Abstract
This article explains how Netflix has transformed the ways in which we interact with media in the contemporary milieu. I argue that Netflix works through a process of planned differentiation, designing unique customization experiences to create a new type of media user that participates in its global and regional release and production strategies. This leads me into a discussion of how the Netflix interface manages the spectators’ experience through a series of connected features. Thus, I detail Netflix’ personalization mechanisms, proposing that, ultimately, its users ‘pay to buy themselves’, or the version of themselves its interface offers back to users upon systematically gathering data on their habits. Finally, I remark that the key characteristics of the current streaming service/spectator relationship are deceptive limitlessness, customization, the automation of content flow and ubiquity, weaving a form of audiovisual engagement that has partially and, at times completely, conquered our everyday.
The envisioned result would seem to be a prime case for flow- a steady stream of programming designed to stay in touch with our changing rhythms and moods, selected and accessible with no effort on our part, anticipating our every interest (…) and nearly infinite in its capacities.
Introduction
When I teach my American cinema course in Spain, I often recommend films to my students, encouraging them to gain knowledge about materials we don't have time to discuss in depth. Their default answer to my suggestion is particularly significant: ‘I’ll check if it's on Netflix’. They do not say that they will check if it's available on a streaming service, in more general terms, or on HBO, or perhaps on Disney +, Sky or Amazon Prime Video. They do not say either that they will try to find a particular film online and download it or stream it from a non-official site, like many students used to do five or ten years ago. Their go to choice is consistently Netflix. Thus, this service has become my students’ primary method to identify streaming services in the contemporary era. In other terms, the brand itself has turned into the categorizing tool to account for one of the dominant forms of media consumption today.
Furthermore, Netflix has become part of the day-to-day speech. In the early 2010s, the phrase ‘Netflix & Chill’ became a synonym of ‘staying home and relaxing’. Soon thereafter, an additional transformation occurred since the expression turned into an equivalent of ‘come over, will watch a movie and will hook up’, especially amongst teenagers (Pilipets, 2019). Seizing the moment, Netflix appropriated the expression and brought it to the fore through its Twitter account. Consequently, this catchphrase entered the mainstream. From then on, users have repeatedly deployed it, creating and spreading contents through social networks with a variety of purposes and inflections. 1 Not surprisingly, an entrepreneur sought to monetize this concept, creating the ‘Netflix and Chill’ condoms, which are still available for sale today (McDonald, 2015). Moreover, in 2020, Ben & Jerry's picked up this trend and launched the ‘Netflix and Chill’d’ flavor in collaboration with the streaming platform (Groce, 2020). On the ice cream company's site, the description of this flavor reads: ‘There's something for everyone to watch on Netflix & flavors for everyone to enjoy from Ben & Jerry's’ (Ben & Jerry’s, 2020). Joining forces to design a combined experience, Netflix and Ben & Jerry's promise to deliver the perfect mise-en-scène for a shared or individual occasion in front of a digital screen. These two companies capitalize on the universal appeal of both brands—a flavor or a show / movie for everyone, respectively—to convince consumers they offer all that is necessary. Hence, Netflix and Ben & Jerry's have strategically arrogated a figure of speech that emerged from the day-to-day interactions of social media users to re-purpose their brands and increase their visibility. In addition, as Napoli (2016b) remarks, upon Netflix's success, companies launching diverse digital content delivery services advertised their products as the ‘Netflix for eBooks’ or ‘The Netflix for magazines’ etc., signaling the streaming service's impact in the cultural and social panorama.
To sum up, Netflix has become part of the everydayness of a significant part of the global population, especially within digital realm. This feat was not enough. Famously, Netflix CEO Reed Hastings stated that Netflix's true enemy was sleep (Sulleyman, 2017). Subsequently, the company's US Twitter account published the following tweet: ‘My Enemy Is Sleep’, incorporating this mantra to its marketing strategy. Hastings’ statement fundamentally points to the ideal customer Netflix attempts to construct: a user who stays connected to the service, day or night, in motion or on a couch, on a tablet, a television set or a cell phone, awake or asleep.
