Essay – Spotify’s datamining practices: An example of surveillance capitalism?

April 30, 2020

Jekaterina Vinogradova, Final Year Student, Politics and International Relations with Study Abroad BSc, University of Bristol


Manokha (2018: 226) presents the case that surveillance has always been present in social life, however, its extent has grown alongside modernity and the bureaucratic state. He also elaborates on Giddens’ (1985) ideas regarding what institutional factors are constitutive of modernity and persuasively argues that in the digital age, surveillance cuts across capitalist enterprise, industrial production, and centralised control of the means of violence (Manokha, 2018: 227). In this essay, I would like to focus on how this idea can be seen through Spotify’s datamining practices, which provides us with illuminating insights into the phenomenon of ‘surveillance capitalism’. I find that considering the levels of surveillance we find in the modern society is impossible without taking into account the role of secrecy and how that “structures social or political relations of exclusion and inclusion; by separating those who know from those who do not” (Horn, 2011: 109). My chosen subject-matter makes the separation between included and excluded, known and unknown, even more nuanced as I tackle something – namely commodification of people’s personal data – that is technically universally known and yet cloaked in secrecy, which often protects tech corporations from criticism, akin to the smoking industry case study presented by Proctor (2008). I find that this secret object analysis is important as it can tackle the apathy that can lead things to become unknown once again through production and maintenance of ignorance (Proctor, 2008; Horn, 2011: 108).


In particular, I am interested in how Spotify, one of the most popular music streaming services, collects, and utilises its users’ data. Elaborating on DeNora’s (1999) conceptualisation of music as a ‘technology of the self’, some have likened the way that Spotify serves up data back to the users to a personality quiz, as music should be considered “a particularly … personality-revealing aspect of people’s lives” (Engel Bromwich, 2020). The service currently boasts over 108 million paying users, and 124 million who use the free version, which contributes to billions of daily streams, which can be translated into an infinite amount of data about the users’ listening habits (DiFranza, 2019). Through real-time analytics, you get to know not only what people are listening to, but where and on what device – it is undeniable that Spotify is a data-driven company and that this must not be left without the same levels of scrutiny we are beginning to have for other services, such as Facebook and Google (Marr, 2017; Beres, 2019).  The data collection is not technically made secret and is often incorporated into Spotify’s marketing, such as the annual Wrapped campaign, which lets the users know about their most played artists and songs (Engel Bromwich, 2020). In 2019, this practice was elevated by providing insights into analytics for the decade that Spotify has been operating, and continuously collecting the users’ data (Engel Bromwich, 2020). Companies, which rely on data collection to provide the personalisation for the success of their business model defend their practices by saying that “it’s not like you’re breaching anybody’s privacy, because the core proposition here is we know you and try to put the right” content in front of the user (Friedland, in Maheshwari, 2017).


Upon closer inspection of Spotify’s privacy policy agreements, it becomes clear that way more data than necessary for mere personalisation is being collected, such as data held on third-party apps, location, the ability to “collect voice commands captured by built-in microphone; and to scan local media files on users’ devices” (Drott, 2018a: 233-34). This move is a great example of digital media companies attempting to blur the line around what are considered acceptable data privacy violations as a trade-off for services provided (Drott, 2018a). The privacy policy also makes it clear that Spotify reserves the right to share the data with various third parties, including its unspecified ‘advertising partners’ (Drott, 2018a; Brewster, 2020). It is also important to note that your data will be collected by Spotify whether you are a paying or freemium user – the only choice you have is whether to quit Spotify or accept this invasion of privacy (Brewster, 2020; Beres, 2019).


The asymmetries of knowledge, and consequentially power, in this relationship between the user and the streaming platform is perturbing, in particular, as it seems to be unavoidable that upon us choosing to use a service, “tech companies can both get access to masses of data and create digital environments that are beneficial to their business and dominance” (Drott, 2018b; Helles and Flyverbom, 2019: 35). Thus, we are met with a paradox under which a company knows way more about us than we do about ourselves, and we are denied access to that information (Dredge, 2015; Zuboff, in Naughton, 2019). This leads us to consider a new form of capitalism, which commodifies human experience as behavioural data – ‘surveillance capitalism’ (Naughton, 2019; Zuboff, 2015). This erosion of individual autonomy has been subtle, due to the ubiquity of technology and this is why the consequences of these developments have been as nefarious and pervasive as they have (Manokha, 2018; Myers West, 2019).


