The New York Times is using machine learning to serve readers a personalized newsletter containing stories they “might have missed.”
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Newsletter editors will sort editorial into three categories. “News you might have missed,” “Best of The Times,” which will contain the week’s most important news, analysis and features, including video, graphics and other media, and “Discover,” with highlights from the features well, with stories from travel, food, health and other lifestyle sections.
For example, a user may regularly read movie stories and reviews written by the Times' Culture reporters. That user's "Your Weekly Edition" would identify and display articles the user has not already read but may be interested in reading.
The Times says “Your Weekly Edition” is “the first of what we hope are many experiments using personalization technology at The Times.”
Last month, The New York Times introduced a pop-up newsletter series with ideas of what to eat, drink, see and do in New York City each weekend, called Summer in the City.
Is this really a step ahead with " machine learning," or another use of standard analytics data to improve the likelihood readers will be drawn and stay with the stories?
Will be interesting in monetizing this percieved level of higher emailed personalization with ads...and the usual engagement metrics...if that works. They they will have a "best of the TIMES" content that spews a nice revenue gusher of highly targeted activity via its readers Now, if they can externally track from NYT site, meaning I view energy news on FT.com..but not NYT..its another way to divert competitor's readers for specfiic coverage..and to try the NYT, e.g. I'll read the times for domestic economics, but not international, that's with The Economist..so how are these new NYT emails going to gradually validate "hey, we at the NYT also have compelling coverage on this energy topic" and with that show "peronalized" energyb content the subscriber hasn't seen YET on the NYT site...but now that subscriber may be motivated.