In quantitative terms, the reach of Netflix is paramount. It expanded to 243 territories in January 2016, becoming almost global with the notable exceptions of China, North Korea and Syria (Aguiar & Waldfogel, 2017). By April 2020, Netflix had reached 182 million subscribers worldwide (Alexander, 2020), more than double as compared to the 70.84 million it had in 2015 (Statista, 2019). In the last year, it has added 10 million subscribers reaching over 190 million (Zeitchick, 2020). In Latin America, today it has 34.3 million subscribers, more than five times than its closest competitor, Prime Video (Pimentel, 2020). Besides, Netflix has over 14 million subscribers in Australia, 12.5 million in the UK, 8.1 million in India and 4.2 million in Japan, weaving a global network with unparalleled penetration (Iqbal, 2020). Consequently, even though Netflix is facing strong competition with Disney + and other streaming services, it is still the world leader. In addition, in the last few years, Netflix has increasingly prioritized its own content. While in 2017 it spent 8.9 billion dollars in original content, this number reached 12.04 billion in 2018. In 2019, Netflix spent an estimated 15 billion (Spangler, 2019); in 2020 and 2021, this figure reached more than 17 billion (Low, 2021; Spangler, 2020). This signals Netflix's attempt to build a robust and heterogeneous catalog it can fully control from beginning to end.
This article explains how Netflix has transformed the ways in which we interact with media in the contemporary milieu. To approach Netflix’ functioning within the streaming panorama, in the first section, ‘Streaming in Context: From Previous Media to Netflix’ Planned Differentiation’, I engage with the works of a wide range of scholars who have attempted to define streaming services within the broader mediascape. In this regard, I relate Netflix to other, pre-existent, media practices such film and television viewing, video rentals and non-official streaming/downloading. Then I explain how Netflix has altered the audiovisual landscape by evolving into a vertically integrated company that has challenged established production and distribution processes. I argue that Netflix works through a process of planned differentiation, designing unique customization experiences to create a new type of media user that participates in its global and regional release and production strategies. Subsequently, in the next section, ‘Netflix and the Algorithm’, I situate the Netflix user within the wider digital scenario of algorithmic culture and surveillance. I contend that, ultimately, the Netflix user is part of a feedback loop in which the service's interface prioritizes selected global hits and a limited roster of titles based on user behavior, geopolitical location and the continuous attempt to hide its catalog limitations while selling the vastness of its collection. This leads me into a discussion of how the Netflix interface manages the spectators’ experience through a series of connected features. Thus, in the following section, ‘We Pay to Buy Ourselves in the Land of Plenty: From Autoplay to Searching & Browsing’, I detail Netflix’ personalization mechanisms, arguing that, ultimately, its users ‘pay to buy themselves’, or the version of themselves its interface offers back to users upon systematically gathering data on their habits and behaviors. For this purpose, I scrutinize the dynamic browsing/viewing within the Netflix interface in relation to the services’ catalog structure and other key features such as the ‘Search’ and ‘Autoplay’ functions. Finally, in the conclusion, I remark that the key characteristics of the current streaming service/spectator relationship are deceptive limitlessness, customization, the automation of content flow and ubiquity, weaving a form of audiovisual engagement that has partially and, at times completely, conquered our everyday.
For these purposes, this article analyzes scholarly research on streaming services, key historical shifts in forms of spectatorship and, more specifically, Netflix and the defining characteristics of its interface. Complementarily, it mobilizes a series of references on the connected ecology of the digital media, especially focusing on algorithmic culture and customization to situate the Netflix / user engagement within today's broader mediascape. It also employs data and statistics from business portals and corporate press releases and documents to address, on the one hand, Netflix's global reach and, on the other, its branding strategies and how they relate to the user interface it constructs. Finally, it analyzes Netflix's interface and the different types of actions —most remarkably, browsing, searching and viewing— users carry out to access the available contents.
While other scholars have previously analyzed Netflix’ interface, I believe that this article offers a novel approach to its operational logics, especially in as much as it pays attention to how the ‘Autoplay’ and ‘Search’ functions combine to create an environment which, based on the data collection of user behavior, fosters extended consumption habits; it also analyzes how Netflix shapes browsing to make the vastness of its catalog apparent, attempting to organize user habits through a series of categories or groupings that target personalization. Additionally, it addresses novel features within the Netflix interface that push towards the automation of consumption, pointing to the increasing presence of algorithmic processes of customization within the contemporary media environment.
