Netflix Recommendations: Beyond the 5 stars (Part 2)
by Xavier Amatriain and Justin Basilico (Personalization Science and Engineering) In part one of this blog post, we detailed the different components of Netflix personalization. We also explained how Netflix personalization, and the service as a whole, have changed from the time we announced the Netflix Prize. The $1M Prize delivered a great return on investment for us, not only in algorithmic inn
Netflix Recommendations: Beyond the 5 stars (Part 1)
by Xavier Amatriain and Justin Basilico (Personalization Science and Engineering) In this two-part blog post, we will open the doors of one of the most valued Netflix assets: our recommendation system. In Part 1, we will relate the Netflix Prize to the broader recommendation challenge, outline the external components of our personalized service, and highlight how our task has evolved with the busi
the 12-step landing page rehab program
Earned media is complicated. Google’s algorithm changed 729 times, just in 2022. Our algorithmic-proof strategies not only help align websites with Google best practices, they ensure optimal visibility across other earned media platforms, like Google Play, the App Store, YouTube, Amazon and Pinterest. We’re experts at making complicated things simple. If you’re not in the top 3 spots for the keywo
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Beyond the Tip: Archer Data Visualization
