Valuation of User-Based Firms

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Valuation of User-Based Firms

The case of Netflix Inc

Mathilde Meier Mysen (93774) and Amalie Antonette Foss (93081) Supervisor: Søren Ulrik Plesner

Master thesis, Applied Economics and Finance

Total characters excluding tables: 268,278 Pages: 118, Contract no: 14234

This thesis was written as a part of the Master of Applied Economics and Finance at CBS. Please note that neither the institution nor the examiners are responsible – through the approval of this thesis – for the theories and methods used, or results and conclusions drawn in this work.

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Digitalization has introduced an economy where numerous companies measure their success based on the network of users, rather than the cash flows. In this thesis, we aim to apply Netflix as a case study to find the most accurate valuation method for user-based companies. Subscribers, both new and existing, are essential value drivers in user-based firms. Thus, by using the User-Based Valuation framework constructed by Damodaran (2018), instead of Free Cash Flow through the Discounted Cash Flow model, we are better equipped to include these significant value drivers.

Further, by using the User-Based Valuation, we are able to include other essential value drivers for user-based firms, namely the usage of Big Data and network effects, which enhances the subscribers’ value.

Master thesis –Applied Economics and Finance, CBS 1

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Executive Summary

The digitization has caused a shift in the economy, with firms utilizing innovative technologies to create new business models. Where high entry barriers previously was a way for firms to keep new entrants out of the video entertainment industry, the digitalization has led to lower capital needs and a higher industry rivalry. However, by creating original content, firms can differentiate themselves from competitors, and the use of Big Data helps the producers customize their content to keep existing users and attract new ones. Further, the user-based firm benefits from network effects, where every additional user enhances the firm value. The change in value drivers, from focusing on pricing units to valuing users, are challenging the traditional way to use the Discounted Cash Flow (DCF) when valuing user-based firms.

We aim to find the most suitable valuation method for user-based firms, using Netflix as a case study.

Subscribers, both new and existing, are essential value drivers in user-based firms. Thus, by using the User-Based Valuation (UBV) framework constructed by A. Damodaran (2018a), instead of the Free Cash Flow, we are better equipped to include these essential value drivers. Through the UBV, we find the value of Netflix to be less sensitive to changes in assumptions concerning future growth in revenue and costs. Further, by using the UBV, we can more easily include the effects of Big Data and network benefits in the valuation. The UBV correspondingly has shortcomings when it comes to the quality of the estimates, because of fewer disclosure requirements regarding user information, renewal rate, and customer-acquisition costs.

The UBV method simplifies the comparison of user-based firms, as the value of new users fluctuates greatly depending on the revenue model of the firm. This method makes it easier to understand why some user-based firms, like Netflix, have a higher enterprise value in relation to cash flow, compared to other comparable firms. Netflix has great potential in new subscribers, as their variable costs are low, giving the firm’s high economies of scale when adding subscribers to their service, which is enhanced by network effects. In addition to this, their use of Big Data in content production helps the firm increase its user renewal rate through customized original content and personalized and efficient interface. Both of these essential drivers come to light using the UBV, which gives us a significantly higher value estimate of $309 per share compared to $192 in the DCF. Comparing Netflix to competitors and other user-based firms, we find that Netflix’s high growth expectations and high EBIT per subscriber supports a value exceeding $300. Because of this, we find the UBV to achieve a more accurate value of user-based firms than the DCF model, especially when the information closures regarding users is high.

Master thesis –Applied Economics and Finance, CBS

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List of Figures

2.1 Netflix timeline 1997-2019 . . . 16

2.2 Number of Subscribers of Netflix from 2011-2018, including free trials . . . 17

2.3 Annual Avg. Adj. Closing Price . . . 18

3.1 MilleXZials exhibit stronger binge-watching behaviors . . . 29

3.2 Video Streaming on different servers . . . 33

4.1 Advanced DuPont Model . . . 53

4.2 Drivers of ROE . . . 54

4.3 Drivers of RNOA . . . 55

4.4 Short Term Liquidity Comparison, Average current ratio . . . 58

4.5 Net income vs. Cash Flow from operations vs. Non-GAAP FCF . . . 61

4.6 Development in Subscribers for HBO, Netflix, Hulu, and Amazon Prime . . . 64

4.7 Development in CAC for the Domestic and International market . . . 67

4.8 Development in LTV for the Domestic and International market . . . 68

4.9 Gross profit per subscriber for HBO and Netflix . . . 69

5.1 Strengths, Weaknesses, Opportunities, and Threats for Netflix . . . 71

7.1 Output of simple regression on Netflix and S&P 500’s return . . . 84

9.1 Price Development of Netflix’s Standard Plan . . . 95

9.2 Percentage of Netflix users by age . . . 97

9.3 Development in costs $M . . . 99

9.4 The value of new users . . . 101

9.5 Corporate Drag drivers . . . 102

10.1 Price to Sales Ratio . . . 106

10.2 PE ratio . . . 107

10.3 PEG Ratio . . . 108

A1.1 Monthly Adjusted Closing Price . . . 131

A2.1 Time spent per user on Leading Video Streaming Service . . . 131

A4.1 Short Term Liquidity Comparison . . . 133

A4.2 Interest Coverage Ratio Drivers . . . 134

A6.1 The value of existing users . . . 137

A6.2 The value of new users . . . 137

A6.3 The Corporate Drag . . . 137

A6.4 Streaming Revenue Development . . . 138

A6.5 Forcasted Variable Cost for Existing Subscribers . . . 138

A7.1 Earnings Multiples . . . 139

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List of Tables

3.1 Media consumers divided into Five Generations . . . 29

3.2 PESTEL Summary . . . 33

3.3 Porters Five Forces Summary . . . 43

3.4 Value extraction gained from Big Data . . . 48

4.1 Analytical Balance Sheet . . . 50

4.2 Tax Payments . . . 51

4.3 Analytical Income Statement . . . 51

4.4 Current and Quick Ratio for Netflix . . . 57

4.5 Solvency Ratio for Netflix . . . 58

4.6 Interest Coverage Ratio for Netflix . . . 59

4.7 FCF 2013-2018, in million dollars . . . 60

4.8 Content obligations Netflix 2013-2018 . . . 62

4.9 Change in Gross Added Customer . . . 64

4.10 Churn rate 2012-2018 . . . 66

4.11 Ratio LTV/CAC 2012-2018 . . . 69

6.1 Annual weights . . . 74

6.2 Revenue growth 2019-2029, DVD segment . . . 75

6.3 Revenue growth 2019-2029, Domestic streaming segment . . . 77

6.4 Revenue growth 2019-2029, International streaming segment . . . 78

6.5 Aggregated revenue and revenue growth 2019-2029 . . . 78

6.6 Cost of revenue 2019-2029 . . . 78

6.7 Other costs 2019-2029 . . . 79

6.8 Amortization of revenue 2019-2029 . . . 79

6.9 Net financial income 2019-2029 . . . 80

6.10 Forecasted Income Statement . . . 80

6.11 Current assets 2019-2029 . . . 80

6.12 Non-current assets 2019-2029 . . . 81

6.13 Current liabilities 2019-2029 . . . 81

6.14 Non-current liabilities 2019-2029 . . . 81

6.15 Forecasted Balance Sheet . . . 82

7.1 Industry Beta . . . 85

7.2 Cost of Debt . . . 88

7.3 Historical capital structure . . . 89

7.4 Wacc inputs . . . 90

8.1 CAPEX Calculations . . . 91

8.2 DCF Valuation . . . 92

8.3 Sensitivity analysis, with new values as a percentage of old . . . 92

9.1 Total Subscribers Renewal Rate . . . 97

9.2 Development in Monthly Fee’s 2015-2018 . . . 98

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9.3 Subscription Development . . . 98

