Condé Nast is enhancing the reader experience through recommendation models – SiliconANGLE

Condé Nast is host to 60 publications, including many beloved and long-running magazines, such as The New Yorker, GQ and Vogue. But its readers may be less familiar with the data infrastructure fueling the media empire.

Building on its relationship with Databricks Inc., Condé Nast is increasingly looking toward implementing artificial intelligence with recommendation models in an effort to engage readers who may not be interested in print offerings.

“What I get really excited about is thinking about how well these models have to understand content to make these predictions, and that’s generally what I like to exploit,” said Tim Shokair (pictured), senior director of data science at Condé Nast. “What I think is going to really last the test of time is good ways to represent content so that we can start to create real personalization or real models that can engage people. Because when we’re sitting here in this attention economy, everybody’s time is so precious and we’re all fighting for the same minutes.”

Shokair spoke with theCUBE’s Savannah Peterson at the Data + AI Summit, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed how data engineers can target user interests and how Condé Nast is integrating AI into its offerings. (* Disclosure below.)

Recommendation models that enhance the reading experience

Condé Nast’s data engineering team stores data about their users and content through Databricks and then employs it for model development. Use cases include analyzing readers’ propensity to subscribe, segmentation for advertising and building a tool that allows users to search 1.2 million runway images in the Vogue Runway app.

“There’s data on our users and data on our content. From that, we can build everything else,” Shokair said. “So, if we have a good way to understand our content and we have a good way to understand how our users interact with that content, then we can start to build more models that draw more engagement, that can get as much value as we can out of our properties and our time with our customers.”

Another application for AI that excites Shokair is narrated audio. Since fewer users are reading articles nowadays, AI-generated audio could allow them to, for example, listen to stories on their way to work and make the content more accessible.

“We are thinking a lot more about how we can leverage all this technology to enhance our offerings and make our content more accessible and easier to discover for our customers,” Shokair said. “For me, I want to keep pushing forward on bettering our content understanding, expanding beyond text to audio and video and starting to really come up with good recommendation models.”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE Research’s coverage of the Data + AI Summit:

(* Disclosure: Databricks Inc. sponsored this segment of theCUBE. Neither Databricks nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE