Introduction
Netflix is a subscription streaming service that originated in America, in Scotts Valley, California, U.S., on August 29, 1997. Netflix had over 221.8 million subscribers worldwide in December 2021. In February 2022, it was recorded that Netflix was the top second media company. Netflix collects an immense number of records from a huge range of customer bases. It collects data based on what the user watches. This research shows how Netflix manages data analytics and its methods of analysis.
Data Analytics
In 2006 Netflix was one of the first users of data analytics. To improve the existing recommendation system, Netflix came up with the challenge that would award $1 million to an individual who could enhance the existing system called Cinematch. Cinematch was a tool used in the early 2000s. In this challenge, participants were to develop an existing algorithm based on the older data, which predicts the movie preference of their subscribers. BellKor’s Pragmatic Chaos team which includes people from different streams, industries, and various institutes was the winner in 2008. Data science and big data analytics are strategies used by Netflix for its recommendation system. Data including the user’s location, watch history, interests, examined data, and viewing duration are gathered by the recommendation system. This allows customized recommendations based on what the subscribers like.
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Recommendation system
A combination of content and a collaborative recommendation system is known as a hybrid recommendation. In this, the recommendation is made by blending the searching activities of the subscriber with the earlier history of recommendation and the viewing habit of the subscriber. This is a simple technique among all types. For example, the series is sweet and sour. The cover for the scene would change to a romantic scene for people who have an interest in romance. Whereas people who are interested in comedy would get a cover of the people laughing. So people who have an interest in, for example, K-dramas, would get more of those kinds of recommendations than other movies and series types and genres.
Based on the user’s first choice, various recommendations will be given to them by Netflix, from this, the first and last choice of the subscribers the system will combine the different scores to increase its accuracy. In this approach, the input and output of the recommendation system work opposite here.
SWOT and PESTLE analysis
Netflix uses SWOT analysis to identify internal and external factors. Swot analysis helps to develop four strategies for the organization. Strengths established brand name, product innovation, trustworthy supply network, and successful market strategies. Weaknesses like huge debt, more investment in newer technologies, and limited copyrights also occur. It does have opportunities to expand into the new country including China, and partnerships in Europe. Threats of increased competition, liability laws in different countries, and changes in subscriber behaviors arise.
Netflix utilizes PESTLE analysis to identify the macro-environment of an organization. A political issue like censorship takes place because different country has different laws, and many contents may not be appropriate for many countries. The economic exchange rate impacts the profits of Netflix and the cost per employee. Netflix is known for charity work which is called Socio-cultural. Technological advancement is increasing day by day and improving content to 4k with less data consumption. Netflix must work legally so customer protection law is necessary. Netflix needs to work out more towards the use of ecological products. Based on SWOT and PESTLE analysis it is recommended that Netflix on the way to stay its use to advance the subscriber’s involvement, explore other countries for expansion, use multi-factor authentication for subscriber authentication, reduce the subscription cost for developing countries like India, use more advanced authentication or multi-factor authentication and produce more original content for a specific region.
Business Analytics
Business analytics is the process where statistical analysis is used. To support the analysis and control of coming business intelligence forecasts, multiple possibility techniques including data mining, statistical modeling, and machine algorithm learning are used in this strategy (Georgetown University, 2018). To sum up, the main aim is to investigate analysis insights and gain information about their subscriber’s preferences.
Subscriber’s experience
AB test is used to individualize subscribers’ understanding. There are two different editions for subscribers and monitor and record subscriber reactions. Netflix uses Landing cards. Every video teaser or image found on the web page of the customer is known as a landing card. This strategy allows Netflix to hook its subscriber’s attention. When the images and videos shown are aesthetically pleasing to their audience, they are more likely to pay attention.
Conclusion
In conclusion, we have discussed regarding Netflix prize competition and the winning team. We also have discussed the recommendation system and recommendation technique used by Netflix. We also discussed how data analytics is used in creating the content which would be a huge victory. We also discussed SWOT and PESTLE analysis and presented a few suggestions on how to improve Netflix.
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