$ 1 billion annually since the year 2016). Moreover, the platform is constantly focused on enhancing the user experience to improve the retention rate, which will translate into savings in acquiring new customers (approx. Netflix estimates it gets around 80% of total watch time thanks to its recommendation system, which is an impressive result.

Generated recommendations are arranged in several rows sorted by their categories and user preferences. In 2006, Netflix organized the 'Netflix Prize' - a competition to select the best data filtering algorithm with a top prize of $ 1 million.Ĭurrently, Netflix uses an advanced system of personalized recommendations based on 4 complex algorithms that take into account both descriptions and target age ranges of movies, as well as ratings and popularity among users. The platform implemented the original version of its recommendation system in the year 2000. Netflix is a trendsetter of modern recommendation models. In this article, we look at the machine learning-based recommendation systems of the largest online services and streaming platforms, and we consider whether the solutions they use can be used in online stores. AI-based solutions are able to improve the user experience with a given website, and for its owners it is associated with increased engagement, better CTR ratios or higher sales. The largest websites operating in various industries use them to gain a strategic advantage over the competition and fight to maintain their position on the market. Artificial intelligence (AI) and machine learning are buzzwords that are increasingly appearing through online articles.

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