The rapid adoption of e-commerce by consumers has been fueled by the increasing number of goods available for online purchase and by the increasing availability of information on the characteristics and performance of these goods. However, this abundance of information and choice has cluttered online shopping environments. Consumers face an overwhelming number of alternatives to choose from and a profusion of information on each option, which reduce their motivation and ability to filter and evaluate products (Iyengar and Lepper 2000; Nagar and Gandotra 2016). Although product filtering and recommendation agents can lower search costs (Brynjolfsson et al. 2011), they tend to yield a narrower range of suggestions, thus making online shopping a tedious experience (Clune 2013; Darlin 2009; Herlocker et al. 2004). In addition, while powerful algorithms have enhanced the accuracy of the recommendations that shoppers obtain, such recommendations are often, by design, too predictable, which means that they overlook shoppers’ desire for the good surprises that can spark their engagement and satisfaction (Adamopoulos and Tuzhilin 2014; Matt et al. 2014). To address this concern, we explore the potential value of online shopping environments that cultivate serendipity, that is, the finding of unexpected but valuable product-related information. Online retailers increasingly value serendipity because it is a significant driver of consumers’ decision satisfaction (Yi et al. 2017), positive affect (Matt et al. 2014), and engagement (Sun et al. 2013). The concept of serendipity is relatively nascent in the Information Systems (IS) field, but several other fields (e.g., marketing, medicine, and engineering) have long recognized the important role it has played in various scientific contexts including the discovery of gravity, penicillin, and computerization (Anguera de Sojo et al. 2013; Kubinyi 1999; Roberts 1989; Van Andel 1994).