Even though Netflix does not exist in a vacuum since other streaming services utilize similar strategies to engage users, I concentrate on this company for two main reasons. First, Netflix has been pioneering in creating personalized consumer experiences that push the logic of automated recommendation far more than other streaming services. Second, Netflix is fully global, and it is specifically an audiovisual media service that (co-)produces and distributes films, television shows and, at times, comedy specials. Some other services have certainly gained a significant market share in the last years. Yet, they are either parts of conglomerates—HBO or Disney + —that have greatly built upon their prior ownership of media content or are components of a company in which audiovisual media is part of a larger, multi-layered, offering, such as Prime Video.
Streaming in Context: From Previous Media to Netflix’ Planned Differentiation
In recent years several volumes and articles have analyzed the increasing importance of Netflix as a key actor in the audiovisual panorama (Jenner, 2018; Johnson, 2018; Johnson, 2019; Lobato, 2018; Lotz, 2017; Mikos, 2016; Tryon, 2013 and others). While addressing key issues such as algorithmic culture, binge watching, digital delivery and distribution, new types of spectatorship, content aggregation, international television flows, viewer immersion, participatory culture or product customization, at the core of all these efforts there is a constant attempt to define a slippery object: streaming services. While some speak about ‘streaming megaplexes’ (Tryon, 2013) remarking their increasing growth in the mediascape, others prefer ‘streaming platforms’ or ‘retailer aggregators’, placing the emphasis on other aspects of these digital scenarios (Vonderau, 2015). Mikos conceptualizes these services as the latest form of time-shifting technologies that began with the VCR and continued with the DVD player to subsequently evolve into digital Video-on-Demand (VoD) platforms (2016:, p. 159). Jenner (2018), on her part, situates Netflix within the development of television. While remarking that television has never been a stable, easily definable, object, this author coins the term ‘Netflix as television IV’—that is, the latest development in the three stages of television previously defined by John Ellis (2000) and Roberta Pearson (2011). Jenner also adds that Netflix entails a re-invention of television, already prefigured by a series of viewing habits related to DVDs or DVRs. Lotz (2017) proposes the term ‘portals’ to refer to internet-distributed television—that is the services that collect, curate, and distribute television programming on the web. She focuses on a variety of services that include diverse customization techniques aimed at appealing to the spectators according to their preferences and previous choices; these strategies had already been historically at work in cable channels. Lobato goes a step further. While recognizing the unmistakable connection with the televisual, he defines Netflix as a ‘boundary object’ (2018, p. 20) existing within a variety of categories scholars utilize to critically study media. Furthermore, Netflix is a shifting target; it is simultaneously an infrastructure builder, a curated database and a territorially bound collection of national media services working within the same platform.
How can we pin down the variety of ways in which Netflix's technology and the digital spectator/user habits interact with one another? Shall we think, as Wu stated, that Netflix aims to rewire our entire culture, replacing the traditional television model with one that responds to the habits and practices of the Internet generation (2013)? How has Netflix altered the ‘spatiotemporal orchestration of flows’ (Cubitt, 2005) as a digital distributor and producer? Netflix is a multi-faceted product that cultural commentators approach from different perspectives. And yet it is inadequate to fix our gaze in the present without studying previous stages of media production, circulation and consumption and how they relate to current practices.
Netflix capitalized on the ways in which people had consumed audiovisual media for generations to appeal to their tastes and habits: from watching TV marathons, renting / purchasing videotapes and DVDs to downloading movies or TV shows through non-official networks to subsequently watch them at will. It also mirrored how customers engaged with an almost defunct practice: video store browsing and renting.
Prior to the rise of cable TV, premium channels and streaming, film and TV aficionados regularly used rental stores to temporarily acquire series and films. Organized like small libraries with categorized shelves, video stores offered multiple choices and encouraged customers to circulate through them, browsing different titles before renting or purchasing one or several of them. Like Netflix's catalog, usually these stores also included curated categories such as ‘recommended by’, ‘staff picks’, ‘The best of European art film’ to direct clients to specific titles, often through the intervention of store owners or employees, who were connoisseurs of the existing catalog (Greenberg, 2010). In addition, especially in large urban centers, video stores contributed to create a feeling of media abundance, continuously updating their catalogs with new releases to allure returning customers. After the popularization of the VHS and DVD technologies, consumers started to regularly buy specific films or box sets, which included either several films or entire seasons of television shows. These spectators could completely determine their own schedules to watch these tapes or DVDs, without the need to comply with any deadline or having to pay a fee for late rental returns (Kompare, 2006). Not accidentally, this was one of the main appeals of the first stages of Netflix as a DVD-by-mail service: customers could retain a particular title if they wished, without economic penalties.