9.4 Value of Existing Subscribers . . . 99

9.5 Subscriber Adds as % of Base . . . 101

9.6 Value of New Subscribers . . . 101

9.7 Total Value of The Corporate Drag . . . 103

9.8 Value of Netflix in the Base Scenario . . . 103

9.9 Sensitivity analysis, with new value as percentage of old value . . . 104

10.1 Earnings Multiples . . . 106

10.2 Earnings growth . . . 106

10.3 Enterprice Value/Users and Revenue/Users . . . 108

A3.1 Advanced DuPont Calculations . . . 132

A3.2 Advanced DuPont ROE . . . 132

A3.3 DuPont Calculations, RNOA . . . 132

A4.1 Summary of risk analysis . . . 133

A4.2 Quick and Current Ratios for Industry & Peers . . . 133

A5.1 CAC Calculations . . . 134

A5.2 LTV Calculations . . . 135

A5.3 LTV/CAC for Netflix . . . 135

A5.4 HBO Subscription Analysis . . . 136

A6.1 Total Subscribers Renewal Rate . . . 136

A6.2 Cost of adding new subscribers . . . 136

A6.3 Technology Growth Rate . . . 138

A6.4 Value of existing users . . . 139

A7.1 Multiple Analysis Sources . . . 139

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1 Introduction

1.0.1 Datafication

Digital transformation is pushing companies in many industries to compete in new ways, by rethinking their business models from selling and contracting products to providing decision support through Big Data analytics. Due to the digital ubiquity associated with Internet Of Things, the business world as we know it will be completely transformed (Iansiti & Lakhani, 2014).

There are several benefits from the new digital technology, like data extraction, analysis, personalization and customization, and continuous experimentation (Varian, 2014). The digital transformation and the increasing use of Big Data to personalize the services has led to a high focus on the value of a user in these new companies. The value of user-based companies is arguably composed of the number of users or subscribers (A. Damodaran, 2018a).

Discounted cash flow (DCF) is one of the most common valuation methods used to estimate the value of an investment. However, the digital transformation appears to be making a shift into an economy where companies measure their success based on the number of subscribers, customers or users they have, rather than the cash flows. The value of a network and a user base is increasing with the use of Big Data in business decisions and strategies, and the traditional DCF valuation will in some cases fail to consider the importance of the number of users connected to these online platforms and services.

This shift has led to a new approach to valuing user-based firms, called the user-based valuation (UBV) (A. Damodaran, 2018a).

In theory, valuation models should yield identical value estimates when the models are based on the same inputs (Petersen & Plenborg, 2012). In this thesis, we will apply both the DCF model and the UBV model to determine if the models can be perceived as substitutes and hence if the models yield the same value estimates. We will apply Netflix as a case study, to better determine how the models perform when valuing a user-based company.

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1.1 Problem statement and sub questions

Netflix has managed to capitalize on the benefits of datafication. The company is recognized for its subscribers, mostly through its high subscription growth. As Netflix is a good representation of a digitalized, user-based company, we will use the company in our case study in order to evaluate which valuation model is most suitable for user-based firms.

We seek to assess Netflix’s performance and value by applying the mentioned valuation techniques. First, we will examine how Netflix managed to shift its business model in order to grow exponentially, and how the firm continuously plans to succeed in following the vast changes in the industry. Furthermore, we will analyze if Netflix can exploit the datafication in a way that will give them a sustainable competitive advantage. Looking into this will help us forecast future performance, and value the equity of the firm through various techniques.

The purpose of the thesis is to examine if the valuation models can be perceived as substitutes, or if one of the models provide a better fit for valuing a user-based firm like Netflix.

This has led us to the following problem statement:

"How to value the equity of user-based companies applying a traditional and user-based valuation method"

• How has the datafication impacted the way user-based firms can be valued?

• What characterizes the video entertainment industry, and how has datafication changed the industry drivers?

• How do internal and external factors affect the value of Netflix?

• How has the financial position and subscriber base of Netflix developed historically and what are the drivers?

• How are significant determinants from the fundamental analysis expected to affect the future performance of Netflix?

• Does the User-Based Valuation outperform the DCF when finding a value estimate for Netflix?

• How can we generalize the findings to the valuation of other user-based firms?

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1.1.1 Motivation

Our motivation for this project is highly driven by our interest in Big Data and innovation. Big Data is emerging as a corporate standard, and the focus is rapidly shifting to the results it produces and the business capabilities it enables. The increased value of data has led to a drastic change in the way businesses operate where the value of subscribers or users to collect data from, is growing swiftly.

Netflix operates in a dynamic environment, and the industry is continuously changing, which result in significant growth opportunities. Netflix is an example of a company that successfully shifted its business model multiple times and grew exponentially because of that — transferring from renting boxed products through mail to delivering on-demand entertainment to individuals all over the world.

Since Netflix launched its streaming service, several competitors have entered the market. Among some are Amazon Prime Video, Hulu, Facebook Watch. Despite this, Netflix is still in the role of the market leader, serving more than 139 million customers. Hence, Netflix’s successful business model and the firm’s focus on the usage of Big Data triggered our interest to write about the valuation of user-based firms.

1.2 Choice of models

We will first cover the different valuation methods, and as we make use of the models, we will discuss the models’ assumptions and limitations. This approach is vital to come closer to the conclusion of which model will be best suited for a user-based firm.

1.2.1 Fundamental valuation using the DCF model

One of the most common valuation methods is fundamental analysis. When using this method, we attempt to assess Netflix’s intrinsic value, by examining related economic, financial and other qualitative and quantitative factors. Studying different macro and micro-economic factors affecting the value of the firm, and use this, together with the historical financial performance, to produce a forecast. Lastly, we will use the predicted forecast, and a suitable discount rate to calculate the discounted cash flow (DCF) to find the present value of the firm (Kenton, 2018).

1.2.2 User-Based Valuation (UBV)

The digitalization, and the new business models that follow add new encounters when finding the best way to determine their enterprise value. Because of this, it might be useful to value Netflix from a different perspective, looking at the value of each user on a disaggregated basis, and then sum the

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results to find the value of the entire company. When using this model, we will distinguish between existing users and new ones. Existing users will be valued based on their loyalty and the profits they generate, while when calculating the value of new users, we need to subtract the cost of acquiring new users before determining their value (A. Damodaran, 2018a).

