The Battle of YouTube, TV and Netflix

Budzinski, O., Gaenssle, S. and Lindstädt-Dreusicke, N.

Budzinski, O., Gaenssle, S. & Lindstädt-Dreusicke, N. The battle of YouTube, TV and Netflix: an empirical analysis of competition in audiovisual media markets. SN Bus Econ 1, 116 (2021). https://doi.org/10.1007/s43546-021-00122-0

(Full length article modified to provide excerpts.)

Introduction

The consumption of audiovisual content is rapidly changing. While traditional television (TV) still dominates the consumption of audiovisual contents of an older age audience, the younger ages already devote more time to consuming audiovisual contents via online streaming services and video portals, such as Netflix or YouTube (also referred to as video-on-demand; VoD). This development is also driven by an increased use of mobile devices, such as smartphones and tablets, allowing for considerably enhanced options of consuming audiovisual contents in not only the living room at home but also virtually everywhere and every time. User figures and viewing numbers from various countries show that particularly younger generations extensively use portals such as YouTube and watch online streaming services such as Netflix, whereas older age groups (50 + years) significantly less switch on these services (see, inter alia, for Germany Lindstädt-Dreusicke & Budzinski 2020, for Scandinavia Audience Project 2019, for the UK Fisher 2019, and for the US Richter 2019). At the same time, traditional TV is not only relatively stronger with the older population (e.g., due to a lack of mobile consumption of non-TV contents, such as YouTube videos) but also in absolute terms. In 2019, the average daily viewing time of TV in the 50 + age groups amounted to 318 min per day, whereas the 30–49 years watched 176 min per day and the 14–29 years only 82 min per day. In addition, consumption time in the older age group slightly increased, whereas it decreased in the younger age clusters, particularly within the 30–49 years (− 18 min per day compared to previous year) (Statista 2020). Thus, the figures do not allow disentangling how much of the dynamics results from complementary services in the mobile online world and how much from viewers abandoning traditional TV and switching to various VoD formats.

The currently relevant online services differ in terms of business models from both traditional TV and from each other. In terms of business models, advertised-financed streaming services (AVoD; e.g., YouTube) can be distinguished from paid-for (by users) streaming services (PVoD; e.g., Netflix) (Lindstädt-Dreusicke & Budzinski 2020). It is possible that streaming services mix these models (i.e., hybrid models, such as Spotify is doing in respect to audio streaming services). Obviously, business models will develop and change along with the high dynamics of the markets in question. Despite the differences in content, business models and treatment by available empirical studies, at the end of the day, all of TV, AVoD and PVoD are offering audiovisual contents to the consumers. In the light of the increasing importance of online streaming services vis-à-vis traditional TV, therefore, the questions arise whether relevant competitive pressure between the services (in our study represented by YouTube, Netflix, TV) exists.

Theory: competition among different channels of audiovisual content

The ongoing process of digitization and the spread of broadband internet technology considerably increased the option for consumers to watch moving audiovisual contents. That traditional TV—irrespective of its transmission media (terrestrial, cable, satellite, online, etc.)—is now facing video-on-demand services changes the competitive landscape. This may be good news, since in many national television markets (including Germany), concentration and (a lack of) competition have been continuous concerns (Budzinski & Wacker 2007; Bundeskartellamt 2011a, 2011b, 2015; OFCOM 2018). However, the competitive interrelations between TV and VoD as well as among different types of VoD services are subject to controversial discussionFootnote 3. Thus, what are the theoretical reasons about factors influencing the competitive interrelation of different channels transmitting audiovisual contents (TV, different types of VoD)?

