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Third Year Big data report - Netflix
Big Data Analytics for Business Transformation (BU32006)
University of Dundee
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How Netflix can use Big Data to Tackle the Problems Caused by Password
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Contents
Summary 2
Introduction 2
Procedure 3
Background on Netflix 3 - 4
Netflix’s Transformation 4
How Netflix Uses Big Data 5
Ethical Side to Netflix’s use of Big Data 5 - 6
Netflix’s Plan to Tighten Down on Password Sharing 6 - 8
Conclusion 8 - 9
Bibliography 10 - 11
Appendices 11
Summary
Page
This report will examine how Netflix has used big data to change the way we watch television. It will explore the issues surrounding password sharing and the impacts that tightening down on password sharing will have on Netflix and its users.
This report will assess the need for Netflix to take action and will recommend various solutions to this problem.
Introduction
Big data in simple terms is huge volumes of data. ‘Big Data’ is continuously growing, every second of every day. It is vast amounts of data that can be analysed to reveal patterns and trends. It can help lead to better decisions being made and better strategy’s being built. Data can be categorised into both structured and unstructured.
The 3 Vs used to define big data have now grown to 5 Vs; variety, volume, velocity, value and veracity. Variety refers to different types of data. Volume refers to the size of data. Velocity referring to the speed of change. Value referring to the value of the data to the company. Finally, Veracity referring to the uncertainty of the data[ CITATION Ber15 \l 2057 ].
Netflix is a streaming service that allows subscribers to watch award winning tv shows, movies and documentaries. The 158 million [ CITATION Jar19 \l 2057 ] paying subscribers can watch the thousands of TV shows and films available both at home and on the go. Big data is fundamental to the way in which Netflix operates. They use big data to analyse and predict preferences of users, instead of relying on creative directors instinctive [ CITATION Sun16 \l 2057 ].
Netflix gathered users’ preferences to create the original series, House of Cards. Netflix used big data to confirm that a remake of the original series would be a winner. The data showed Netflix that a combination of the actor Kevin Spacey, director David Fincher and a spin off on the story line of the original House of Cards, would be a guaranteed success. Through their effective use of big data, Netflix have been able to transform their business into, not only a platform that provides mainstream films, but gives users access to original Netflix content. Netflix own the rights to stream their original content [ CITATION Net19 \l 2057 ] which means value is being added to the business.
Blockbuster’s brand online [ CITATION Gre14 \l 2057 ]. Blockbuster rejected this offer and in 2010 the company filed for bankruptcy protection [ CITATION Tif19 \l 2057 ].
Netflix’s Transformation
Netflix has transformed the way people watch movies and tv series. Before Netflix, people would have to plan around when a film or show was aired on TV. Now, there is no need to plan, as Netflix allows users to watch whatever they want, wherever they want to. Subscribers are able to steam any of Netflix’s thousands of films or series on whatever digital form is easiest. Whether it’s on a television, tablet or mobile, Netflix is always ready to be watched. Instead of having to wait a week until the next episode comes out, Netflix uploads the whole series so that subscribers can binge watch until they have finished.
Netflix has also transformed the way in which movies and series are created. Having 158 million subscribers, means access to a vast amount of data. ‘The more subscribers Netflix gets, the more data it amasses’[ CITATION Ben16 \l 2057 ]. This data is used to create films and series that are guaranteed to be a hit, for example House of Cards.
Netflix’s transformation has disrupted the entire movie and television streaming industry. The company’s innovation has led to other companies falling behind as they can’t keep up with the technological changes as well as Netflix do. Furthermore, Netflix has transformed customer experience by offering a service that can be used whenever is needed and for as long as needed. This has led to improved customer satisfaction, meaning an increase in revenue for Netflix.
Netflix’s transformation has allowed them entry to new markets. They are now not only a steaming service, but they are also producers as they create their own ‘original’ content. This is due to big data analytics which has supported them to make this decision. “Netflix is expected to spend more than $14 billion this year on original content” [ CITATION Nic19 \l 2057 ]. This entry into a new market allows them to produce exactly what their audience wants. This customer satisfaction from original series will attract new customers who also want to watch the new hit shows designed by Netflix.
How Netflix Uses Big Data
Netflix uses structured and unstructured data to better understand their subscribers, they can see what they are watching, browsing and skipping. Because Netflix is such a big company, they have huge volumes of data and their understanding of users is becoming more granular. This data gives Netflix insight into their customers, what they like and what they don’t like. There are lots of different Niches that people like to watch, and if Netflix provides content for all of those different niches, they will have a ready audience for those types of content.
Netflix uses big data to recommend to users what to watch next. 80% of what users watch on Netflix is driver from recommendations [ CITATION Bla19 \l 2057 ]. Netflix has put a lot of effort into fine tuning their algorithms so that it will understand consumers and then give them the content that they will actually enjoy.
Netflix using big data gives them many a competitive advantages against other companies. It allows them to make fast and confident decisions, improves their responsiveness and gives them built in market research [ CITATION Dav18 \l 2057 ]. The use of big data secures them with accurate facts which can then help them to make better decisions within the organisation.
Big data allows Netflix to identify trends and patterns before they even occur. This level of responsiveness ensures they have a competitive advantage. Through the continued use of big data to analyse future trends, this guarantees the long-term survival for Netflix because they understand the needs of the users. Through the use of big data, Netflix can use big data to constantly track and analyse what people are watching, from what date they watched a show to when the user pauses the show [ CITATION Mic19 \l 2057 ]. They use big data to gain access to what users search for and watch on Netflix to create a unique recommendation list for each account.