1.2.3 Relative Valuation

Comparing Netflix’s value to the value of the industry peers will help us obtain a better assessment of its financial worth. This method is an alternative to the DCF and UBV, where we use multiples, averages, ratio, and benchmarks to determine the firm’s value. In the relative valuation, we will use enterprise-based, equity-based and subscription-based multiples for Netflix and the peer group.

1.3 Delimitation

1.3.1 Time Limit

A company valuation is usually highly dependent on the company’s performance as well as the underlying general economic environment and financial markets. Because of this, it is necessary to set a cut-off date for when new information is no longer considered to avoid having to constantly change the underlying assumptions and arguments for the valuation. The value of Netflix will be determined as of 31th of March 2019, meaning that any information published after this date is not regarded.

1.3.2 Information

When describing and presenting Netflix as a company, we focus on the essentials regarding the market value of the company. Moreover, the value estimate is calculated on a stand-alone basis, and no synergy effects are accounted for. In line with a typical investor analysis, we will solely make use of secondary data, because the company is listed on the stock exchange in the period covered in the analysis. This ensures that the valuation is based on the same level of information as attained by the investors, as it is assumed that the investors do not hold any internal information. We assume that the reader is familiar with the economic and financial theory used in the analysis and will therefore not conduct a detailed discussion and proof of the models applied.

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1.4 Thesis outline

We will first give an understanding of the business model of Netflix through an introduction of the industry, company, and competitors. Throughout the thesis, we will focus on investigating value drivers, and how these drivers will affect the current and future growth.

1.4.1 Strategic Analysis

The strategic analysis is divided into three parts, to characterize macro, industry and internal factors affecting the value creation for Netflix as well as the whole video entertainment market. To gain insight about the macro factors driving the video entertainment industry we will use the extended version of PEST, namely the PESTEL framework. This framework includes a broad range of relevant macro factors influencing the company’s environment. Porter’s five forces are applied to develop an understanding of the attractiveness and competitive environment of the industry. The framework provides insight into how the value is distributed among the players, with an external focus. The VRIN framework is used to examine if the use of Big Data in decision making provides Netflix with a sustainable competitive advantage. VRIN is a classic framework, also called the "resource-based view of the firm" which states that, for Big Data to provide a sustainable competitive advantage, it has to be inimitable, rare, valuable, and non-substitutable (Lambrecht & Tucker, 2015).

1.4.2 Financial Analysis

In the financial analysis, we will evaluate the financial performances of Netflix from 2013 to 2018. The aim will be to identify Netflix’s historical earnings and performance by dividing the accounts into operational and financial activities. The analysis aims to investigate changes in the essential figures of Netflix and the peer group. Using the Advanced DuPont model, we perform a profitability analysis to examines whether the historical changes in the essential figures are company-specific or if there is a general trend in the video entertainment industry. Furthermore, we use a liquidity risk analysis to measure financial risk and the company’s ability to meet future obligations. The cash flow analysis examines Netflix’s cash flow in relation to its net income. Lastly, we perform a subscription analysis to explore the development of subscribers as well as the profitability of the subscribers.

1.4.3 SWOT

We make use of the SWOT framework to state important findings from the strategic and financial analysis in a structured manner. Furthermore, we will specify the most significant value drivers for

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Netflix recognized throughout the analysis.

1.4.4 Forecasting and valuation

The findings from the strategic and financial analysis are used to design pro forma financial statements for the future. The pro forma statements will form the basis for the present value models. After forecasting and calculating the equity value based on both the DCF and the UBV, we will make use of the peers to acknowledge Netflix’s value relative to the substitutes and competitors. These models are based on different assumptions, which will be elaborated in the respective sections.

1.4.5 Sensitivity analysis and discussion

After conducting the different valuation methods, we will provide a sensitivity analysis to examine how changes in the elemental value drivers affect the value estimates. The sensitivity analysis will be helpful when determining the uncertainty concerning the models, and how this affects the reliability of the approaches. Lastly, we will consider the benefits and the limitations of using the different methods in valuing user-based firms and try to generalize the findings to other user-based firms.

1.5 Data Gathering and Validity

As the thesis is written from an external perspective, only publicly available information is included.

These sources include annual reports, analyst reports, financial statistics, the company’s webpage, official governmental databases, and articles. We have primarily used the books; Petersen & Plenborg (2012) "Financial Statement Analysis," Koller et al. (2010) "Valuation: Measuring and managing the value of companies" and A. Damodaran (2018a) "Going to pieces: Valuing Users, Subscribers, and Customers."

We acknowledge that there is a possibility that these sources of information contain biases and errors, which will affect our results. However, we consider our sources to meet the reliability requirements as companies are responsible for publishing accurate information, as well as websites, research reports and statistics are carefully selected. We have also availed ourselves of both internal and external analysis from highly credible analysts. Attempts are made to use a critical perspective, including the use of many different sources to verify and criticize data collection, and we have attempted to obtain a certain objective validity (Guba, 1990). However, we acknowledged that the thesis is characterized by subjectivity, as forecasting and valuation are forward-looking.

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2 Company and Industry Analysis

2.1 Industry definition

Netflix operates in the video entertainment industry, which is severely competitive and subject to rapid changes. The industry includes the telecommunication, media, and entertainment sector. Because of the digital age of multitudinous data and online streaming, entertainment is delivered more uniquely opposed to before. Today, TV shows and films are more accessible, and online viewership’s continue to rise, due to streaming sites like Netflix. By 2019 experts predict that video streaming will account for 80% of all internet traffic (Roshan, 2018). Netflix’s product is primarily online video entertainment, which includes streaming and downloading of videos or other internet-based objects. For our purpose, we will mainly focus on Subscription Video-on-Demand (SVOD) actors, a service that offers subscribers unlimited access to a range of programs for a monthly rate (Techopedia.com, n.d.).

Netflix is a user-based company. One can argue that the value of these kinds of companies is composed of the number of users. There are three user-based models. The first is the subscription-based model (ex. Netflix), the second is the advertising-based model (ex. Yelp), and the third is a transaction-based model (ex. Uber) (A. Damodaran, 2018b). Subscription models tend to be stickier, making revenues more predictable, but it is challenging to grow subscription fees at high rates. An advertising-based model allows for higher growth in a firm’s early years, and a transaction-based model has the highest potential for revenue growth from existing users. Furthermore, user-based business models can be combined. For example, a firm can charge a subscription fee simultaneously as they sell additional products and services, combining both the subscription and the transaction-based models.

2.2 From DVD to online streaming

Linear TV, where users watch cable TV programs with a fixed broadcast schedule, has been a success for centuries. Despite this, users have become increasingly dissatisfied with the navigation and complexity of cable TV, as it is both time-limited and inflexible. However, Online Video entertainment, provides users with content whenever they want, on whatever screen they want. The number of traditional Pay TV subscribers continues to drop as more people are trimming or cutting the cord completely. In 2018, 67 % of PWC’s respondents subscribed to Pay TV, which is down from 73 % in 2017 and 76 % in 2016.

PWC also found that 76 % of the respondents subscribe to Netflix, meaning that a higher amount of people subscribe to the online streaming service than to Pay TV (PricewaterhouseCoopers, 2018).

