Dark patterns in subscription cancellation: what the research found

The largest empirical audit of dark patterns to date is Mathur and colleagues' 2019 ACM CSCW paper.

The Princeton-led research team automated the crawl of approximately 11,000 popular shopping websites and manually categorized the deceptive interface choices they found. The paper produced the first quantitative picture of how widespread dark patterns are and which categories appear most often.

Mathur et al.: "We discovered 1,818 dark pattern instances, together representing 15 types and 7 broader categories. These dark patterns appeared on 11.1% of the 11K shopping websites we crawled. Shopping websites that were more popular, according to Alexa rankings, were more likely to feature dark patterns." — Mathur, A. et al. (2019). "Dark Patterns at Scale: Findings from a Crawl of 11K Shopping Websites." Proceedings of the ACM on Human-Computer Interaction, 3(CSCW), Article 81.

The seven categories the paper identified are: sneaking, urgency, misdirection, social proof, scarcity, obstruction, and forced action. Cancellation flows concentrate the obstruction and misdirection categories. Obstruction makes a desired action (cancellation) artificially harder; misdirection visually steers the user toward the action that benefits the company.

The US Federal Trade Commission's 2022 staff report formalized the regulatory framing, adopting a similar taxonomy:

"Companies are increasingly using sophisticated design practices known as 'dark patterns' that can trick or manipulate consumers into buying products or services or giving up their privacy." — Federal Trade Commission. (2022). Bringing Dark Patterns to Light: Staff Report.

The same staff report led to the FTC's 2023 proposed Click-to-Cancel rule, which requires that cancellation be at least as easy as signup. The rule explicitly cites the Mathur et al. findings as evidence of the scope of the problem.

The practical reading: the dark patterns in your cancellation flow are not isolated edge cases. They are documented industry-wide phenomena with their own academic and regulatory literature.

References

• Mathur, A., Acar, G., Friedman, M. J., Lucherini, E., Mayer, J., Chetty, M., & Narayanan, A. (2019). Proceedings of the ACM on Human-Computer Interaction, 3(CSCW), Article 81.
• U.S. Federal Trade Commission. (2022). Bringing Dark Patterns to Light. Staff Report.

Related: Hidden cancel button · What is a dark pattern · Click-to-cancel law · Loss aversion