Hidden features: The Tools that Firms Use to Manipulate Consumers on Digital Platforms and Beyond

An article published by the New York Times 4 years ago showed how Uber used psychological manipulations to influence drivers’ behaviour 1. To incentivize drivers to work longer hours, Uber takes advantage of people’s obsession with “goal pursuit” by letting them know how close they are to hitting their earning goal when they try to log out of the application. Further allegations levelled at the multimillion ride-share company include the practice of alerting drivers about the potential money they would lose by not working on a busy day rather than notifying them about potential gains of working in such a day. In this instance the company exploited what is known as loss aversion, a cognitive bias that explains why individuals focus more on losses than gains, and prefer avoiding losses to acquiring equivalent gains. 

Uber also employed a method used by game designers and social media app developers to keep users hooked. For example, Netflix automatically loads the next episode in a series, Tinder encourages users to keep swiping in a quest for a better option, and let us not forget Twitter’s and Instagram’s endless feeds 2. Uber has a feature known as “Back-to-back trips” that sends drivers new ride requests while they are still busy with their current trip. This approach is conducive to an addictive experience. It seems trivial on a surface level, since working longer hours can be considered a win-win for both the drivers and the ride-hailing company. However, the difference turns out to be enormous. Uber benefits more by having more drivers on the road whereas drivers are better off when there are more riders in a given area than available drivers – surge pricing situation.

The Not-So Rational

Over the years, social scientists have intensively studied topics on motivation, addiction, and different kinds of cognitive biases. With the emergence of behavioural economics, the days of the homo economicus are almost behind us as more and more experiments and subsequent policies have highlighted the weaknesses of the rational choice assumption. The behavioural economics field recognizes that agents are boundedly rational, that is, they have cognitive limitations and biases that can lead them to making suboptimal decisions. It therefore explores these shortcomings to design institutions that help people make better choices and to craft better policies. Businesses leverage methodologies from behavioural sciences as well to design better products and processes. Without a surprise, Uber is one of the many companies that hire behavioural and data scientists to carry out experiments on their platforms. Despite how remarkable the insights from behavioural sciences are, they also offer opportunities for manipulation. Firms can exploit information they have about consumers to influence their behaviour and maximize profits. Especially in this era of the digital economy, companies can develop platforms that collect users’ data, track their behaviour, then change conditions based on the feedback they receive.

There are many examples and studies that highlight how firms respond to consumers’ bounded rationality to their advantage. Gym companies for instance exploit overconfidence of consumers about future self-control and the power of inertia (a tendency to stick with the current situation). This explains the extent of consumers’ overestimation of attendance and the delay of automatic-renewal contracts cancellation despite low attendance 3. Similarly, loss aversion may cause consumers to prefer flat-rate contracts even though they would pay less if they chose a pay-per-use contract. This situation arises when consumers overestimate or are highly uncertain about their future consumption 4. Firms with low marginal cost have an incentive to offer flat pricing because it can mitigate the effect of consumers overconsumption.

The advantage firms have over consumers is that they constantly interact with the market and therefore have more opportunities to understand its vulnerabilities. Consumers on the other hand often have less opportunities to understand the environment, which explains why they have limited experience in relevant markets. This edge gives firms ways to meet consumers at their weakest state: overwhelmed by time constraints, partial information, and inattention. Moreover, when companies compete in the market, they use framing strategies to tap into the inertia bias mentioned earlier. The incumbent firm may use a product campaign or price promotion campaign to ensure that the alternative product appears as similar as possible and make it less relevant. A consumer with inertia bias will find it difficult to compare different products presented to her and will therefore stick to the default. On the other hand, to ease off competitive pressures, firms can create an artificial product differentiation to give consumers an impression of a differentiated product 5. This is referred to as “Spurious” Product Differentiation since it does not increase consumer welfare and stems from the fact that consumers can misperceive the value of the products presented to them. 

Conclusion

Is there a limit up to which companies can exploit consumers’ bounded rationality? How relevant are regulations in a context where firms operate in a gray area of legality? We notice in some cases, consumers naively approve or are not bothered by these behavioural practices (e.g., addicted social media users or Uber drivers trying to maximize earnings). One could agree that the mandate of relevant authorities’ interventions should be to protect the consumer and improve overall social welfare. For instance, by increasing transparency on prices and customers’ expected cost for each product’s option; by alerting subscribers about their usage to avoid unexpected charges. Yet the big part of the responsibility lies with firms themselves. They need to draw a line between the do’s and don’ts of the behavioural science apparatus and use it to nudge consumers into making better decisions. Generally speaking, no tool is inherently good or bad, it is good when harnessed for good and it is bad when it falls in the hands of the bad guys.

By Daniel Tunda

References:

1 Scheiber, Noam. “How Uber uses psychological tricks to push its drivers’ buttons.” The New York Times 2 (2017).

2 Alter, Adam. Irresistible: The rise of addictive technology and the business of keeping us hooked. Penguin, 2017.

3 DellaVigna, Stefano, and Ulrike Malmendier. “Paying not to go to the gym.” american economic Review 96, no. 3 (2006): 694-719.

4 Grubb, Michael D. “Behavioral consumers in industrial organization: An overview.” Review of Industrial Organization 47, no. 3 (2015): 247-258.

5 Spiegler, Ran. Bounded rationality and industrial organization. Oxford University Press, 2011.

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