![]() ![]() Implicit data contains search, order, and click history and explicit data contains comments, likes, engagement. Recommendation engines are built on data, the more data it contains, the better the engine will be at generating the correct recommendation.ĭata for the recommendation engine is collective in two ways: implicit and explicit. Used correctly, recommendation engines can deliver a more personalized customer experience, boosting engagement with products. Recommendation engines are data filtering tools built on finding patterns to recommend the most relevant items to a user. This newfound data allowed Netflix to utilize machine learning (ML) to offer a hyper-personalized experience for all users. ![]() Not only was Netflix able to offer consumers easy-to-access and affordable content, they generated billions of data in the process. Netflix has radically evolved TV and film engagement through their streaming platform. We explore how Netflix uses machine learning to customize each subscriber’s homepages to display the most relevant content. ![]()
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