Fundamental differences in content

Fundamental differences in the type of content that is broadcasted may limit the intensity of competition between Netflix, YouTube, and TV. An often-raised objection claims a service such as YouTube (AVoD) does not compete with the likes of traditional TV and PVoDs, such as Netflix, because its content is predominantly non-professional and/or non-commercial (inter alia, Bruns 2008; Ritzer & Jurgenson 2010; Bundeskartellamt 2011a, 2015; Dennhardt 2014; Fuchs 2014). According to this view, YouTube mainly represents a social media platform, where users upload content for other users (cat videos, fail videos, etc.), i.e., a sort of user-exchange of contents, and professional contents from business companies are in the clear minority. The nature of YouTube’s early ‘user generated content’ (from users for users) has changed a lot and initial ‘private’ uploaders professionalized towards being active content providers, offering regular video uploads regarding specific topics according to the channel’s media concept (Döring 2014; Budzinski and Gaenssle 2020). Notwithstanding the still existing type of non-professional content, this trend of professionalization points towards the significant turnovers and revenues that content providers such as so-called social media starsFootnote 4 earn through participation on YouTube’s advertisement revenues as well as through product placements—with the latter further emphasizing the commercial nature of the content supply (Budzinski and Gaenssle 2020; Gaenssle and Budzinski 2021). Nowadays, a significant share, if not most of the views on YouTube, fall on commercial content, most of which is professionally produced; the most popular 20% receive 97% of views (Ding et al. 2011) and 10–30% of videos have fewer than ten views (Chowdhury & Makaroff 2013).

A related aspect refers to content differences in terms of the extent of exclusive and/or original content. While this used to be a domain of traditional television, Netflix and Amazon Prime Video for instance, as well as new players, such as Disney + and Apple TV + , aim at attracting their audience especially with original (own produced) or exclusive content (e.g., Netflix with House of Cards or Orange is the New Black) (inter alia, Aguiar and Waldfogel 2018; Benes 2019).

Content differences corresponding to different purposes of usage

Content differences between the different types of services that relate to different consumption purposes represent a second aspect. While YouTube is known to predominantly provide shorter videos (e.g., short clips, music videos & social media star entertainment), both Netflix and TV focus on longer pieces, such as movies, series, and shows. These content differences may go along with different ways of consumption. For quick information (specific tutorials/help, etc.) or social network elements (i.e., follow stars or friends, sharing content), YouTube meets the consumers’ preferences, whereas for full-length video content the choice falls on the other types of services. Therefore, YouTube may be more relevant for purposes, such as bypassing waiting or traveling times, covering smaller breaks and shorter entertainment spaces, etc., whereas PVoDs, such as Netflix and TV, are preferred for filling an evening of entertainment or a free Sunday afternoon, for instance. As such, the two service types would rather complement each other than compete with each other. These differences in contents and consumption could reflect in service usages different times of day: Netflix and TV should be the prime-time competitors according to this view, whereas YouTube is more a media for “in-between” moments throughout the rest of the day. However, with the professionalization of AVoD content, average video length is developing towards traditional video formats. A study conducted by the search engine Pex (Turek 2019) shows that average YouTube videos are 11.7 min long (December 2018), with popular categories reaching up to 25 min on average (gaming 24.7 min; film & animation 19.2 min). Moreover, serial consumption of videos and so-called binge watching (Rubenking et al. 2018; Gaenssle & Kunz-Kaltenhäuser 2020) allows consumers to watch hours of video content without interruption—a phenomenon that is further fueled by individualized recommendation systems and auto-play modes (for instance, for music videos).Footnote 5 Independent of the single video length, this may result in hours of successive consumption; accumulating to a total consumption length, which is easily comparable to full-length movies. These developments show converging trends and increasing comparability of services.

