How can we tell whether streamed films or series work? The impossibility of unifying success criteria

Subscription Video On Demand (SVOD) platforms are increasingly making access to their cheaper subscription models conditional on viewing with advertising. So much so that, according to data from the eMarketer report Guide to connected TV: Content, measurement and advertising, advertising investment within the television streaming market will grow from the more than $29 billion expected in 2024 to almost $41 billion in 2027. In this context, it is increasingly necessary to standardize how audiences are measured, allowing the connection between content and users to be objectified and quantified.

Open access research by the Universitat Oberta de Catalunya (UOC) argues that a uniform concept of success for SVOD platforms is not viable, and cannot be applied across the board to all services that operate using this model. The research has been led by Elena Neira, course instructor in the Faculty of Information and Communication Sciences at the UOC and a contributor to the Learning, Media and Entertainment Research Group (GAME), who has recently completed her doctoral studies in the Humanities and Communication programme. Other GAME researchers have also participated in this study: Judith Clares and Jordi Sánchez Navarro, dean of the aforementioned faculty and leader of GAME, a group especially interested in the transformations of communication practices associated with the widespread use of and access to the internet.

The article begins by stating that, up to now, most of the consolidated platforms in Spain are reluctant to be transparent regarding data on the consumption habits of their users. One of the main reasons given is that "their business model is not based on the sale of advertising space". They consider, therefore, that their audiences should not be audited like conventional television.

Very different data models

The UOC research reveals a clear division when it comes to evaluating the success of streaming content. On the one hand, there are companies specializing in media research, which focus on sample data, obtained from a representative panel of individuals, as a way to achieve homogeneous, stable and transparent measurement. This is the method used by media research companies, for instance Nielsen, to assess audiences. On the other hand, streaming platforms prefer platform data, because they allow them to predict user preferences and explain correlations between content and viewing habits, based on the entire digital footprint of users connected to one of these platforms, as in the case of Netflix.

Each of these models has advantages and disadvantages. Sample data are based on a representative panel of individuals, which gives them the advantage of reducing market uncertainty. However, they do not reflect all the consumption taking place in SVOD ecosystems. Platform data are a form of big data, generated by users' digital footprints in an online service. Their greatest value is in their granularity, the level of detail and precision with which user consumption data are compiled and analysed, which allows us to learn from the combination of data. Their greatest limitation is the biased use that can be made of them, especially if the data is not debugged initially.

Beyond the eye-catching numbers

SVOD companies continue to cling to a quantitative view of success, expressing it through standard indicators such as the number of viewers, views or hours accumulated, although qualitative markers also proliferate, such as engagement reflected in social media. However, the study by the GAME group researchers has confirmed, through interviews with different actors in the sector, that other dimensions of what is considered success need to be taken into account: a consumption dimension, related to each user's contact with the content; a financial dimension, which reflects the return on investment; a temporal dimension, connected with the time frame that limits the commercial success of the content; and a market dimension, linked to the content's position in relation to other competing content.

Towards a stable but flexible measurement of success

According to the research, these dimensions are the key to avoiding all the points of friction that prevent a standardized approach to what is considered successful in SVOD content. Although this means losing the more complete, dynamic and fluid vision of assessment offered by platform data, it can be made more flexible through relevant indicators related to the dimensions mentioned above.

These indicators are: the intensity, recurrence of viewing and content completion rate (indicators directly related to customer loyalty); popularity, understood as the ability to generate a very enthusiastic collective response from a large number of users (an indicator closely related to business objectives, i.e., attracting and retaining customers); engagement, an indicator that reflects the link between user and content, whose main manifestations are publicity (media coverage and public attention that the content receives), fandom (a community of enthusiastic followers that forms around that specific content) and social resonance (the impact and relevance that said content has in public discourse and in society in general). The latter is essential for building loyalty and extending the reach of the content, and developing the commercial relationship between service and customer (given that the content is part of a strategy for selling and maintaining subscriptions, its indicators of success are the return on investment and customer satisfaction).

This research contributes to UN Sustainable Development Goals 9 (Build resilient infrastructure, promote sustainable industrialization and foster innovation) and 12 (Ensure sustainable consumption and production patterns).

UOC R&I

The UOC's research and innovation (R&I) is helping overcome pressing challenges faced by global societies in the 21st century by studying interactions between technology and human & social sciences with a specific focus on the network society, e-learning and e-health.

Over 500 researchers and more than 50 research groups work in the UOC's seven faculties, its eLearning Research programme and its two research centres: the Internet Interdisciplinary Institute (IN3) and the eHealth Center (eHC).

The university also develops online learning innovations at its eLearning Innovation Center (eLinC), as well as UOC community entrepreneurship and knowledge transfer via the Hubbik platform.

Open knowledge and the goals of the United Nations 2030 Agenda for Sustainable Development serve as strategic pillars for the UOC's teaching, research and innovation. More information: research.uoc.edu.