To conclude, we must confront the idea that while the era of total surveillance we are encountering might make it seem that there are no secrets, perhaps “secrets are all there are” (Gilbert, 2007: 23). While marketing has always been defined by persuasion, bordering on deception, this has escalated in the digital age (Proctor, 2008). This is why it is paramount to consider how the politics of secrecy are enacted as people are understood merely as data and “our experiences of subjectivity and communication are increasingly mediated through technologies of digital consumer surveillance” (Birchall, 2016: 154). A look into Spotify’s practices regarding its users’ data is an important example, as it is “currently the world’s most valuable music company” and has had a tremendous impact on the way the streaming industry uses, and capitalises on, our personal data that we can’t help but willingly handover as our need for privacy are confronted with desires for community (DiFranza, 2019; Myers West, 2019).




Beres, Derek, 2019. How Spotify manipulates your emotions and sells your data. Big Think, [online] 20 February. Available at: <> [Accessed 9 March 2020].


Birchall, Clare, 2016. ‘Managing Secrecy’, International Journal of Communication10: 152-163.


Brewster, Thomas, 2015. Location, Sensors, Voices, Photos?! Spotify Just Got Real Creepy With The Data It Collects On You. Forbes, [online] 20 August. Available at: <> [Accessed 8 March 2020].


DeNora, Tia, 1999. ‘Music as a technology of the self’, Poetics27 (1): 31-56.


DiFranza, Ashley, 2019. Spotify: Big Data Shows Big Results. Northeastern University, [online] 4 October. Available at: <> [Accessed 9 March 2020].


Dredge, Stuart, 2015. Spotify has six years of my music data, but does it understand my tastes?. The Guardian, [online] 6 January. Available at: <> [Accessed 12 March 2020].


Drott, Eric A., 2018a. ‘Music as a Technology of Surveillance’, Journal of the Society for American Music12 (3): 233-267.


Drott, Eric A., 2018b. ‘Why the Next Song Matters: Streaming, Recommendation, Scarcity’, Twentieth-Century Music15 (3): 325-357.


Engel Bromwich, Jonah, 2020. What Do Those Spotify ‘Top Fans’ Messages Mean?. The New York Times, [online] 27 February. Available at: <> [Accessed 5 March 2020].


Gilbert, Jeremy, 2007. ‘Public Secrets: ‘Being-with’ in an era of perpetual disclosure’, Cultural Studies21 (1): 22-41.


Helles, Ramus, and Flyverbom, Mikkel, 2019. ‘Meshes of Surveillance, Prediction, and Infrastructure: On the Cultural and Commercial Consequences of Digital Platforms’, Surveillance & Society17 (1/2): 34-39.


Horn, Eva, 2011. ‘Logics of Political Secrecy’, Theory, Culture & Society28 (7-8): 103-122.


Maheshwari, Sapna, 2017. Netflix and Spotify Ask: Can Data Mining Make for Cute Ads?. The New York Times, [online] 17 December. Available at: <> [Accessed 5 March 2020].


Manokha, Ivan, 2018. ‘Surveillance, panopticism, and self-discipline in the digital age’, Surveillance & Society16 (2): 219-237.


Marr, Bernard, 2017. The Amazing Ways Spotify Uses Big Data, AI And Machine Learning To Drive Business Success. Forbes, [online] 30 October. Available at: <> [Accessed 9 March 2020].


Myers West, Sarah, 2019. ‘Data Capitalism: Redefining the Logics of Surveillance and Privacy’, Business & Society58 (1): 20-41.


Naughton, John, 2019. ‘The goal is to automate us’: welcome to the age of surveillance capitalism. The Guardian, [online] 20 January. Available at: <> [Accessed 11 March 2020].


Proctor, Robert, 2008. ‘Agnotology: A Missing Term to Describe the Cultural Production of Ignorance (and Its Study)’, in Proctor, Robert, and Schiebinger, Londa L. (eds.) 2008. Agnotology: The Making and Unmaking of Ignorance. Stanford: Stanford University Press, pp. 1-35.


Zuboff, Shoshana, 2015. ‘Big other: surveillance capitalism and the prospects of an information civilization’, Journal of Information Technology 30 (1): 75-89.


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