With the advent of digital technology and the subsequent appearance of non-official P2P networks a key shift occurred: films and television shows became moveable, downloadable files that could be easily transferred, copied and stored. Through these practices users have sidestepped the official delivery of content and have created their own horizontal networks of exchange and consumption despite litigation efforts from media corporations and law enforcement agencies (Cunningham & Silver, 2013). The ability to download, store, delete, copy and watch files at will using applications like VLC player or UTorrent entails a fundamental shift in the ways in which spectators consume media that situates them closer to DVD and VHS spectators and further from linear television viewers: from mostly passive recipients of pre-scheduled content to active participants in the consumption process; or, in other terms, from viewers to users who often watch several episodes of a series or films one after another (Kompare, 2002). Furthermore, able to browse and choose an overwhelming variety of films and television shows from non-official sites, digital users often accumulate terabytes of content to subsequently watch it (or not) as they see fit, creating their own private libraries of content that they can share (or not) with other P2P users. Thus, for years now digital users have typically constructed their own databases to organize their files, anticipating the functioning logic of contemporary streaming services (Kompare, 2010). Hence, two key characteristics of the current appeal and functioning of streaming services such as Netflix—binge watching and the existence of a multifarious and ample catalog—existed at the very core of how P2P networks participants were engaging with the acquisition, exchange and consumption of content. Thus, Netflix’ unparalleled expansion in the last decade is greatly based on the adaptation and transformation of preexistent types of media engagement. Netflix has also challenged standard industrial practices in the film business, has progressively shifted from distribution to production, turning into a vertically integrated company, and has created a variety of global/local markets through a series of connected processes of planned differentiation, as I explain below.
Netflix has grown to become a global player in the digital mediascape through three basic strategies. First, significantly increasing its reach in the last decade by disrupting dominant forms of distribution based on spatial and temporal windows (Lobato & Lotz, 2020; Steemers, 2016). In this regard, Netflix, like other streaming services, has favored a ‘multiterritory footprint’ that requires exclusive ownership over content for a prolonged period (Doyle, 2016, p. 645). Second, investing more and more on original contents, therefore reducing its dependence on licensing agreements with other companies, especially Hollywood studios and other multimedia conglomerates, which have launched or expanded their own streaming services. Third, becoming global and regional by striking partnerships with media companies to dominate both national and international markets, working through a logic of planned differentiation. For Netflix geographically customizes catalogs depending on a variety of factors such as temporary distribution agreements and viewer preferences—that is, it targets global- audiences, creating a multinational subscriber base (Lotz, 2021). Through its expansion in the last decade, Netflix has managed to go beyond geographical criteria to design its recommendation categories in each territory. Gathering further data, Netflix has been able to ‘identify the same viewer segments in the different territories. Their viewing niches are now global’ (Fernández-Manzano et al., 2016, p. 575). Surely, Netflix aspires to construct global audiences with colossal hits such as Stranger Things (2016-). At the same time, in major and mid-size markets, Netflix maintains a commitment to deliver local products in order to appeal to the linguistic and cultural competences of these universalized and yet regionally specific spectators. These processes of planned differentiation go a step further since Netflix displays its catalog a highly customized fashion. Each user encounters a diverse hierarchization of the available media, which is based on the complex, algorithmic processing of his/her actions within the application's interface. Thus, Netflix has created a ‘hyper-personalized and yet connected media diet… supported by new digital media networks, services, and technologies’ (Matrix, 2014, p. 134).
In today's streaming world, users can also decide when and how to stop, rewind, fast-forward, and return to a show whenever they want. They can also divide their attention in simultaneous activities while utilizing the Netflix interface in a variety of devices—from mobile phones to 60-inch TV sets. These new, multi-focus, spectators deal with concurrent stimuli in a regular basis, reacting and actively engaging with what Ernst has called ‘permanent data transfer’ (2004:, p. 54). Able to access content on multiple screens, spectators may start watching a film on a computer at their workplace, continue it on their ride home using a mobile phone, and finish it on a TV set, traversing devices as the rhythms of their everyday dictate how such content is accessed. Asked to dynamically participate in the viewing processes while navigating, touching, multiple screens, spectators must confront the interface—that is, a seemingly transparent surface of ‘endless choices’ which is, in actuality, a carefully crafted customized experience that services like Netflix create for subscribers deploying algorithmic techniques with two main goals: catch their attention and retain them (Neira, 2020, p. 61).