Ethical Side to Netflix’s use of Big Data
The number of Netflix’s subscribers are growing, meaning the amount of data that they have access to is also growing. A company having vast amounts of data could mean that they take advantage of this. Netflix can see what shows different users binge watch from the data it
However, it was decided this was not an effective way to stop the problem as people will hardly ever sign in and out of the account so the strategy would barely be tested.
The second, and most effective tactic we recommend is geographical fencing of the Netflix account. This would ensure that mobile phones and tablets using the account would be restricted to using it in a certain area. This would effective at stopping the owner or users sharing the account with too many other people.
A final strategy that we recommend would be the use of Touch ID when using Netflix. However, this would not feasible as many laptops and tablets do not have the facilities to use Touch ID.
It has to be noted at this point that Netflix is not wanting all users to have their own individual account – they are wanting to stop too many people using one account. They want to encourage people to have a maximum of 5 profiles on their account which means 5 individuals using the account. If people are using the streaming site correctly, this allows Netflix to operate efficiently and provide an excellent customer experience.
There will be many positive outcomes to both Netflix and users if this problem is solved.
It was found from our survey that over 35% (Appendix 1) of our participants share their Netflix account with more than 5 people. This is the exact problem that Netflix is trying to solve, and the collection of our own data shows this is indeed a real problem.
An obvious advantage for the streaming company if people are forced to set up their own accounts, is a substantial increase in their profits. Netflix and other similar companies “lose billions of dollars” a year because of too many people using one account (Villas-Boas, 2019). If there is the correct number of people on an account, and they all have their own profile, then this means the users will be able to make better use of recommendations. This will have an overall positive impact on their customer experience. It also means users will feel more secure about who has access to their data if they know who is using their account. This means Netflix will gain a better imagine as they will be providing members will more secure accounts once the tactics have been implemented. They may even gain new subscribers due to their improved reputation.
However, there will also be negative impacts on Netflix that come with this major change. From our data we found some conflicting opinions. A few participants commented that they find recommendations based on what the other account users watch useful and that they find things to watch that Netflix would not have recommended to that individual person. Stopping password sharing would mean these individuals would not receive such a large variety of recommendations.
Another trend that came from our survey was that if people were going to have to pay for their own accounts, then they want to see more being offered to them (Appendix 2). For example, Netflix should be offering music and other benefits included in the subscription. This could become a competitive advantage for Netflix if they offered music as this is something Amazon Prime currently offers to members. Netflix would have to gather data about the kind of music consumers would like and this could be based off of their viewing history (such as documentaries about musicians) or their age group.
Adding music to the membership of users could also lead to the creation of a new market as more online streaming services might follow suit and the competition could increase. This problem will be easily solved by Netflix once they see a dramatic boost in their profits because of the increased number of accounts. With this money and the use of big data, they will be able to improve the experience of their members and retain and gain more subscribers.
Conclusion In conclusion, through Netflix’s transformation, it has become a global business with millions of subscribers. The business has been successful in using the data gathered to; identify trends and patterns before they even exist, achieve competitive advantage and provide excellent customer experiences.
In terms of the ethical use of Netflix’s big data, the company are showing to only use the data collected to enhance customer experience. However, as the amount of data that the business has access to is growing rapidly, this is starting to worry customers when they start thinking about it. Netflix needs to ensure they don’t get persuaded to misuse the customers data and keep performing within the data protection act.
Bibliography
Dixon, M., 2019. Selerity. [Online] Available at: seleritysas/blog/2019/04/05/how-netflix-used-big-data-and- analytics-to-generate-billions/ Erevelles, S., 2016. Big Data consumer analytics and the transformation of marketing. Journal of Business Research, 69(2), pp. 897-904. Hsu, T., 2019. The World’s Last Blockbuster Has No Plans to Close. The New Year Times. Jarvey, N., 2019. Netflix Recovers From Rocky Second Quarter, Adds 6 Million Subscribers. Hollywood Reporter. Levin, S., 2019. Netflix co-founder: 'Blockbuster laughed at us ... Now there's one left'. The Guardian. Marr, B., 2015. Data Science Central. [Online] Available at: datasciencecentral/profiles/blogs/the-5-v-s-of-big-data-by- bernard-marr [Accessed 03 12 2019]. Morgan, B., 2019. What Is The Netflix Effect?. Forbes. Morris, D. Z., 2018. Fortune. [Online] Available at: fortune/2018/07/08/netflix-original-programming-13-billion/ [Accessed 03 12 2019]. Netflix, 2019. Neflix. [Online] Available at: help.netflix/en/node/ [Accessed 03 12 2019]. Newman, R., 2010. US News. [Online] Available at: money.usnews/money/blogs/flowchart/2010/09/23/how-netflix-and- blockbuster-killed-blockbuster [Accessed 03 12 2019]. O'Brien, C., 2016. My conversation with Netflix CEO Reed Hastings. Business Insider.
Pegg, A. H. a. D., 2018. Facebook fined for data breaches in Cambridge Analytica scandal. The Guardian. Sadowski, J., 2016. Companies are making money from our personal data – but at what cost?. The Guardian. Satell, G., 2014. A Look Back At Why Blockbuster Really Failed And Why It Didn't Have To. Forbes. Stratt, N., 2019. Apple reportedly ups TV spending by $5 billion to compete with Amazon and Netflix. The Verge. Villas-Boas, A (2019) Big streaming companies like Netflix and HBO are looking to crack down on freeloaders who use other people's passwords and accounts, Available at: businessinsider/netflix-hbo-streaming-companies-look-to-prevent- account-password-sharing-2019-11?r=US&IR=T (Accessed: 04/12/2019).
Wilson, B., 2016. How Netflix changed the way we watch. The Telegraph.
Appendices
Third Year Big data report - Netflix
Module: Big Data Analytics for Business Transformation (BU32006)
University: University of Dundee
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