Algorithmic Labor As a Game: Agency, Passion, and Unpaid Work in SEO

Thursday, 10 July 2025: 00:00
Location: FSE036 (Faculty of Education Sciences (FSE))
Oral Presentation
Ivanova MIRELA, University of Basel, Switzerland
This paper examines the work of Search Engine Optimization (SEO) specialists who optimize websites for private businesses to achieve higher rankings on Google’s Search Engine Results Pages (SERPs). Google’s search engine is conceptualized as a proprietary marketplace (Staab, 2024; Christophers, 2022), where website owners compete for user attention. SEO specialists are the paid labor power responsibilized for improving website visibility. They have to navigate the inherent uncertainties of this market, shaped by the dynamic interactions between Google’s algorithms, user behavior, and competitors (other website owners). Through qualitative interviews with SEO professionals in Germany and Switzerland, the study explores how these specialists perceive and experience their algorithmic labor.

The findings reveal that SEOs experience a strong sense of agency and efficacy in navigating the uncertain algorithmic environment, framing their work as a game. This agency stems from their ability to influence marketplace outcomes by studying, interpreting, and strategizing around algorithmic rules. This, in turn, fosters a deep personal investment—or "illusio" (Bourdieu & Wacquant, 1992)—in the “game” of their work. The online marketing specialists frequently describe their work not merely as a job, but as a passion, love, or even a hobby. This romanticization of work (Gregg, 2011) conceals the unpaid labor involved, such as continuous self-education and skill development, which SEO specialists pursue in their free time. The paper argues that this phenomenon is grounded in the construction of SEO work as a metrified game. This gamified structure (Ranganathan & Benson, 2020) enhances their sense of agency, deepening specialists’ commitment to their work, while simultaneously concealing the labor embedded in activities perceived as “free time.” The paper thus illustrates how algorithmic, game-like experiences align individuals’ motivations with managerial interests.