Netflix and the Algorithm
For the last two decades, consumers have increasingly partaken in a connected ecology that grants them access to cultural items through multiple, interrelated devices (Burroughs, 2015; Holt & Sanson, 2014). Furthermore, today content flows are channeled and re-articulated through these networked users. Accordingly, consumers are key nodes in the production of content in as much as their preferences, consumer habits and actions have been transformed into targeting tools for the marketing and branding processes carried out by major corporations (Petruska, 2018; Thurman, 2008; Zuboff, 2019). Hence, their behaviors are stored, analyzed and charted, becoming the measures of who they are; these data are systematically utilized to shape their digital identities and to create user profiles that are constantly compared to their own, prior histories and others’ data (Belk, 2016). Compiling and processing all these data, companies such as Netflix create both individualized experiences and user groupings, customizing their catalogs to appeal to the different market niches they identify. Thus, through their actions, users allow media companies to track and systematize their behaviors in order to guide their consumption processes.
This major shift entails the preeminence of a business model based on the prioritization of personalized services (Alexander, 2016; Arnold, 2016; Jenner, 2016). This task has been facilitated through the development of what Hallinan and Striphas label algorithmic culture—namely, ‘the use of computational processes to sort, classify, and hierarchize people, places, objects, and ideas, and also the habits of thought, conduct, and expression that arise in relationship to those processes’ (2016:, p. 119). Moreover, the widespread utilization of data mining to gather information about the behaviors of digital users allows media companies to generate an ‘algorithmic identity’ (Cheney-Lippold, 2011) for each of them, which can measure their habits and communicative patterns when engaging with media. Consequently, these companies address potential customers through a series of personalized strategies that constantly create varying recipes or recommendations to lure users into sustained acts of consumption. In this regard, on services like Netflix, these recommendations become the main mechanism through which everything that appears on the user interface is organized and designed (Seaver, 2019). In addition, media companies not only attempt to make users believe that the content they deliver was designed specifically for them; they also control what content they access and the steps they undertake to carry out a specific act of consumption (Cunningham & Silver, 2013; Finn, 2019). In other terms: while the individual may experience a feeling of control, ultimately, the rise of algorithm culture and identity has exponentially increased the corporate knowledge about any media user. Concurrently, it is also necessary to remark that each digital user is an unstable mishmash of often conflicting patterns, which is only partially predictable (Cheney-Lippold, 2017). There is not a single, core self but, conversely, a multiplicity of selves that behave in a variety of ways, at times contradictorily, at times complementarily, depending on their needs and goals in a variety of media environments (Belk, 2013). And yet, streaming services constantly attempt to pin down these multifarious identities and turn them into trackable data to target customers. They monitor users’ behaviors, analyzing their interactions within the service with unremitting surveillance (Chamberlain, 2010). With each action within the Netflix interface, users not only express their choices but also offer a diversity of models to predict their behavior, and, potentially shape it. These techniques of personalization are thus a complex set of predictive operations that manufacture products based on users’ behaviors and what they may want next (Zuboff, 2019, p. 279). Netflix itself makes it crystal-clear: its recommendations are fundamentally based on users’ actions—how they rate shows, their viewing histories and the ratings of other Netflix members with similar tastes (Netflix Help Center, 2018). In other words, by interacting with the Netflix interface users are not only making a series of immediate choices but also, to a great extent, shaping their own future within the service.
This sophisticated and massive gathering of data is not only deployed to customize the interface of a given user but also to execute the release and production plans of streaming companies (Christian, 2018). For example, through its original productions, Netflix has persistently targeted an eclectic pool of customers, producing both mainstream and specialized content. Furthermore, designed to promise endless choices, obscuring licensing restrictions and simplifying users’ actions, Netflix sells a utopia of simplicity and unparalleled access, turning the non-official activities through which users consume content—for example, separately downloading the video and subtitles files—cumbersome and, if buying the service's promise of infinite choice, unnecessary (Vonderau, 2015). Nonetheless, Netflix is, in actuality, a shifting, editorially managed library of content (Johnson, 2017). Or in other terms, a customized audiovisual catalog built upon countless data that is culturally, industrially and geographically specific, and, concurrently, attempts to appeal to the individual taste, viewing habits and actions of users while capitalizing on salient audiovisual trends or cycles at a given historical juncture (Lobato, 2015). To put it succinctly: “From both the production and the consumption standpoint, big data-fueled algorithms are increasingly dictating how media consumers navigate their media environment, while also increasingly dictating content production decisions” (Napoli, 2016a, p. 2).
