart magazines,” Flipboard has begun using machine learning technology to better customize content for each reader based on reading habits and broader interests from across the mobile web.
Today, Flipboard unveiled its updated mobile app, which pulls from thousands of topics including content from news organizations, influencers and native advertising and other editorial operations. While previous versions would show the same people browsing a section the same content, the update allows Flipboard to provide users with curated stories and ads based on their interests, along with those from people they might follow on the app or on other platforms such as Twitter.
The redesign is the app’s fourth, an update that founder and CEO Mike McCue said he hopes the more personalized platform will help to increase reading and engagement, while also providing additional avenues for advertisers.
The app, which now has more than 100 million monthly active users, has been steadily ramping up its advertising offerings. In August, it introduced programmatic ads based on inventory from Rubicon Project. In December, it debuted swipeable “roundup” ads, which show several products or pieces of sponsored content within the same ad unit—much like the Carousel ads on Instagram and Facebook.
According to FlipBoard CEO Mike McCue, previous version of the mobile app have been a “snacking experience,” where users follow a lot of subjects and publications in a single feed. He said the updated app is meant to help people organize their experience as they follow more areas of interest. Along with the algorithms, he said the company has dozens of editors to provide a more human element of curation.
“A smart magazine is a lot like a smart playlist,” McCue said in an interview. “I don’t want to put every song I like from the eighties, but I like the eighties and maybe three different bands. This is basically kind of the same concept but applied to content.”
For its Smart Magazines, Flipboard has integrated a number of features, including a home screen carousel that lets anyone swipe through many as nine magazines for their smart magazine. The feature is meant to be one of several ways the company is trying to increase personalization within the app, along with custom RSS feeds, a “passion picker” to search through topics of interest and a redesigned profile.
Flipboard is also adding social actions, such as a way to “heart” a story—similar to how other platforms allow for likes—to signal to their followers that a story might be worth reading. Users can also add stories to their magazine from other sources within the app for later viewing.
One of the first brands to use the updated advertising tools is eBay, which has been marketing within the app since late 2015. While the online retail giant spent the first year building brand equity through interest- and influencer-driven content, it’s now hoping to drive more actual customers based on the types of products they might be interested in. To do this, eBay is integrating its APIs with the app for native ad units.
For starters, it’s promoting items that are for sale in various categories, which are then targeted to users based on Flipboard’s interest graph. (One example: If someone is reading tech stories, they might be targeted with real-time ads based on eBay’s electronics inventory.) According to Llibert Argerich, eBay’s global director of social and content, the goal is less about getting eBay users to buy more through the app and more about acquiring new customers.
According to Argerich, mobile now accounts for more than 59 percent of eBay’s overall traffic. It’s also increasing in terms of actual sales, making up around $10.7 billion of the $22 billion in revenue the company reported last year. He said social has continued to grow “massively” over the past three years, and now accounts for more than 10 percent of marketing traffic generated through paid and affiliated initiatives.
“Our aim is to really understand what’s going on on Flipboard,” Argerich told Adweek. “What a given individual is doing on Flipboard, what kind of content they’re consuming, and then presenting them with very relevant targeted products based on the content and contextually relevant targeting. It’s based on the behavior they have on Flipboard rather than the behavior they have on eBay.”