Linearity, devices, and social network elements

VoD, in general, differs from TV in that there is no fixed program schedule as a take-it-or-leave offer for consumers. Instead, VoD consumers can watch all available contents whenever they want and compile their “program” by themselves. The media literature calls the schedule-bound service linear and the on-demand type non-linear (inter alia, Berman et al. 2009; Kazakova & Cauberghe 2013; Steemers 2014; van den Bulck & Enli 2014; Simons 2015; Enli & Syvertsen 2016). A further difference may relate to the device of usage. One expects consumers of traditional television programs or Netflix (PVoD) to prefer large television screens, while YouTube-style AVoD services are mostly watched on mobile devices (laptops, tablets and, particularly, smartphones). However, due to the possibility of downloading content to mobile devices and watching it ‘on the road’, consumers may start to watch their favorite shows—regardless of the original service (AVoD, PVoD or TV)—while, e.g., traveling to work. Eventually, social networking elements, such as commenting, sharing or liking content, may represent a differentiator. This social media function is usually not possible for linear TV, although broadcasters recently started to increase audience engagement, e.g., in live shows with audience questions or the possibility of writing (WhatsApp) messages. Nevertheless, due to the nature of the non-linear availability of content, audience ratings, comments, and shares are possible on AVoD and PVoD. Especially AVoD services such as YouTube or Twitch entail networking elements and active ‘below video commenting behavior’. However, former non-digital players in the market also adapt to new possibilities and try to increase audience engagement.

The economics of attention

Overall, the different services seem to converge and try to use all possible ways to increase the time recipients spent consuming their content. Attention may be a scarce resource and, in the face of information overflow due to omnipresent mobile access to the internet, a relevant one for online content consumption (Falkinger 2008; Anderson and da Palma 2012; Evans 2013; Boik et al. 2017; Gaenssle 2021). According to the economics of attention, all content providers compete for the scarce attention of the users who can spend every minute of their attention only once. Therefore, if a user opts for watching YouTube videos, she cannot spend this attention to a Netflix serial anymore and vice versa (opportunity costs). Given that many users spend a relevant time of any day for working, sleeping, and other activities (childcare, sports, etc.), competition for the remaining time for watching audiovisual online content may be intense. Furthermore, even though there are differences in detail, a large part of content and consumption regarding all three types of services is about entertainment and, thus, referring to the same underlying intention or want of the consumer.

From this theoretical perspective, the case for TV and Netflix-style services being in competition with each other appears to be straightforward. In a way, services such as Netflix may be viewed to take the place of TV, entailing the advantages of traditional TV and adding the luxury to be non-linear, so that users do not depend on a given program schedule anymore, but can cherry pick their times and contents (Tefertiller 2018; Budzinski and Lindstädt-Dreusicke 2020; Fudurić et al. 2020). Therefore, it may mainly be a generation effect separating the two types of services with older generations just being slower to adapt to a superior new good (Lindstädt-Dreusicke and Budzinski 2020).

However, while enhanced choice options will mostly benefit consumers’ preferences, there can be exceptions to that. Choosing does require investing cognitive capacity and in some situations in life—like the end of an exhausting day, where someone just looks for some relaxing entertainment before going to sleep or background entertainment without active engagement (like radio consumption is often done)—users may not want to spend cognitive resources on low-involvement routine consumption (Vanberg 2002; Budzinski 2003). Then, a linear service such as TV may be superior, since it demands less cognitive engagement and decision effort.Footnote 6 Moreover, regular television consumers might enjoy the feeling of being connected to society, watching what other people nationwide are also watching, i.e., networking and commonality effects as well as cultural inclusion by, e.g., national popular TV shows. Finally, the bundling of information and entertainment, e.g., news and prime-time movie as a bundle, may be valued by consumers, and be very tiresome to self-compile (or even impossible due to lack of supply) on PVoD and AVoD.

Notwithstanding, the newer services entail a tool that may serve a similar purpose. The algorithm-based recommendation service of Netflix, YouTube and others, may substitute for the linear program schedule in cases of routine and low-involvement consumption. Based on individual data, recommender systems provide content suggestions for (indecisive) consumers. To simplify the demand-process and lower the cost of active consumption decisions, services use auto-play modes (immediately starting the next video), content suggestions, trailers, etc. (see for a detailed analysis Budzinski et al. 2021).

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