The development of Online Video had its first rise in the early days of the world wide web in 1995 when

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several formats for streaming the first videos were released. In the period 2005 till 2010, broadband penetration increased, allowing significant fractions of the population to stream online video. HTTP- based adaptive streaming quickly became the weapon of choice for high-profile live streaming events, and this introduced an increase of services like LoveFilm, Amazon Instant Video and Netflix (Zambelli, 2013). The rapid changes caused a multitude of online content producers and platforms transforming the way we consume video. Consequently, the broadcast networks started losing viewers, and pay TV customers cut the cord to go online (Wikipedia, 2019). Today, digital technology presents benefits such as open innovation, which allows for platforms to utilize crowdsourcing. Firms can similarly leverage data, and execute their businesses using machines and machine learning. Internet traffic alone generates vast amounts of data that can be converted into insightful information (Roshan, 2018).

2.3 Presentation of Netflix

Netflix, Inc. is the world’s leading internet television network with more than 139 million paid streaming memberships located in over 190 countries. The members of Netflix have access to more than 140 million hours of TV shows and movies, including original series, documentaries and feature films. The content can be watched as much as the customers want, anytime, anywhere, on nearly any internet-connected screen. Additionally, the members can play, pause and resume watching the content without commercials or commitments. Netflix offers three different streaming plans. The basic plan costs $7.99 a month and allows users to watch content on one device, the standard plan costs $10.99 and allows simultaneously streaming on two devices and in high definition, and lastly Netflix’s premium plan costs $13.99 and allows four devices to stream simultaneously and in 4K (Netflix, 2018).

Netflix started as an online DVD rental company in 1998 when Reed Hasting and March Rudolph saw an opportunity to enrich the home entertainment market. They wanted to change the less customer-friendly market, and even though VHS dominated the market, and only 2 % of the American households owned a DVD player at that time, they took a huge gamble and launched Netflix. Customers in the United States could subscribe and have unlimited access to DVDs sent to their houses. Netflix completed an IPO in 2002, allowing Netflix to repay debt and open more distribution and shipping centers to reduce time-lags between DVD shipments (Carroll et al., 2009). There was an apparent demand for DVD rental, as the number of Netflix subscribers rose from 500,000 in 2002 to 2,6 million in 2005(Oomen, n.d.).

Two years later, in 2007, Netflix launched its streaming service, making them a pioneer in the internet delivery of TV shows and movies. The streaming service was an ecosystem for internet-connected screens, with continuous supplements of content that enabled consumers to enjoy TV shows and movies

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directly on their internet-connected screens (BBC, 2018). From 2007 to 2010, the company’s streaming facilities became available on different game consoles, handheld devices and TVs in the US. In 2010, the firm further launched in Canada, following with Latin America and the Caribbean in 2011, and the UK in 2012 (BBC, 2018).

Netflix is known for being innovative, enhancing the opportunities made possible by technology. The firm was early on using Big Data to provide its users with a basic rating system. These ratings were based on the number of views, customer feedback, if videos were watched until the end and IMDB ratings. After seeing success with the rating system, they evolved their business model to gain further insight into customers preferences. They created a community for the customers and focused on tailoring the content to the individual user. Netflix continued to evolve its algorithm to an open source initiative to gain more data and technological knowledge of more people, intending to make its service even better.

In September 2009, they started a crowdsourcing competition and offered a prize of one million dollars to the crowd who came up with the best improvements to their recommendation model (Oomen, n.d.).

In 2013, Netflix started producing its original content, debuting with the series “House of Cards.” The foundation for the manufacturing of their in-house content production was their customers’ data. Netflix made use of Big Data to better understand their customer’s preferences, which gave them a substantial competitive advantage when producing the content. Where studios were only wanting to make a pilot of House of Cards, Netflix already knew that this series would become a hit based on their data, and immediately signed up for two seasons (Oomen, n.d.). Netflix is continuously improving the customers’

experience by expanding the streaming content. The firms exclusive and original programming includes several Emmy, Golden Globe and Academy Award-winning original series and documentaries (Spangler, 2018).

Figure 2.1: Netflix timeline 1997-2019

Source: own contribution

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2.3.1 Products

Considering streaming as Netflix’s main product, and the segment with the most significant growth, this will be our prime focus in the analysis. Even supposing conditions might vary within the segments, we have chosen to analyze and forecast them collectively in the user-based valuation. The Domestic DVD segment is declining and will have little impact on the total estimated value of the company.

The reasoning for the aggregated valuation is mainly because information disclosure concerning the subscribers is on an aggregated basis. Second, investors are usually interested in the value of the entire company, as it is not possible to buy shares in disaggregated parts of Netflix.

2.3.2 Geography

Netflix is situated in more than 190 countries. However, we have chosen the US market as our main focus of attention in parts of the strategic analysis. This focus is chosen since Netflix is a US based firm, where the US is the biggest market with most of the revenues coming from this market in the years 2013 to 2017. Furthermore, we will consider the company globally when preparing the financial statement and draw on the consolidated annual results in the financial analysis.

2.4 Netflix’s customer base and stock price development

Netflix has had a massive growth in both customer base as well as share price development since the establishment in 1997. Since Netflix introduced its streaming service in 2007 and with the introduction of the international expansion in 2010, the company has acquired millions of streaming subscribers worldwide. Figure 2.2 illustrates the development during recent years.

Figure 2.2: Number of Subscribers of Netflix from 2011-2018, including free trials

Source: own contribution with data retained from STATISTA

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Counting free trials, Netflix had more than 148 million streaming subscribers worldwide, including 60.55 million American subscribers, in the fourth quarter of 2018. Since the popularity of Netflix’s streaming service has increased, the company’s DVD rental service has declined. From 2017 to 2018, Netflix had a massive decline in the DVD rental service from 11.17 million to 2.73 million subscribers (Statista, 2019b). Netflix’s additional subscribers in 2018 were nearly as many as HBO added in the US during the last 40 years, giving a better understanding of how quickly Netflix is expanding both in the US and internationally (Sheetz, 2018).

Correspondingly with the subscription development, the share price development has had tremendous growth the recent years. Netflix share price has, since it when public in May 2002, increased with around 8,000 %. Figure 2.3 below illustrates the annual development of Netflix’s share price. Additionally, Appendix A1.1 displays The Monthly Adj. Closing Price.

Figure 2.3: Annual Avg. Adj. Closing Price

Source: own contribution with data retained from YahooFinance

Not long after its IPO in 2002, the share price had a downtrend until early October 2002 due to intense competition between the actors in the market. Afterward, the share price increased going forward to 2004 as a consequence of the company’s dominant position in the DVD-by-mail industry. Until 2009, the company had a relatively stable development in the stock price. However, from 2010 and onward, Netflix has had an exponential growth. The growth was mainly due to the investor’s positive expectations facing the launch of Netflix’s streaming service as well as the international expansion (Investopedia, 2016). Netflix had a substantial downturn in 2011 because of corporate mistakes. Announcement of

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increased DVD prices resulted in an adverse reaction from customers. Further, shareholders responded negatively to the announcement of splitting the Netflix into two separate companies leading to a withdraw of the plan soon after. It took the company around two years to get the stock price back to the all-time highs (Caplinger, 2016).

