Case 1 Netflix BIS 371
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School
Illinois State University *
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Course
371
Subject
Information Systems
Date
Dec 6, 2023
Type
docx
Pages
2
Uploaded by SuperBat3088
1.
What are Disney's strategy goals related to launch of their third streaming service Disney+?
Disney’s output and creativity was declining after Walt Disney had died, and avoided getting taken over, instead named Michael Eisner the head of Disney’s movie studio. He increased both quantity and quality of Disney’s movies, however, was pushed out in 2005 due to a Disney’s shares stagnating. Bob Iger soon took over, leading to buying the Marvel comics franchise, acquiring 21
st
Century Fox and Fox, upgraded and expanded its parks globally, and lastly getting into the market of video-on-demand with new streaming services such as Disney+. In 2017 to 2019 the percentage of people who subscribed to more than one streaming service doubled, allowing
Disney to take advantage of this opportunity and roll out Disney+ in the fall of 2019, creating enormous opportunities for them. Their goals began to be more focused towards streaming and the progression of consumers moving towards streaming services as a whole and the renovation of the entertainment industry.
2.
What machine-learning use cases would best help accomplish these goals. It might be helpful to categorize these into three areas (descriptive, predictive and prescriptive). Artificial intelligence and Machine Learning utilizes historical data to make
predictions with enormous amounts of data and input variables and helped to create models as well as answer questions such as, “Which of these things
are similar?” (descriptive), “Which are most likely to act in a certain way?” (predictive), and “How can we affect the outcome?” (prescriptive). Machine learning allowed for Disney to be able to understand how humans process information and attribute relevant data and variables to humans or other variables. This helped to better understand how to appeal to the consumer and mimic a model that could predict what and where humans are going and
what they interact with, within streaming and entertainment. 3.
What can be learned from Netflix's use of Machine Learning? Netflix’s use of machine learning has led them to being one of the top competitors within the streaming services industry. Netflix gave incentives to people who could help progress their already in place algorithms to better appeal to the consumer, ultimately, making an impact on the industry and making them an organization that we can learn much from. They used machine
learning to incorporate a recommendation system from users’ data such as their profiles, ratings, and similar users. Their use of Machine learning contributed to generating content recommendations which accounted for ~80% of the TV shows that people watched on the service. ML also helped to find “characteristics that make content successful,” and give them competitive advantage by creating efficiencies in the show development and production processes and individualizing and improving the user experience. All these uses can be seen
being used by others within the streaming industry and learning from how Netflix uses their Machine Learning to increase customer satisfaction and continue learning and growing.
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