Netflix prioritizes novel content, creating a sense of immediacy. In this regard, it greatly privileges its Autoplay function with two main goals; firstly, to feature and promote new releases; secondly, to encourage viewers to keep watching without their direct intervention (Johnson, 2019, pp. 216–217). Now it is worth exploring further the importance of content flow at the core of Netflix's engagement with its users and, specifically, how the service's interface interpellates them to maximize their time within its framework. In that regard, it is time to analyze how the Autoplay function works, and how it relates to content browsing and the partial marginalization of the Search function.
We Pay to Buy Ourselves in the Land of Plenty
:
From Autoplay to Searching & Browsing
To call Netflix a VoD service may be appropriate in as much as users interact with its interface and ‘choose’ what content they will watch. However, after this initial choice, typically the Autoplay function can, potentially, do the rest for us, since it works under the assumption that users will keep watching (McCormick, 2016; Stanfill, 2015). In other words, Netflix, as a media service, flows by default. As soon as the user opens its interface, without even choosing any content, Netflix automatically plays an excerpt of a featured product, which varies regularly depending on the company's promotional strategies. Although users may act in a variety of different ways when using Netflix—letting Autoplay dictate what they watch, completely disregarding it, or occasionally use it—the Netflix interface is designed to require minimal work or decision-making on the user's behalf. In addition, this emphasis on on-demand fundamentally neglects the very functioning of Netflix as a recommendation-based audiovisual catalog that explicitly directs users in specific directions. As Alexander has noted, Netflix’ software Cinematch is ‘a system that constantly translates seemingly chaotic behavior into recurring and therefore predictable patterns’ (2016:, p. 84). Providing the illusion of never-ending choices, the Netflix interface seemingly organizes its thousands of titles into manageable categories through a complex set of recommendation filters. In fact, by 2013, 75% of all user activity was determined by the interface's recommendations (Cohn, 2019). Users can, indeed, circumvent all these filters and utilize the ‘Search’ function, which is not centrally featured when one opens the Netflix interface but conveniently displaced to the top left side of the screen. If the searched content is available, Netflix does highlight the selected choice. However, if it is not, the search function activates a ‘similar titles’ logic, suggesting dozens of titles, attempting to satisfy users through a recommendation strategy that hides the lack of availability of a particular title
In this scenario, users pay services such as Netflix to buy themselves, or the complex version of their viewing habits and preferences this type of service designs and constantly updates. For Netflix, like other companies, co-constructs the users’ selves, utilizing their data to shape consumption choices. Consequently, these aggregate selves are jointly assembled and shared (Belk, 2013, p. 489). While creating the illusion that the contents it offers are an extension of our taste and preferences (Finn, 2019), Netflix opens new routes for us to engage with the salient products it aggressively highlights through tags such as ‘trending’ or ‘recently added’, prompting us to be in tune with novel series or films
Browsing becomes a key tool for users to engage with the constantly shifting contents Netflix offers; it also allows users to visualize the algorithmic translation of their actions and preferences into a series of categories that may result appealing. 2 When browsing Netflix titles, apart from standard labels like ‘horror’ or ‘comedies’, ‘trending’ or ‘top lists’, one may be find categories based on technological criteria like ‘Ultra HD 4k’, seasonal criteria, ‘Christmas movies’, or customized criteria depending on the users’ own actions within the service, ‘Suggestions based on the fact you saw X or Y tile’ or ‘Recommendations for user X’. The Netflix interface may even suggest when and how to watch a particular item through its tagging mechanisms, for example ‘Crime TV series for a marathon on the weekend’, implicitly organizing our life rhythms and habits. In other words, when scrolling up and down the interface, users encounter trending products, creative non-standard tags that frequently vary and their own, past history as Netflix's users. The sheer visibility of this ‘optimized’, tailor-made experience requires for users not only to binge watch until falling asleep but also to recurrently browse the Netflix catalog so that its size and variety becomes apparent.
