Podcast Recommendation Engines and the Future of Analytics

Featuring Michael Schrage, Author of Recommendation Engines and Research Fellow at the MIT Sloan School of Management

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As AI & machine learning software continues to get smarter, the field of personalized recommendations is only going to continue to grow. 

But just how far will it go? If you think of a nine-inning baseball game, we’re likely somewhere in the third inning, meaning there is still a lot of game left to play. 

So what advancements are coming, and how do we navigate the world of data?

In this episode of Leading With Data, Michael Schrage, Research Fellow at the MIT Sloan School of Management, talks all about the future of recommendation, as well as his new book, Recommendation Engines. 

In addition to his role at MIT, Michael is also a visiting fellow at the Imperial College Business School of Innovation & Leadership, as well as an author of multiple books, including his most recent publication, Recommendation Engines

In this episode, we discuss:

-The motivation behind Michael’s latest book, Recommendation Engines

-The future of data aggregation and why we’re just getting started with advanced recommendation analytics

-The Customer Lifetime Value (CLV), and why that is more important than any sale you can make in the short term

-What causes most businesses to fail when it comes to digital transformation

If you want to hear more, subscribe to Leading with Data on Apple Podcasts, Spotify, or here.

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