Onward from 2012, the share price proliferated, mainly due to further international expansion as well as the launch of Netflix original content in 2013. In 2015, the company demonstrated its pricing power by increasing its subscription prices while still retaining most of its customer base (Caplinger, 2016).

This increase resulted in Netflix delivering three times the consensus estimates, and the stock price increased correspondingly. In July 2015, Netflix announced a 7:1 split, becoming the second stock, after Apple, to ever split at this ratio. Investors reacted positively as the stock seemed more liquid, enabling smaller investors to buy in, and the stock price kept on increasing (Investopedia, 2016).

During the first half of 2016, the share price was affected by skeptic investors due to the enormous global expansion as well as lower subscription growth than expected from the quarterly report. Further, Netflix increased the subscription fee, which led to an adverse reaction on the stock price. By the end of 2016, investors’ expectations had improved, and the stock price reached an all-time high. The company significantly outperformed expectations in 2017, with higher subscriber growth than anticipated by management’s forecast, resulting in nearly 60 % growth in the share price in 2017 (Kalogeropoulos, 2018).

The company continued to have a massive growth in 2018, with substantial progress in subscription numbers as well as receiving 23 Emmy awards. The day after the Emmy awards the stock price increased 5 % (Castillo, 2018). Additionally, announcements at the end of 2018 about a further increase in the monthly fees in the US caused the share price to rise, but it fell soon after when the company’s fourth-quarter earnings report met investor’s expectations (Levine-Weinberg, 2019).

2.5 Competitors and peer group

Peer group analysis is a vital part of valuing a company, as it is essential to see how Netflix’s performance has evolved relative to its peer group. The constituents of the peer group should be similar to Netflix, particularly in terms of their primary area of business and market capitalization (Petersen & Plenborg, 2012). In this section, we will examine Netflix’s peer group, which will act as a benchmark in our analysis and the valuation of the company.

The market for entertainment video is severely competitive and subject to rapid changes. Netflix competes against other entertainment video providers, such as multichannel video programming distributors and internet-based content providers, including providers of pirated content, video gaming providers and DVD retailers. They furthermore compete more broadly with other sources

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of entertainment that customers could choose in their moments of free time. Lastly, they compete against entertainment video providers and content producers in obtaining content for their service, both for licensed streaming content and for original content projects. We will examine both the direct and indirect competitors in order to achieve a more detailed picture of the industry and the potential threats.

2.5.1 Direct competitors

Netflix operates in a market with several companies providing similar types of products to different markets. After examining the companies in the industry, we found the peers to be HBO, Hulu, and Amazon Prime Video, as these companies are most comparable to Netflix when it comes to the customer base, earnings, and product lines.

2.5.1.1 HBO

HBO is a subscription video-on-demand service operated by the American television network, Home Box Office (HBO), owned by Time Warner (Baumgartner, 2018). The service launched in 2015, and in 2018 HBO had a total of 144.7 million subscribers, with over 5 million subscribers in the US at the beginning of 2018 (Smith, 2018). The service provides on-demand access to HBO’s library of original programs, films, and other content, and HBO Now, which only serves the US market has a subscription fee of $14.99 per month (Welch, 2015).

2.5.1.2 Hulu

Hulu is a streaming service offering access to live and on-demand channels, original series, and films.

Hulu was established in 2007 and is owned by Hulu LLC, a joint venture with The Walt Disney Company, Comcast, and AT&T (WarnerMedia, 2019). In 2017, Hulu expanded by adding live news, entertainment, and sports from TV channels (Hulu, 2019). Hulu’s current business model, in contrast to that of Netflix, supplements cable television rather than replace it. As of 2019, Hulu has more than 25 million subscribers in the US (Ifeanyi, 2019). In contrast to Netflix, Hulu offers both ad-supported and commercial-free subscription. The ad-supported subscription costs $7.99 per month, whereas the commercial-free subscription costs $11.99 (Hulu, 2019).

2.5.1.3 Amazon Prime Video

Amazon Prime Video is an online video-on-demand service owned by Amazon. The service was launched in 2006 and offers films and TV shows for purchase or rent, and Prime Video, a selection of Amazon

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Studios original content and licensed acquisitions (Amazon, 2018). In some countries, Amazon Channels is offered, which allows viewers to subscribe to other suppliers’ content, including HBO in the US.

The monthly subscription fee is $12.99 per month, and Amazon Prime Video had 101 million global subscribers in 2018 (Reisinger, 2019).

2.5.2 Indirect competitors

Considering the indirect competitors of Netflix, there are infinite services available on the market. Since Netflix is an entertainment platform, it competes against other sources of free time entertainment.

These services range from online services like YouTube to TV channels, cinemas as well as video games.

YouTube is the world’s largest video-sharing site where users upload and share videos for other users to view (BrandTheChange, 2017). YouTube has recently including streaming of live events which has made the competition harder for Netflix (Bhasin, 2017). When YouTube shut down globally for a few minutes in October 2018, Netflix’s viewing and sign-ups spiked, indicating the major competition Netflix faces from YouTube (Patches, 2019). Furthermore, TV channels offer alternative sources of entertainment to the people who want to keep up with current trends and news around the world. The threat of TV channels triumphing potential Netflix streamers is especially heightened during political periods such as election time. Despite the rise of streaming services, the appeal of the cinema has not yet been eliminated. Many cinemas are offering a unique experience, with for example better projectors, upgraded seating to more comfortable recliners and sofas, complementing with selections of alcohol and food (Investopedia, n.d.). IMAX has maintained relevance in the video entertainment industry, by including the features mentioned above as well as 3D movies. Additionally, added physical features to the movies such as movements, smells, water, etc. is enhancing the experience of going to the cinema compared to online streaming at home. Lastly, from Netflix’s earnings report in 2018, they indicate that Fortnite is its biggest competition, where Fortnite is a famous battle royale video game.

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3 Strategic Analysis

The purpose of the strategic analysis is to identify important aspects of the company’s future cash flow potential and risks, enabling a forecast of key financial drivers. In a changing world, especially within such a rapidly changing industry as the streaming industry, it is vital to know the different circumstances influencing the industry as well as the company. In this strategic analysis, we will be using the theoretical models PESTEL, Porter’s Five Forces and VRIN. After the financial analysis, we will apply the SWOT model to summarize and highlight the results of both analyses, in order to clarify the drivers we will make use of in the forecasting.

Limitations with these frameworks are that it only provides a snapshot of the industry in the past. This might weaken the outcomes considering the industry is rapidly evolving, and trends like globalization and rapid technological advances. Furthermore, the definition of the industry might be a weakness as the company can straddle multiple sectors. However, we find the video entertainment the most suitable for Netflix, as it includes the telecommunication, media, and entertainment sector. We will only address the factors that we find valuable for forecasting the value of Netflix, and may, therefore, exclude factors that might be relevant for Netflix but not our analysis.