In ‘The Netflix Recommender System: Algorithms, Business Value and Innovation’, Netflix engineers Gómez-Uribe and Hunt state that the service's interface is designed to minimize the amount of time that users spend deciding what content to watch since their research has proven that this is a key factor in customers’ retention, a crucial aspect for the company's financial bonanza (2015:, p. 2). According to these authors, Netflix aims to achieve the maximum amount of ‘moments of truth’—that is, a customer choosing to watch a specific title within seconds of logging in. As media scholars, we can accept their assertions or problematize them, keeping in mind two known facts. First, as a company, Netflix is notoriously opaque in giving information and data about the success or failure of its titles and how users intact with the service. Second, Gómez-Uribe and Hunt worked for Netflix when their article was published and, without dismissing the integrity of their research, one wonders if they would publish any account on the Netflix user interface that would not augment the reputation of the product they contributed to create. Consequently, in my view, while acknowledging their research, we need re-focus our inquiries in complementary directions in order to have a more comprehensive picture of how subscribers utilize the Netflix interface. Undoubtedly, Netflix attempts to produce and distribute appealing content for its customers since, otherwise, many of them would cancel their subscriptions. At the same time, it is important to highlight the fact that Netflix also aims at selling its inescapability within the contemporary mediascape to the point that, as I remarked in the beginning of this article, it has managed to become the preeminent identifying label for media streaming services for many consumers. One of the key reasons through which Netflix has achieved this status is its ‘all you can eat’ approach to the acquisition and production of titles to appeal to geographically specific users through a variety of titles that fit their preferences, tastes, and linguistic and cultural skills while also delivering universal hits. Through its extensive catalog, the ‘illusion of plenty and abundance’, in the words of Johnson (2019), Netflix nurtures its inescapability, its status as the default streaming choice for media users. Designing a user friendly, visually appealing and easy-to-navigate interface, Netflix needs users to watch content, indeed, but it also requires for users to constantly explore the sheer size of its catalog and its numerous and creative groupings of titles so that this magnitude becomes constantly evident. In other words, browsing is central for the visibility of Netflix’ status as an unparalleled content provider. In this scenario, browsing also contributes to strengthen the misleading idea that the Netflix catalog is limitless
Conclusions
A commercial for iPhone XR shows a series of people either barely awake or asleep in front of this device's screen as Julie Andrews’ soothing ‘Stay Awake’ plays in the background. 3 Two text messages appear throughout the advertisement: ‘The longest battery life in an iPhone ever’ and ‘You’ll lose power before it will’. The message is crystal-clear: the new iPhone model offers endless stimuli, outperforming the endurance of the human body. In other words, iPhone XR is both potentially ubiquitous and everlasting, keeping users constantly connected beyond their physical and mental capabilities. Apple's commercial strategy echoes Reed Hastings’ above-mentioned statement that Netflix’ enemy is ‘sleep’. Both media giants aim at mastering our bodies, minds and, perhaps souls, beyond our daily conscious hours, infiltrating our dreams and nightmares, as unrelenting companions that monitor our most intimate rhythms and ways, gathering information to ultimately deliver more and more stimuli that may appeal to us. This is precisely the reverse of the utopia of unlimited choice these companies try to promote since their goal is that users internalize their indispensable presence in our everyday. In other terms, without them, we aren't ourselves; we need them to be us.
I open this article with William Uricchio's words, precisely because they accurately predict three of the key characteristics of today's streaming panorama. First, users confront a continuous flow of customized content that is designed not only to keep them in front of multiple screens but also to interact with their life rhythms and moods, effectively penetrating their everyday and becoming ubiquitous as they navigate the contours of the social fabric. Mobile devices such as iPhone XR greatly exist to guarantee this perpetual connectedness, being the tools through which users access audiovisual streaming. Second, gradually streaming services have attempted to facilitate and minimize the users’ actions to watch content with functions such as Autoplay and a remarkable amount of recommendation categories. Recently, they are going a step further. In the early months of 2021, Netflix launched a new opt-in feature for offline users, ‘Downloads for You’. It automatically downloads shows that the app infers a user may like. According to Patrick Flemming, Director of Product Innovation, ‘we do the work so there is always something new waiting to entertain and delight you’ (2021). Previously, in 2016, Netflix had created the ‘Smart Downloads’ feature, allowing users to download episodes of their favorite shows for offline consumption. Now, Netflix has almost completely taken users’ choices out of the equation. Users only need to turn the new feature on; once this is done, customized content, exclusively based on the users’ own histories within the Netflix app, will become available, seamlessly and ubiquitously. Thus, it seems clear that the streaming company is increasingly pushing for an environment in which the automation of content consumption becomes dominant. Potentially, this is also an ideal scenario for Netflix to strategically highlight different audiovisual products, following its global and regional strategies. The “Downloads for You’ feature envisions a future with no more browsing, searching or even choosing, simply the relentless consumption of the content Netflix curates, ‘allegedly’, for each of us. Furthermore, on April 2021, Netflix launched ‘Play Something’, a feature designed for users who want to bypass all decision-making and dive in whatever the interface selects (Johnson, 2021). 