Home Publishers Sports Publisher On3 Tries AI Recommendations To Keep Engagement In Its Home Court

Sports Publisher On3 Tries AI Recommendations To Keep Engagement In Its Home Court

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Publishers are getting real about the declines in traffic from search and social media. Some pubs are maximizing revenue per session (RPS) to get the most out of the traffic that still comes to their properties.

On3, a site that tracks high school and college sports, as well as operating a network of 70+ fan pages for specific teams and communities, has long been committed to the RPS model, said CRO Brandon O’Neal. On3’s RPS strategy seeks to replicate the walled garden playbook by keeping the attention of its 15 million unique monthly visitors focused on its properties, he said.

“We’re always looking for ways to drive users to stay,” O’Neal said. “And social media has done such a good job with that ‘scarcity brain’ mentality, where, like it or not, there’s always another thing to scroll to.”

With that playbook in mind, in Q3 of last year On3’s sites integrated a content recommendation feed operated by Mula, an agentic publisher monetization platform. The content recommendation feature has helped On3 keep its engagement and RPS consistent amid traffic drop-offs to publisher sites and the growing scarcity of online attention, O’Neal said.

Engagement and ecommerce

On3’s content recommendation uses AI and the publisher’s first-party data to determine which types of stories or teams a user is interested in, then surfaces recommendations for more content across the network. These recommendations can be served either on On3’s web properties themselves or within email blasts sent to On3’s list of 3 million readers.

So far, On3 has added Mula’s tech to about 20 of its sites, and it’s considering bringing the experience to its mobile app and fan forums, O’Neal said. Mula’s recommendations run the gamut from text-based articles and fan forum posts, to ecommerce listings and vertical video, the latter of which On3 has been adding to its content mix through a separate partnership with publisher video monetization company EX.CO.

Mula’s tech also uses engagement and RPS data to determine the best place on the page to place recommendation widgets. This model helped On3 take a more data-driven approach to keeping users engaged with its content, in contrast to how it has traditionally experimented with social media-esque infinitely scrolling feeds, said Mula co-founder and CEO Jason White.

Through On3’s partnership with sports memorabilia company Fanatics, Mula’s tech can also show ecommerce listings for team merchandise that readers might want to purchase, with On3 receiving a cut of the revenue. Such recommendations can include everything from T-shirts and jerseys to an autographed mini-Notre Dame football helmet, which one On3 reader recently bought for $2,500, O’Neal said.

And, through Mula’s new partnership with native ad platform RevContent, On3 can also recommend paid listings for other publishers’ content, which adds an additional revenue stream for On3. The idea is that, once Mula’s AI has determined a user isn’t likely to interact with any more of On3’s content, On3 can then collect revenue by sending that user to another publisher.

According to O’Neal, On3 would likely not have been able to partner with RevContent on its own. But On3’s relationship with Mula, combined with Mula’s arrangements with other publishers, brought enough scale to make the RevContent integration feasible.

And, another layer of value that Mula brings to publishers is that they don’t have to manage their own ecommerce or native content businesses, said Richard Marques, CEO at RevContent.

“Commerce can be a high-margin, diversified revenue channel for publishers, but it’s a full-time gig at least,” Marques said. “And this way, Brandon doesn’t need to deal with our account managers or our salespeople [on the native content side].”

Value added

As far as determining what content to show a reader in a given moment, Mula’s platform always keeps RPS as its “god metric,” White said.

For On3, Mula’s RPS optimization tends to prioritize ecommerce listings first, White added. From there, On3 shifts to prioritizing content that will keep users engaged, with vertical video rising to the top, he said, followed by On3’s other content. Then, once Mula’s algorithm determines that readers are nearing the end of their likely engagement window with On3, it might serve them sponsored links to other publishers through the RevContent integration.

If readers click the RevContent-provided link to a different site, On3 collects revenue on a cost-per-click basis.

The addition of the RevContent revenue stream has helped On3 collect more consistent revenue, O’Neal said, whereas its ecommerce revenue is more subject to fluctuations. After all, he joked, it’s not every day that someone buys a $2,500 autographed helmet.

And, unlike overloading pages with ads or floating video players, O’Neal said the Mula integration feels like it actually brings value to sports fans by showing them content they’d enjoy or merchandise from teams they care about.

“The way we look at it” he said, “is if we’re providing value to our users, it’s something worth trying.”

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