With around 27 per cent of consumers encountering dark patterns in offline environments, the report suggests that deceptive design is not exclusive to digital platforms
While online retail remains the primary site for dark pattern exposure, with 50 per cent of consumers reporting such experiences, a report has revealed that these design techniques that subtly influence consumer choices are prevalent across both online and offline retail environments
A report by Esya Centre noted that around 27 per cent of consumers also encountered them in offline environments, suggesting that deceptive design is not exclusive to digital platforms. The report added that despite their prevalence, dark patterns appear to have limited behavioural impact. Over 39 per cent of respondents noted no change in shopping behaviour online, and 55 per cent reported the same for physical retail.
Interestingly, a sizable share (38 per cent online and 27 per cent offline) perceived certain dark patterns as beneficial in aiding decision-making. While ecommerce platforms like Amazon, Meesho and Reliance Ajio, are perceived as relatively trustworthy, the travel and hospitality sectors stand out for using aggressive tactics, like hidden fees and seat selection traps, triggering greater consumer frustration.
“While recent regulatory focus has been primarily on online marketplaces, we believe a more holistic approach would better serve consumers. The recent self-governance advisory specifically targeting digital platforms creates an uneven playing field and overlooks similar practices in traditional retail. What is needed is a collaborative framework that clearly distinguishes between acceptable marketing tactics and manipulative design elements, regardless of where the transaction occurs,” stated Meghna Bal, Director, Esya Centre.
The report urged joint responsibility among businesses, platforms, and regulators to foster a retail ecosystem grounded in transparency, trust, and informed choice. It advocates for a collaborative governance model that leverages the strengths of each stakeholder, particularly as artificial intelligence (AI) and machine learning tools gain traction in detecting and curbing deceptive practices, to design context-sensitive, scalable regulatory solutions.
