During the 46th annual UBS Global Media and Communications Conference in New York, Meredith Kopit Levien, chief operating officer at The Times, said the publication will aggressively invest in hiring people with backgrounds in artificial intelligence, machine learning, data science and mobile engineering to create personalized feeds for readers so they keep coming back.
The Times has been a poster child in getting people to pay for its content and has historically achieved that by keeping strategy simple: Take strong stories not found elsewhere and parlay them to capture paying users.
It's already topped $1 billion from paying subscribers, and earlier this month, said it captured some $258 million from subscriptions in the third quarter, up 4.5 percent year-over-year.
But not all paying subscribers stick around, and many bounce once introductory offers — such as paying $1 a week for access — expire, Levien said. "The high-octane gas that powers our display and subscription business is engagement," Levien said on stage during a UBS panel Monday. "And the easiest way to describe engagement is getting people to make a daily habit of the New York Times and if we get that right, we lift both businesses over time."
The Times puts out some 200 stories each day, but adds that even its most active users only read a handful of them. The publication believes that it can increase its odds in converting people to pay full-price by personalizing what stories they see. Back in June, the company debuted "Your Feed" within its iOS app; the feature allows people to follow developing stories, specific writers and topics.
"That is a way to get an enormous amount of active and passive signals from people that we can then use to show them things that are more interesting to them," Levien said. "Right now, we are intently focused on hiring mobile engineers, machine learnings specialist and data scientists to improve our ability to do that. You will see us deploy that [personalized data feeds] much more across our destinations."
When asked about machine learning and artificial intelligence, Levien said: "We have an enormous amount of value that we already produce. The challenge is how do we get that value in front of people based on the signal we have, based on what interests them? You will see us get more aggressive about that in the coming years."