To stay ahead of the competition, companies invest a considerable amount in data. Companies hire data science experts and data analysts to analyze the wide expense of available data. Netflix is the greatest example of the effective use of data, that has taken the place of the largest media company Disney. Netflix uses predictive algorithms and deep analysis to help implement the best experience for their users.
A 10% increase in data accessibility will result in more than $65 million additional net income for the typical Fortune 1000 company. By 2020, there will be more than 50 billion smart connected devices in the world, collecting, analyzing and sharing data. (source)
Ways to Optimize the Netflix Streaming Experience with Data Science
Here we will discuss some emerging ways to optimize the Netflix clone script streaming experience with data science. Let us have a look at them.
Optimizing Content Caching
Optimizing content caching on all appliances that are based on the viewing behavior of the users is one of the most exciting problems. With millions of users, with limited storage capacity and a large catalog, it is difficult to be cached to ensure that when a user plays a particular series, documentary or movie. The problem is solved by Netflix’s own content delivery network named as Open Connect. Netflix stores its content on internet service provider (ISP) locations.
Personalized Streaming Experience
Personalization can also be based on a user’s device, network characteristics, and location, etc. To keep a track record of the algorithm that once the playback has started which works in real-time and near real-time. That algorithm determines what server to download that content from and what bitrate should be served etc. network A user could have very different expectations and experiences with a very high-bandwidth connection on a home compared to a user with low bandwidth on a mobile device on a cellular network.
Improving Content Quality
Another interpretation of improving user experience is by having a look at the content like video, audio, closed captions, subtitles, etc in a movie or show. Before Netflix publishes the content live for users, Netflix receives the content in the form of digital assets further these digital assets encoded and quality checked. In addition to the quality check, Netflix clone also provides an option of giving feedback to their users if there is any issue while watching the content.
Recommendation Algorithm
Netflix asks its members to rate their curiosity or interest in any movie they have seen and in movie genres. By helping users to find their choice of content helps Netflix to reach towards its success. Netflix makes sure it with help an algorithm because if the audience will run out the choice of content they will move on to other video streaming development companies. This recommendation algorithm works pretty well for the users of Netflix.
Predictive Quality Control
Data science can help to identify the defective assets. Data and data science play a significant role in Netflix’s working. The key role of a predictive quality control model is to identify all the defective results. Like most model-building exercises, domain knowledge played an important role in this project.
Testing Regularly
Demographics have a way of changing constantly that is why data-driven models should be constantly checked. To achieve maximum optimization, the algorithms that Netflix uses are constantly updated in order. Data science execution should be performed carefully. Netflix has shown us that ML can be used to convert the user’s desires into the company’s business goal. Data can predict whether experimental projects or particular innovations can take off.
Identifying Available Data
With a large number of subscribers, a tremendous amount of data comes that Netflix can use. Before starting the subscription, a user needs to give information to Netflix about their interest in any particular genre. When they watch a movie then Netflix asks them to rate the movie. These pieces of information are used to discover new shows and movies of their choice. Netflix understands its user’s preferences and choices with the help of the vast data collected from these events.
Conclusion
Now it is easy to understand how Netflix makes decisions based upon data. Data science and analytics gives one a better insight so that one can run a business effectively and can offer a superior product. People have the advantage who work with data over to those who work on instinct. Those who wish to enter or want to make a career in data science or in the online world, there are many ways that can enhance your business and keep you alive in the market.