3.1 PESTEL

In this part of the strategic analysis, we will perform a PESTEL framework to analyze and monitor the macro-environmental factors that affect Netflix. We make use of the extended version of the framework, as the company is highly regulated by political and legal regulations towards their intellectual properties as well as environmental factors. It is fundamental to conduct a situational analysis of the external forces facing an organization, in order to evaluate how well the organization can differentiate themselves from the competition and create a competitive advantage (Jurevicius, 2013). We will concentrate on the US market in some of the section considering this is currently the biggest market for Netflix.

3.1.1 Political and legal factors

Political factors determine the extent to which government policy may affect a company or a specific industry. The political factors include circumstances like political policy and stability as well as trade restrictions, fiscal and taxation policies. Legal factors concern what is legal and allowed within the territories that the industry operates. The legal factors include employment legislation, consumer law, health, and safety, international as well as trade regulation and restrictions (Jurevicius, 2013).

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3.1.1.1 Net neutrality

Net neutrality is highly essential in the video entertainment industry because it affects the infrastructure.

Net neutrality is an open-internet protection principle where Internet Service Providers (ISPs) should treat all data equally and not differentiate or charge differently based on user, content, website, platform, application, type of equipment, or method of communication (Gilroy, 2011). Hence, companies are not allowed to make special arrangements to achieve, for example, better bandwidth speed. ISPs are middlemen who build and maintain the fiber optic cables and satellites that allow consumers to connect with Internet Content Producers (ICPs), like Facebook and Netflix (Feldman, 2017).

The main issue with net neutrality is how the Communication Act of 1934 should classify ISPs. They can either be classified as Title I “information services” or Title II “common carrier services.” The classification affects the Federal Communication Commission (FCC) authority over ISPs because the FCC would have a significant ability to regulate ISPs if classified as Title II, but little control over them if classified as Title I (Sommer, 2015).

Net neutrality in the US has been a conflict between network users and service providers since the 90s, where most of the conflict arises based on how internet services are classified by the FCC (?). In 2015, Under the Obama administration, FCC adopted rules to protect net neutrality and issued the Open Internet Order which reclassified ISPs as Title II services, giving them authority to enforce net neutrality. As a part of the Trump Administration in April 2017, FCC chairman, Ajit Pai, proposed to reverse the neutrality policies, returning to the previous classification of ISPs as Title I services. FCC voted in favor of repealing the order, which went into effect in June 2018, despite efforts in Congress to retain the 2015 Open Internet Order. As a result, over 20 states launched a joint lawsuit against the FCC, while California created its own state-level net neutrality law which is being challenged by the federal government (Collins, 2018).

As a result of no net neutrality, the industry may face insufficient competition regulations, and it may further lead to monopoly conditions. ISPs may have competitive advantages if they own their ICP, such as Comcast who owns NBC Universal or AT&T who is entering the streaming industry in 2019, where they can favor access for their benefits (MarketWatch, 2007). This matter will be discussed further in Porter’s five forces. However, Netflix (ICP) might pay Comcast (ISP) to guarantee that Comcast customers can stream its movies at full HD resolution, giving Netflix a competitive advantage (Matzko, 2018). How the laws around net neutrality evolves in the coming years will therefore profoundly affect the competition in the market since several ISPs are already in the competition or are entering in the following years.

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3.1.1.2 International regulations

Many of the actors in the streaming service operate internationally, which can lead to several challenges considering countries may have laws and regulations that prevent the growth of streaming services.

Months after the company’s global expansion in 2016, Netflix was facing problems in several major Asian markets. In Indonesia, the country’s largest internet service provider, PT Telekomunikasi Indonesia Tbk, blocked all content on Netflix, because it had concerns about the content Netflix was offering and accused Netflix of not having a necessary business permit. They meant the content displayed violence and adult content, which was against the country’s rules. Indonesia is one of Asia’s most populated countries with around 250 million people (Kelion, 2016). As a result of this and other issues from the international expansion, Netflix suffered an operating loss of 104.2 million dollars for streaming video outside the U.S in the first-quarter of 2016 (Pak & Danubrata, 2016).

As of 2019, Netflix is available in more than 190 countries worldwide. However, the streaming company is not available in the world’s largest market, China. Netflix is not operating in China because of regulations within the country. In China, one need specific permission from the government to be able to operate, and the country has strict rules dictating the distribution of content. These regulations include heavy censoring of content and China limit foreign content to 30 % of a series or movie, which eliminates most of the content on Netflix. Further, Netflix also faces fierce competition from domestic streaming services in China, where many of these streaming services have close ties with, or even funding from, the government (Greenberg, 2016).

Europe is an essential market for Netflix. At the beginning of 2017, the EU Parliament voted to remove geo-blocking and other geographically-based restrictions that undermine online shopping and cross-border sales. The regulation was implemented in December 2018, and before this regulation was put in motion, it was impossible to get access to international content, which for Netflix, resulted in a variable content library for different countries (Esteana, 2015). With the new international regulations, customers can travel around Europe without online content changing. For Netflix, this will lead to a more extensive content library for the customers, higher customer satisfaction and eventually more subscribers. Furthermore, this might help to make legal services more attractive than illegal services.

3.1.1.3 Piracy growth

Piracy is a remaining issue for streaming services like Netflix. BitTorrent is a file sharing protocol, which is used to distribute data and electronic files over the internet. It is one of the most common protocols for transferring large files, such as digital video files containing TV shows (BitTorrent, 2019).

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After years of steady decline, BitTorrent usage is once again growing. In 2015, BitTorrent’s share of upstream traffic on fixed broadband networks in North America had dropped to 27 % from 52 % in 2011. The drop was mainly a result of rising quality and inexpensive streaming alternative to piracy.

However, the trend is now reversing slightly, where BitTorrent’s traffic share is repeatedly growing worldwide.

The growth has especially been significant in the Middle East, Europe, and Africa, where BitTorrent in 2018 accounted for 32 % of all upstream network traffic. The main reason for the rise has been exclusivity in streaming content, where an increasing number of sources are producing exclusive content available on a single streaming or broadcast service. For example, Game of Thrones for HBO, House of Cards for Netflix, The Handmaid’s Tale for Hulu and Jack Ryan for Amazon. As it is expensive to subscribe to all of the online streaming services, it is common to subscribe to one or two of the services and pirate the rest (Bode, 2018b). This is especially true overseas, where geographical viewing restrictions limit access to popular US content.

3.1.1.4 Password sharing

Password sharing is a concerning issue within the streaming industry since it allows several people to share one account. According to the research company Magid, password sharing is practiced by more than a quarter of millennials. Moreover, research firm Parks Associates predicts that 9.9 billion dollars of pay-TV revenues and 1.2 billion dollars of revenue from subscription-based streaming services will be lost to password sharing each year (Cuthbertson, 2019).

As of 2016, a survey estimated that 65 % of Netflix users share their account with one other person, while 19 % of users share their subscription with three or more people (Archer, 2016). By limiting the possibilities for password sharing, the streaming services would be able to increase their subscriber numbers. The UK-based Synamedia unveiled their artificial intelligence software at the CES 2019 technology trade, which is said to solve the issue and save the streaming industry billions of dollars.

