It’s Time to Talk about Consumer Strategies on Algorithmic Platforms

By Godofredo Ramizo Jr. – Oxford Internet Institute

What clever strategies do consumers employ when dealing with algorithmic platforms such as Uber, Amazon, and Deliveroo, among others? And how do these consumer strategies affect the welfare of platform workers and the interests of the platform company?

Many researchers have already explored how platform workers strategise to assert their interests against clients, algorithms, and the platform company (Anwar & Graham, 2020; Jarrahi et al., 2019; Lehdonvirta, 2018). But what about consumers on these platforms? To my surprise, little empirical work has been done on the specific strategies of customers or consumers, and the effects of these strategies on platform workers and the platform company. Understanding consumers strategies is critical given that they are a large part of the digital economy. Moreover, the behaviours of consumers creates the constraints and opportunities facing platform workers and the platform company.

The platform playbook – A typology of consumer strategies

I investigate this puzzle in my recent article entitled “Platform playbook: a typology of consumer strategies against algorithmic control in digital platforms” published in Information, Communication and Society.

Through multi-method fieldwork focused on commuters using ride-hailing platforms in Metro Manila, I demonstrate that consumers develop a wide range of strategies to achieve better terms for themselves and meet the needs of daily life. I categorise these strategies into five main types: optimisation, mitigation, boundary hunting, straddling, and heuristic formation. I further elaborate these into 18 sub-types and provide examples. These strategies are made possible by exploiting algorithmic features, undermining social enforcement of platform rules, capitalising buyer’s leverage, and tapping consumers’ social connections, and committing violations that are invisible to algorithms. To my knowledge, this is among the most detailed typology of consumer strategies in algorithmic systems presented in the literature so far.

Consumers act strategically against algorithmic control

The range of strategies described under the platform playbook of consumers reveals important insights about the nature of their strategic behaviour. First, consumers differ from workers, in terms of innate leverage, and in how these groups form, conduct, and derive strategic value from social interactions. Second, the wide use of strategies that aim to manipulate the human counterpart means that counterpart intent should be conceived, alongside algorithmic and managerial control, as tripartite forces constraining the behaviour of actors in the digital economy.

Lastly, consumer strategies often inflict disproportionate costs on workers rather than on the platform company. Many of the consumer strategies in the typology increase the supply side’s operational costs, time delays, and occupational stress – all of which directly impact the workers’ welfare and profit. However,  these same clever efforts to make the best use of platforms help consumers integrate digital platforms into their daily lives. Consequently, these strategies which aim to soften the platform’s control ironically harden consumer reliance on the platform, thus serving the platform’s long-term goal of creating a committed consumer base. In sum, the use of consumer strategies can mean that workers lose out, while the platform company benefits from increased user reliance.

The typology and conceptual implications laid out here can sensitise future studies to the breadth and complexity of user strategies in algorithmic systems and digital platforms. A promising direction is to explore how these consumer strategies can be used to serve consumer welfare and the public good, while still respecting the legitimate interests of platform companies, service-providers and workers.


Anwar, M. A., & Graham, M. (2020). Between a rock and a hard place: Freedom, flexibility, precarity and vulnerability in the gig economy in Africa. Competition & Change, 1–22.

Jarrahi, M. H., Sutherland, W., Nelson, S. B., & Sawyer, S. (2019). Platformic Management, Boundary Resources for Gig Work, and Worker Autonomy. Computer Supported Cooperative Work (CSCW), 29, 153–189.

Lehdonvirta, V. (2018). Flexibility in the Gig Economy: Managing Time on Three Online Piecework Platforms. New Technology, Work and Employment, 33(1), 13–29.

Ramizo Jr, G. (2021). Platform playbook: a typology of consumer strategies against algorithmic control in digital platforms. Information, Communication & Society, 1-16.