Platforms and Cultural Production. Thomas Poell
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In addition to allowing cultural producers to save on creation, distribution, and transaction costs, platform companies provide them with access to a bigger and more heterogenous groups of end-users. Facebook, for instance, is available in more than 100 languages. Apple, WeChat, Alibaba, and Line cater to large regional and national audiences (Jia & Winseck, 2018; Mohan & Punathambekar, 2019; Steinberg, 2019). For producers vying to attract regionally diverse audiences, such reach has had profound effects. While the headquarters of the most powerful platform companies are located in just a few countries (i.e., the US, China, and Japan), complementors are much more geographically dispersed. YouTube’s content, for instance, is “largely born global”; as a result, content creators on these platforms are said to be “more racially plural, multicultural, and gender diverse by far than mainstream screen media” (Cunningham & Craig, 2019: 49, 11). A similar increase in geographical diversity can be seen in the book, music, and game industries. Cultural or language-based affinities play an important role here. In India, for example, creators who speak Bengali and Marathi – two of the 121+ languages spoken in India – use streaming platforms to their advantage by creating “demand for regional content from the local and global Indian diaspora” (Mehta, 2020: 117).
Business model alignment
For cultural producers, the trade-off for economic opportunity is often conformity. To enter into a platform market and engage in economic transactions, complementors have to align their business models and work with the economic framework set out by platform operators. Even though such frameworks can be changed at whim, a platform’s business model is a highly formalized arrangement of economic technologies and standards meant to engender trust among complementors. This ensures that markets are transparent and economic friction is reduced. Pricing standards are just one example of how platforms formalize transactions. For example, app developers selling paid apps via Apple’s app store cannot engage in dynamic pricing because they are not allowed to pick any random price tag they want, nor can they set different prices for individual users. Instead, they have to pick from price points pre-set by Apple.
While advertising is one of the most visible monetization options driving platform markets, there is a plethora of other revenue streams, such as subscriptions, microtransactions, and donations. The Apple app store, for instance, lists five business models to choose from: paid (a set, up-front payment), free (i.e., advertising), freemium (optional in-app purchases), subscription (recurring revenues), and paymium (a mix of the paid and freemium model).10 Then there are platforms that do not provide complementors with direct means of monetizing their content (Stoldt et al., 2019). Social networks such as WhatsApp, Instagram, and Twitter welcome complementors to establish a presence on their platform, but provide no direct sources of revenue. The unspoken agreement between these platforms and its users – both end-users and complementors – is that these platform subsidiaries serve as a way to garner visibility and steer attention their way. Instagram influencers are able to generate considerable income by posting sponsored content paid for by brands, but Facebook itself does not pay directly for posts. For this reason, Facebook has become a major headache for traditional institutions, especially news organizations (Myllylahti, 2018).
Collectively, these examples reveal that, while platform business models are marked by a high degree of formalization, complementors are not fully platform-dependent when it comes to generating revenue. Musicians, for instance, retain the ability to secure income outside the boundaries of a platform, such as through selling merchandise or live performances (Hesmondhalgh & Meier, 2018). For complementors, finding the “right” balance between platform-dependent and platform-independent forms of income can be a complicated, continuous exercise. For instance, Spotify not only streams music, it also helps users purchase concert tickets – thus granting the company infinitely more control of previously platform-independent transactions. Similarly, Twitch has added a number of monetization functionalities, some of which integrate the streaming platform more deeply into one of the many business units of its parent company Amazon.
In the end, what makes digital markets more efficient than physical ones is a platform’s ability to extract, store, and analyze information about its end-users and any of the transactions it facilitates. Nick Srnicek goes as far to say that “twenty-first century advanced capitalism” is “centered upon extracting and using a particular kind of raw material: data” (2017: 39). Platforms can provide complementors with detailed market and customer insights, often in real time. To be sure, the systematized gathering of user or market data is not without historical precedent, as media companies have long sought to gather actionable information (Ang, 1996; Napoli, 2011; Turow, 2011). What is different are the scale and the velocity of these efforts.
The datafication of digital markets has a number of implications, discussed in this chapter, chief among which is the lowering of costs. Another side-effect of datafication is that platform markets can be made more transparent compared to nondigital markets – at least to those who are granted access to valuable platform data. For example, data intermediaries can provide information on which app is ranked number one in an app store, creators can see how many people are watching and donating, and journalists can test different headlines to see which one attracts more readers (Beer, 2018; Petre, 2018). Similarly, because data is at the very heart of the digital advertising ecosystem, platform companies remain at the forefront of tracking, analyzing, and modeling end-user behavior (Couldry & Mejías, 2019; Turow, 2011). Game developers, movie studios, and newspaper companies use digital platforms to advertise their games, hype their movies, and sell subscriptions, respectively. The functionality provided by advertising technology is incredibly sophisticated and seemingly endless because of Google’s and Facebook’s relentless investments in data tracking and user targeting technology (Crain, 2019).
Then again, as with so many transformations ushered in by digitalization and datafication, digital advertising is a double-edged sword for complementors. On the one hand, it allows cultural producers to find, track, and target new pockets of end-users that can be sliced and diced into highly granular subgroups. Compared to, let’s say, putting an advertisement in a local newspaper, the ease with which small and medium-sized enterprises (which many cultural producers are) can use Facebook’s and Google’s advertising tools is remarkable. Using Facebook’s targeting tools, it is relatively simple and affordable for a game developer to set up a small advertising campaign to, for example, target a small group of players to see if they like a new game. Using Facebook’s advertising analytics tools, that same game developer can then see the exact demographics of those who have downloaded the game along with features of those who keep playing it; such data can, in turn, be used to launch even better targeted digital advertising campaigns.
On the other hand, using platforms for “user-acquisition” campaigns as described above only makes complementors all the more platform-dependent. In certain cultural industry segments, such as the game app economy, growing an audience organically – without paying money – can be too uncertain, too slow, or simply impossible for new market entrants. As a result, publishers are forced to invest heavily in digital advertising campaigns if they want to reach audiences and get noticed among the never-ending glut of digital content. Facebook’s