The technology tracks and analyses the activity of a subscriber and informs the operator if there are any unusual patterns. It is confirmed that several pay-TV operators are testing the technology (Cuthbertson, 2019).

3.1.1.5 Taxation of the streaming industry

Digital Goods and Services Tax Fairness Act of 2018 established a national framework for how states should apply their sales and use tax systems to sales and uses of digital good and services (Kranz et al., 2018). Taxation of the streaming industry for users has long been an essential discussion, especially in

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American politics. Traditional cable TV is taxed, whereas streaming services are not taxed as for now.

Cable TV companies are not the only ones who are suffering from this practice. American cities and states correspondingly lose income as the streaming industry has increased profoundly in the last years.

American cities and states have started introduction taxes for the usage of the internet to compensate for the income loses. In 2015, Chicago was the first big city to introduce a 9 % taxation on digital amusements services, including concert, sporting events, music, video, and gaming (Avalara, n.d.).

Streaming services are consequently dependent on the state-specific regulations of taxes, and potential changes in taxation may have a massive impact on the income stream for companies like Netflix.

3.1.2 Economic factors

The economic factors cover how the evolution in the national and international economy is affecting the video entertainment industry and its profitability.

3.1.2.1 Exchange rates

Netflix is currently operating in over 190 countries worldwide, which means that the company is widely exposed to fluctuating exchange rates. The company aims its pricing around 10 dollars for a basic monthly subscription. However, within certain markets this can be as high as 19 dollars due to exchange rates and VAT. In some countries, the exchange rate moves Netflix into a luxury purchase which could negatively affect the demand from the “price-conscious” segment. In 3Q15, Netflix’s average monthly revenue for its international streaming segment was 7.56 dollar per member, this was a 10 % decline from 3Q14, illustrating the significant impact the exchange rate has on the revenue (Pelts, 2016).

The USD has the last five years been relatively stable, with a downward trend in 2017 followed by an upward trend in 2018 and beginning of 2019 compared to the most important European currencies, namely EUR and GBP. At the end of 2018, international streaming accounted for 58 % of the total average paid streaming memberships, and the international market is expected to continue expanding in the future. This fact indicates that Netflix’s exposure to exchange rate risk is high, as a small change in the currency can have a significant impact on the revenue stream. Furthermore, Netflix does not use foreign exchange contracts or derivatives to hedge against any fluctuations in foreign exchange rates, which exposes Netflix to even more risk (Netflix, 2018).

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3.1.2.2 Corporate tax rate

In 2018 the US government changed the corporate tax rate from 35 % to 21 %. However, the effective tax rate for companies is often lower because of different deductions concerning for example financial expenses. The average tax rate for US technology firms in 2017 was only 16.9 % (Gittleson, 2018).

Aforementioned is beneficial for corporations as the lower corporate tax rate reduces the cost of capital, which enables more investments and hence increased capital stock. The American corporate tax rate is now on the line with the OECD average corporate tax rate (York, 2018).

3.1.2.3 Product placement

In the streaming industry, only Hulu offer a cheaper version of its service with ads. Thanks to Netflix, Amazon, HBO, and other "commercial-free" TV services, people are moving away from shows with ad breaks, and according to a survey, 23 % of Netflix subscribers said they would drop the service if they started running ads (Martin, 2019). However, it has become more common to use product placement as a marketing tool within the industry. By 2019, the product placement spending is predicted to be 11.44 billion dollars in the US, which is a substantial increase from 4.75 billion dollars spent in 2012 (Statista, 2019a).

Stated by Greg Isaacs, chief product and marketing officer at product integration firm Branded Entertainment Network, more than 70 % of Netflix shows have at least one product placement. Further, Amazon Prime is placing product advertisements in almost all of its shows. According to Isaacs, brands pay between 50,000 and 500,000 dollars per episode on Netflix or Amazon Prime. However, it is uncertain exactly how much money Netflix and Amazon earn from product placements (Nadeem, 2017).

Aforementioned can be a further opportunity for the streaming services in the future, and Netflix has the opportunity to make use of this in their interactive shows.

3.1.3 Social factors

Social factors focus on the social environment and include changes in trends, cultural factors, and consumer behavior. It is essential to evaluate these factors in order to understand customers’ needs and preferences.

3.1.3.1 Cord-cutting

Cord-cutting is a growing trend that is adversely affecting the cable industry. Cord-cutting refers to the process of cutting expensive cable connection in order to change to low-cost TV channel subscription

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over the internet. The cord cutting concept became known at the beginning of 2010 as more internet solutions became available (Techopedia, 2012).

As of 2019, 14 % of US homes participate in the cord-cutting trend which is a 48 % increase over the last eight years (Cohen, 2019). CNBC’s survey from 2017, shows that 57 % of Americans have a streaming service, where 51 % of American streamers subscribe to Netflix (Liesman, 2018). The demographic profile of US cord-cutters shows that the phenomenon extends to all age groups and all income groups. Across income, households with lower incomes are most likely to have disconnected their pay-TV services, with nearly 60 % of cord-cutters having a household income below 50,000 dollars and nearly 30 % having a household income below 25,000 dollars. However, 10 % of cord-cutters has a household income exceeding 100,000 dollars, suggesting that price is not the only aspect explaining the trend (Masoero & Mishra, 2016).

3.1.3.2 Original content

Simultaneously as more people are cutting the cord, the making of exclusive original content has evolved among streaming services. Netflix’s original content has been gaining more viewing among the subscribers, where 37 % of US desktop viewing in November 2018 was from original content on Netflix, up from 24 % in November 2017. Netflix’s originals are competing with licensed TV classics, and six out of the top 10 most-watched shows on Netflix were original content. As the competition increases in the future, Netflix will have to rely more on original content (Hale, 2018). The steady incline in the viewing of Netflix’s original content makes this shift easier for Netflix, and the increased popularity for original content is a great opportunity for Netflix. However, other streaming services are also focusing on producing original content, resulting in an increased rivalry between the streaming services to produce the most exceptional shows.

3.1.3.3 Binge racing and Binge watching

Binge-racing is Netflix’s term for someone who watches all episodes of a new show within 24 hours. This phenomenon is a new trend that has emerged in the streaming industry, and Netflix has announced that 8.4 million subscribers binge race. Over the last four years, the number of people binge-racing has grown more than 20 times (Morris, 2017). Netflix has made it easy to both binge race and binge watch (watching several episodes in a row), by automatically playing the next episode, and by allowing the subscribers to skip the introduction. This trend has brought a competition element into the watching and has increased engagement for the subscribers.

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Figure 3.1: MilleXZials exhibit stronger binge-watching behaviors

Source: Deloitte Digital media trends survey, 12th edition

Table 3.1: Media consumers divided into Five Generations

Generation Gen Z Millennials Gen X Boomers Matures Year of birth 1997-2004 1983-1996 1966-1982 1947-1965 1946-prior

Figure 3.1 displays the binge-watching behavior of the five different generations presented by Deloitte in their Digital Media Trends Survey, 12th edition. Table 3.1 presents more in-depth details about the five generations. The graph shows that binge-watching is most popular for the youngest generations, being the ones that watch the most episodes during a binge-watching.

