Products bearing premium brand labels are known to increase perceptions of efficacy and improve objective consumer performance relative to lesser‐branded equivalents, in what is traditionally described as a marketing placebo effect. In this paper, we suggest that experiences bearing these highly regarded brand labels can lead to a reverse effect, such that consumer performance actually declines with their use. Our findings demonstrate across domains of improving mental acuity, learning a new language, and developing financial analysis skills that completing performance‐branded training experiences impairs objective performance in related tasks, relative to lower‐performance‐branded or unbranded counterparts. We posit that branded training experiences can evoke a brand‐as‐master relationship in which consumers take on a subservient role relative to the brand. As a consequence, higher‐performance brands may impose greater demands upon consumers, increasing performance‐anxiety and interfering with an individual's ability to perform effectively. These results document an important ramification of applying branding to learning experiences and identify contexts in which traditionally positive marketing actions can backfire for consumers.

Recent research shows that algorithms learn societal biases from large text corpora. We examine the marketplace‐relevant consequences of such bias for consumers. Based on billions of documents from online text corpora, we first demonstrate that from gender biases embedded in language, algorithms learn to associate women with more negative consumer psychographic attributes than men (e.g., associating women more closely with impulsive vs. planned investors). Second, in a series of field experiments, we show that such learning results in the delivery of gender‐biased digital advertisements and product recommendations. Specifically, across multiple platforms, products, and attributes, we find that digital advertisements containing negative psychographic attributes (e.g., impulsive) are more likely to be delivered to women compared to men, and that search engine product recommendations are similarly biased, which influences consumer's consideration sets and choice. Finally, we empirically examine consumer's role in co‐producing algorithmic gender bias in the marketplace and observe that consumers reinforce these biases by accepting gender stereotypes (i.e., clicking on biased ads). We conclude by discussing theoretical and practical implications.