LOS ANGELES — JustFor.fans (JFF) today announced the unveiling of its personalized “Recommendations” page, which suggests new models to members to expand their user experience.
The all-new feature uses AI to detect performers the JFF member already follows and suggests other content creators they might like based on who else subscribes to them, among other factors.
Founder and CEO Dominic Ford explained that the company “focuses a lot on providing internal traffic to our models. Unlike other sites, in which models are responsible for bringing all of their own traffic, our models routinely attribute 30-40% of their sales to our internal traffic.”
“We expect that percentage to go up with the launch of this new feature, which is one more way we introduce users to models they might not know about yet,” said Ford.
The Recommendations system takes many factors into account to assist JFF members, such as how long ago they subscribed to a particular model, and how often that model updates their content.
The list of suggestions returned are models that have been active within the last two weeks on JFF, and exclusive models are shown first.
Before his work in the adult industry, Ford was a software engineer at an AI think-tank in Cambridge, MA. He later went on to lead development teams for personalization software — building and using systems like the one JFF is using — for major retail websites.
“AI software development is my background, so it was only a matter of time until I integrated a system similar to the ones I used to build for the Department of Defense and major retail websites into JFF,” Ford added. “The results have been stunning. The page is already responsible for a large percentage of new sales per day.”
To learn more about the new Recommendations feature, visit JustFor.fans.
For more information, follow JFF on Twitter.