3.1.3.4 Internet users and time spent on digital video

Gen X and especially Boomers continue to spend a significant amount of time watching traditional TV.

However, the number of Millennials who watch traditional TV has declined. At the same time, the Millennials are increasingly watching more online video, even outnumbering those who watch traditional television.

Digital video is the most time-consuming digital activity among adults, representing 1 hour and 26 minutes of daily media time, an increase of 9 % since 2017 (McNair, 2018). According to the analysis done by Streaming Observer, the average Netflix user spends 1 hour and 11 minutes each day streaming.

In all age groups, the percentages of Americans using the internet to access TV content has increased over the years, whereas 87 % in the age group 18-24 and 90 % in the age group 25-34 use video streaming, being the two largest age group (Richter, 2017).

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Additionally, there has been a substantial change in TV viewing habits over the years. Viewers who stream programming rely more heavily on recommendations than in the past, for both learning about and deciding which program to watch. Word of mouth recommendations and data-driven recommendations through SVOD (subscription video on demand) services have become more crucial among Millennials in discovering and navigating through content (Xstream, 2015).

3.1.4 Technological factors

Technological factors focus on how innovation, research, and technological development could affect a market or industry. Factors could include changes in digital or mobile technology, automation, research and development (Jurevicius, 2013). In the streaming industry, technology is an essential factor in order to succeed. Technology has a significant impact in regards to several factors including product attributes, resources, competencies, competitiveness, and performance. The technological development within the industry is very dynamic, and the competition is massive.

3.1.4.1 Streaming capacity and quality

In 2018, Netflix re-encoded its entire catalog, to produce pictures using the smallest amount of bandwidth.T his design allows customers with 4GB data to increase their streaming to 26 hours of Netflix content per month, an increase from just 10 hours before. These improvements are especially crucial for developing areas where Netflix is trying to expand, particularly in Africa, Southeast Asia, and South America. DAMTech, now owned by Disney, is the first to stream in 60fps and 4K, and its technology powers streaming services like HBO Go, WWE Network, and MLB.tv (Alvarez, 2018).

Netflix focuses heavily on content quality by shooting its content in 6K, even though the picture is in 4K right now. Netflix has similarly been a big proponent of high dynamic range, which delivers more vibrant colors and deeper blacks (Mano et al., 2018). However, all content needs to be at a high quality, independent of whether users are watching on an iPhone X, Galaxy S9 or an older, entry-level smartphone. The streaming companies must present the same experience and capability across a wide variety of devices.

3.1.4.2 Automating the production

Digitizing of the production has been a technology development within the industry resulting from the streaming companies producing exclusive content. Netflix has with the help of an app called Move, simplified aspects of the production process, like crew management and scheduling shoots (Alvarez, 2018). Ultimately, Netflix envisions that these apps will be used by tens of thousands of people, both

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employed by the company as well as third-party vendors working on Netflix production around the world. The production has been a significant challenge since the business of content creation is very slow to adapt to technology production (Shankar, 2018). However, by making the actual production processes as easy as possible, Netflix can maximize the amount of creative output.

3.1.4.3 Translation system, HERMES

Netflix has furthermore built HERMES, the first online subtitling and translation test, and indexing system. It is a platform which allows individuals with a background in subtitling to contribute to captioning a variety of media from Netflix’s library. The software automatically grades the translation, making it easy for Netflix to find the best translators. Netflix developed the platform because they were previously relying on third parties for subtitling, but due to differing methods of assessment by its subcontractors, they could not maintain the same standard of quality across the different languages (Blog, 2017). This innovation has resulted in faster and higher quality translation efforts for Netflix to

serve its programming to its 190 countries.

3.1.4.4 Recommendation system

An increasing trend in the streaming industry is the recommendation system. Netflix personalize what customers watch through gathering data on their preferences. Netflix runs 250 A/B tests each year where they test users with two slightly different experiences to see how they respond. The experience can vary from changes to the way the Netflix player looks or the mechanisms by which people find shows. The streaming company also have multiple different landing cards, which is the images that are shown for each of its titles as people scroll through shows, where the purpose is to find the most popular options. Perhaps the biggest personalization on Netflix is the rows of shows a user is presented with, which is primarily based on watching history. More than 80% of the TV shows and movies watched on Netflix are discovered through the platform’s recommendation system (Blattmann, 2018).

On average a person views 40 to 50 titles before they pick a show or a movie, and people are profoundly affected by the personalization of shows shown. Netflix’s algorithms will occasionally resurface customers unfinished shows to tempt them back. Netflix further personalize its recommendations based on when, where and how customers are watching. They may, for example, be presented to shorter programs when they log in late at night and may not be looking to watch an entire show from the beginning (Burgess, 2018). Engineers say they could potentially apply the same method to the short descriptions of each title or even trailers, making it even easier to attract the customers to watch shows and movies (Schneck, 2019). Recommendation engines are compelling personalization tools because it is a unique

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way of showing people items they will like, but are unlikely to discover by themselves. Other companies in the industry, like Amazon Prime Video and Hulu, are also using recommendation systems, but Netflix’s recommendation system remains the most complex.

3.1.4.5 Virtual reality and interactive television

Virtual reality (VR) and augmented reality have quickly become a popular topic across several industries.

According to a report from Zion Market Research, the global VR market expects a valuation of more than $26 billion by the end of 2022. With the emergence of technologies like Facebook 360 and YouTube 360, consumers can interact with content through human experiences. However, Netflix has not focused on VR after they in 2015 introduced a 360-degree app that lets users step into a virtual room to watch movies or TV shows (Shaffer, 2018).

Despite a deficient focus on VR, Netflix has begun to produce content which is two-sided through interactive television. In June 2017, Netflix released the animation for kids “Puss in Book,” allowing viewers to pick between different endings of the same show. Further, in 2018, they released an episode called “Bandersnatch,” unveiling an extended 90 minutes episode of the British TV series “Black Mirror”

to showcase the new technology. The technology allows users to choose how an episode will develop, as different storylines options are presented throughout the viewing (Bradley, 2018). Netflix plans to introduce more engaging content in the future (Prahl, 2019). So far, interactive television is mostly used in the video gaming industry, and it is uncertain how it will develop within the streaming industry.

3.1.5 Environmental factors

Environmental factors relate to the influence of the surrounding environment and the impact of ecological aspects. With the rise in importance of Corporate Sustainability Responsibility (CSR), this element is becoming more critical (Jurevicius, 2013).

Vast amounts of energy are needed to keep data flowing on the internet and demand will only increase as our reliance on digital services grows. Some of the energy is generated from clean energy sources, but most of it comes from burning carbon-based fossil fuels, which scientists believe is contributing to raising the global temperatures. The entire information technology sector, from powering internet servers to charging smartphones, is already estimated to have the same carbon footprint as the aviation industry’s fuel emissions. Streaming video accounts for the most significant part of the world’s internet traffic and watching video online at home can be compared to having two or three old incandescent light bulbs on. Further, as well as the power used by these devices, energy is consumed by the networks that distribute the content. Therefore, more demand for technology means a higher requirement for energy.

Valuation of User-Based Firms