siliconindia | | AUGUST 20229the product recommendation engine generates over 35 percent conversion by creating unique, hyper-personalized experiences for each customer.Amazon Considers Data From: ·Customer demographics·Search query·Average time spent on searches·Past purchase history·Brand affinity·Category browsing habits·Time of past purchases·Average spend amountConsidering Netflix as another example, it is recognized as the first company to deliver a high level of personalization in media entertainment through data science. Netflix leverages data analytics for business victory in two significant ways. The first is its capability to offer a personalized suggestion system to its subscribers to keep them involved. The second is to leverage data to produce their content strategy.Netflix's customer ratings of its film or television programs feed into its recommendation system. However, while explicit user ratings play a vital role in Netflix's recommendation system, Netflix acknowledges that the implicit signal is more robust. Through the analysis of implicit data- such as viewing behavior, Netflix seeks to match viewers with the programming they might like to see depending on the mood or time of day. This means that Netflix can track when users start, stop, rewind, fast forward videos and can also identify the time of day, location and the device on which the streaming occurs.Netflix operates on an algorithm to predict content that users will want to see. It combines behavioral characteristics with predictive learning to send 103 million users unique movies and show recommendations to increase engagement and loyalty. Netflix's recommendation engine has been critical to customer retention as 80 percent of users follow through on a suggestion, and only 20 percent search for content.Netflix considers data from: ·Customer behaviors (including viewing history, ratings, viewing times, preferred device, viewing duration)·Movie information (including titles, genres, categories, actors, release year, and more)·Members with similar tastes and preference
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