In developing a recommendation system, netflix is also not alone, you know. Because they had held a competition from 2006 to 2009. This competition challenged the participants to create an algorithm that could accurately predict film ratings. Long story short, the bellkor team won this competition, and they won a prize of 1 million usd. Netflix immediately uses the algorithm created by the bellkor team into its recommendation system. The bellkor team won the netflix competition in the netflix case study is netflix satisfied? Of course not. They are still trying to improve the accuracy of their recommendation system. You do this by adding the variables considered in the algorithm . So, what are the factors that netflix considers to determine film recommendations? Here are some of them: movies or shows you’ve watched when did you watch the film where you are watching the device used for viewing how long did you watch the film how often do you pause the movie what movies have you watched to the end what are some scenes that you often repeat? Keywords that you often type in when searching for shows that’s a lot, right?
Netflix at a glance
You can imagine how much data netflix has to process to provide super accurate recommendations. Anyway, what made netflix so passionate about building a recommendation system? What benefits does netflix get from this feature? Also read: what is data mining? The following is the definition and examples of practice! What benefits does netflix get from big data? Even though it looks simple, the recommendation system is actually one of the main factors that helps netflix retain its users. Based on Australia B2B Leads research conducted by netflix, 75% of its users rely on the recommendation feature to find shows they like. The reason is simple. Users don’t need to bother digging for movies through the search feature. Just by looking at the recommendations section, they can find films that suit their tastes. The result?
How Does Netflix Leverage Big Data?
The number of surviving consumers is increasing . Based on netflix’s data, this achievement was achieved because 80% of its users followed the recommendations provided by netflix and watched it to the end. Thanks to netflix’s persistent efforts to increase user convenience, they have now succeeded in becoming a media company that has the highest value (valuation) in the world . In addition, of course, this achievement cannot be separated from their ingenuity in exploiting the potential of data. Also read: big data and its role in shaping linkedin now what lessons can be taken from the netflix case study? Okay, now you know how netflix reaches hundreds of millions of users who feel comfortable staying on its platform? In essence, netflix uses big data to create an accurate movie recommendation system. They do it in various Mobile Lead ways, from holding algorithm competitions, to considering many variables to present the right recommendations. Well, the netflix case study is one of many cases out there that illustrate how useful data science is for business development.
