Personalisation has extended to our entire user experience in the digital world. In practical terms, almost all the online services promote us to create a user profile and from there, they offer access to personalised content and/or services. This leads us to the generation of Big Data associated with user profiles which the companies harvest through analytic and predictive algorithms, which they later use to recommend, filter, and provide the content we consume. Having more and more detailed data from user profiles allows for the platforms to detect tendencies in a global public and to create the content that has the greatest chance for success. This chapter examines the massive data management that occurs on platforms that distribute visual content on demand and its impact on content creation. We will focus on Netflix as a paradigm example.
TopIntroduction
In recent decades, the audiovisual sector has undergone major changes that have affected all phases of production of audiovisual content, the content itself, the marketing related to that content, the value chain, and the way in which viewers or users relate to and consume the content. The change may seem radical in some respects, but the most striking element is the speed at which it is taking place.
With the introduction of the so-called information technologies, digitalisation and the creation of the Internet, our notion of space and time has been reconfigured. Communication technologies are causing time to accelerate (Virilio, 1997) and space to contract (Augé, 2002), which places us before three concepts around which the most significant changes at the communicative level revolve since the appearance of the Internet: digitalisation, ubiquity and instantaneousness.
The Internet, due to its characteristics and implications, has become an environment that forces us to redesign processes (Roca, 2012). The digitalisation of contents and their access through the Internet alters, at the same time, production systems and knowledge transmission systems.
All companies working with content and/or processes that can be digitised are speeding up the process that turns products into services. Netflix, Hulu and Spotify are examples of these models. The era of access (Rifkin, 2000) to content and services is replacing that of ownership.
These multinational media companies are using the new digital revolution in communications to connect the world and, in the process, they are inexorably pulling the cultural sphere into the commercial sphere, where it is commodified in the form of ready-made cultural experiences for their customers, mass commercial shows or personalised entertainment (p. 18).
Internet access is allowing consumers to manage their time and space for consumption. An environment where content is available anytime (instantaneousness), anywhere (ubiquity) and on all devices (mobility) has changed users’ consumption habits and their relationship with content and content providers.
“Speed changes the view of the world” (Virilio, 1997, p. 23) and this time in a more pointed way, by being an intrinsic element of this hyperconnected society and of the technologies of instantaneousness that have shaken the foundations and processes of the cultural industry sectors: press, music, audiovisual, editorial, etc. An industry such as the audiovisual sector, whose business model is based on the management of intellectual properties in time and space, with products that can be digitised and easily reproduced, has seen how in just a few years it has needed to adapt to changes and, in some cases, redefine or even reinvent its business model.
This chapter joins other research on the relationship between new technologies and users (McLuhan, 1996; Battelle, 2006; Manovich, 2005; Gertrudix, Borges-Rey, & García, 2017) and aims to understand the mass data management carried out on audiovisual distribution platforms on demand and its impact on users and content creation.
To this end, we will analyse the management of audiovisual content within streaming video-on-demand platforms, taking Netflix as a paradigmatic example. We will focus on the company’s data analysis and recommendation system, working with primary and secondary sources: bibliographic and video review, analysis of data published by the company itself and specialised press.
TopBackground
On 4 December 2009, an entry titled “Custom Searches for Everyone” featured on Google’s corporate blog. Many missed it, but that day saw the largest change in the history of search engines (Pariser, 2017). The change brought about by Google was a turning point in the way we consume information: the era of personalisation was beginning.