During the 46th Annual UBS Global Media and Communications Conference in New York, Meredith Kopit Levien, the EVP and Chief Operating Officer at The New York Times, said that the publication will begin to invest in artificial intelligence, machine learning, data science and mobile engineering. Through this, the publication aims to create a personalized feed for readers to ensure that they keep coming back.
The New York Times has already crossed the $1 billion mark through paid subscriptions, and earlier this month also announced that it made close to $258 million from subscriptions in the third quarter, up 4.5% year-over-year. The publication has achieved this by keeping its strategy simple: “Take strong stories not found elsewhere and parlay them to capture paying users.”
“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.”
“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.”