SUSTAINABILITY OF NETFLIX’S BUSINESS MODEL
This piece has been authored by Ayushi Goel, a third-year student at Rajiv Gandhi National University of Law, Punjab.
Netflix’s Business Model
Netflix started out as an internet-based DVD-rental service during the late 1990s. It allowed users to surf through a large collection of movies and tv-show titles on its website. Users would pick the titles they wanted to rent. The DVD of the same was then delivered to them by postal service along with a prepaid envelope for returning it after the rental period expired. Users could have as many titles in their possession at any given time as their subscription plan allowed.
Gradually, Netflix allowed its users to stream the movies and shows online, while also retaining its DVD-rental feature. Subsequently, Netflix plunged into content creation where it would produce Netflix originals for the exclusive viewing of its subscribers. House of Cards was its first notable original production. In 2010, Netflix went international. By 2016, Netflix had established its market in most countries. Whereas its rental and streaming wings remain profitable, what attracts new subscribers to Netflix is its fresh content. These new subscribers are the biggest source of revenue for Netflix.
Unlike a lot of other digital media platforms like Amazon Prime which mostly catalogues and streams existing movies and shows, with only a small portion dedicated towards producing original content, Netflix’s business model is centered around the rapid churning out of content under the banner of Netflix Originals. This is primarily responsible for its rapidly expanding consumer base.
Aswath Damodaran, an economics professor at the New York University, has pointed out that Netflix’s business model is not economically viable[i]. Netflix’s valuation in the market has increased manifold during 2010-2017. Netliflix’s rapidly increasing consumer base is the primary reason behind this apparent investor-community faith in Netflix. Damodaran argues that Netflix uses its original content to attract more and more subscribers. However, content-creation is a very cost-intensive activity. In 2018, Netflix released 1,500 hours of Netflix originals[ii]. This is very proactive by any studio’s standards. The costs of content creation are immense, from poaching famous Hollywood talent to commissioning scripts and set-design, it is a costly affair.
Damodaran has predicted that in order to retain the faith of its investor-community, Netflix has to keep churning out content at the same pace, so that it keeps attracting new subscribers and does not lose out on the existing ones. What Netflix is also doing in order to gain new subscriber-base, especially ever since its debut in the developing countries, is offering subscriptions at very cheap, promotional rates. Netflix cannot, anytime in near future, increase its prices significantly, or it will run the risk of losing its newly-achieved not-so-loyal consumer-base.
In short, Netflix’s balance sheet shows more expenditure than receipts. This expenditure is, in principle, owing to Netflix’s decision to pursue content creation relentlessly. In October last year, Netflix announced that it would raise $2 billion in debt-financing to fuel its content creation. However, even if Netflix wanted to break-free of the high costs of content creations, it could not stop producing content at the current rate. If it does, it runs the risk of losing subscribers who joined in the first place due to Netflix originals, which in turn will force investors to retract their investments. However, there will come a time, sooner rather than later, when Netflix will have reached its saturation point as far as gaining new subscribers is concerned. It is at that point that the balance sheet deficit is going to sting and Netflix is going to come crashing down.
Legal Viability: Big Data and Anticompetitive Concerns
In the year 2006, Netflix launched a contest to come up with an advanced algorithm that could analyze user preferences based on their viewing history. The amount of prize money was US $ 1000,000, which goes on to show the importance of this big data algorithm to Netflix.
Big Data refers to the new methods and algorithms facilitating collection, storage, and analysis of data that is beyond the scope of traditional databases[iii]. Access to consumer data not only allows Netflix to prompt suggestions to its viewers based on their viewing history, but Netflix has admitted that its algorithms store and process user data in a way as to divulge their preferences and taste. Netflix then uses this data to produce content tailored for those category of viewers. Netflix’s Jonathan Friedland has admitted that Netflix’s algorithms knows what people like to watch and this “gave them confidence that they would find an audience for a show like House of Cards.”[iv] This abuse of data is not only a direct infringement of users’ right to privacy, which is a separate legal discussion, but also has anticompetitive dimensions.
Anticompetitive practices refer to any agreement, decision, or practice which constitutes barrier or restriction on trade[v]. According to Smith and Telang, with their sophisticated algorithms, big companies use the user data to gauge if there’s any demand in the market for their content-ideas, resulting in highly targeted and preference-based marketing[vi]. Not only does Netflix make use of user data to tailor its content, but also prevents its competitors and others from accessing this data. Not only this, users are prevented from accessing their own viewing data. In a competitive market, users would have a choice not to agree to this condition but Netflix is a dominant player, hence users give in to this demand.
Not only does this restricting of data give Netflix an unfair competitive advantage over other small distributors who do not have access to such sophisticated algorithms, but it also gives Netflix an edge in negotiations in its contracts with actors and directors. Netflix refuses to share with them how many views their movie or show received, in the absence of which, they are at a disadvantage as to evaluating and negotiating as per their worth. Thus, it could be easily said that, Netflix is abusing user data to gain anti-competitive advantage and exclude competition from the market.
If Netflix wishes to keep out of the antitrust net, it needs to seriously reconsider its big data policies. Although, Netflix’s home country, U.S is seemingly reluctant to look into antitrust concerns of big data, E.U is coming down upon the same with an iron fist. A number of companies there are facing huge fines for anticompetitive use of big data. Now that Netflix has gone completely global, it needs to bring its policies in compliance with regional and domestic legislations of the countries it is operating in.
[i] Fred Imbert, Finance professor Damodaran says Netflix's big-spending business model can't last, CNBC(Oct. 23, 2018), https://www.cnbc.com/2018/10/23/finance-professor-damodaran-says-netflixs-big-spending-business-model-cant-last.html ( last visited Apr. 19, 2019).
[ii] Mark Sweney, Netflix puts content above costs but is the policy sustainable?, The Guardian(May 25, 2018), https://www.theguardian.com/media/2018/may/25/netflix-puts-content-above-costs-but-is-policy-sustainable (last visited Apr. 19, 2019).
[iii] Joshua D. Wright et al., Antitrust Analysis of Big Data, 2 CLPD 35, 41 (2016).
[iv] Tien Tzuo, The Netflix Effect, Medium(Oct. 2, 2014), https://medium.com/@tientzuo/the-netflix-effect-49e31f4ff050 ( last visited Apr. 19, 2019).
[v] Ovidiu-Horia Maican, Anticompetitive Practices, 4 Persp. Bus. L.J. 180, 186 (2015).
[vi] Michael D. Smith, Rahul Telang, Streaming, Sharing, Stealing: Big Data and the Future of Entertainment, (6th ed. 2016).