4 The ‘Downloads for You’ and ‘Play Something’ seek to eliminate or, at least minimize, the vast majority of users’ decision-making. In other words, Netflix potentially becomes a ubiquitous curator which inexorably provides content, just a click away. Consequently, services such as Netflix are prioritizing what Hesmondhalgh and Lotz have labeled ‘automated personalized recommendation’ (2020:, p. 403). They aim to make our experience ‘effortless’ and, to a certain, passive, since audiovisual content comes to us, without requiring significant intellectual labor on our part. To put it succinctly, they partake in a widespread set of practices within the contemporary digital realm in which “it is no longer enough to automate information about us; the goal now is to automate us” (Zuboff, 2019, p. 8). Third, at the same time and complementarily, streaming services capitalize on the illusion of endless choice, what Uricchio defines as ‘nearly infinite in its capacities’. Although Netflix’ catalog may be vast and diverse, it is finite, even if this company makes every effort to hide this fact, constantly selling an idea of plenitude that combines both mainstream and prestige products (Tryon, 2015, p. 106). This is precisely one of the keys of Netflix's success: the appearance of limitlessness, of making users believe the service has everything they may want, shrewdly hiding or downplaying the temporality of licensing agreements by constantly delivering new content, as a non-stop distribution and production machinery users need to constantly check if wanting to be in tune with the trending mediascape.
As content circulates through multiple devices and users access their personalized media catalogs three things appear clear. Firstly, users increasingly consume media through services that make them participants in both customized types of engagement and collective processes of exchange within the wider public sphere. They may share a Netflix account with three other people and, yet, at the same time, each user typically has his/her own profile, separately, building his/her own audiovisual library as part of a shared process that, nevertheless, from a consumption standpoint, is mostly individualized. In other words, these services speak directly to us, selling to our user alter egos the carefully woven versions of ourselves they have relentlessly constructed through the constant surveillance of each of our steps within these platforms. In that sense, we pay to buy ourselves. Secondly, the wide development of algorithmic techniques certainly informs the production, acquisition and distribution strategy of these companies. Services such as Netflix process consumption habits and tastes and subsequently strike licensing deals with content owners or (co-) produce their own artifacts through a global and yet regionally specific strategy aimed at catering to a diversity of users. Thus, they create highly personalized experiences for each user, derived from the continuous gathering of data as he/she interacts with their interfaces. These processes of planned differentiation are at the very core of how streaming services appeal to users through a variety of shifting contents. In that regard, two interface features are central in structuring the interaction between Netflix and users; on the one hand, the default ‘Autoplay’ function, designed to immediately hook spectators as soon as the interface opens and, subsequently, encourage unceasing consumption through an automated content flow; on the other, the creation of a smooth, pleasing and potentially interminable browsing experience in an attempt to create the illusion of an unfathomable catalog, which will satisfy the vast majority of customers. Thirdly, these streaming services are ubiquitous, attempting to appear seemingly necessary for users. In other words, they try, often successfully, to conquer our everyday, beyond specific leisure time slots or viewing environments. As digital portability and Internet data networks become progressively faster and more reliable, we are constantly wired, ready to consume at any given time. Simultaneously, unbeknownst to us, we are also providing information and data about our networked practices—browsing history, phone conversations, online purchases, social networks’ posts etc.—fueling the recommendation filters that frame our digital experiences. Our digital histories become assets different companies trade, based on the fact that algorithmic operations can potentially predict our future behaviors. In this scenario, it is perhaps time to turn away from useful and yet insufficient concepts such as Video-on-Demand to account for the role, characteristics and technological fabric of customized services such as Netflix and call them what they are: our ever-present, daily audiovisual fix, one that flows and stops, and flows again as we touch screens and remote controls, navigating interfaces that have been designed for every moment of our social lives, even if, at times, we subvert these programmed scenarios by completely veering in unexpected directions.
Footnotes
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The author(s) received no financial support for the research, authorship and/or publication of this article.
