Learning from the Dark Web: Leveraging conversational agents in the era of hyper-privacy to enhance marketing - Thomaz, F; Salge, C; Karahanna, E; Hulland, J (Springer, 2019)
The Web is a constantly evolving, complex system, with important implications for both marketers and consumers. In this paper, we contend that over the next five to ten years society will see a shift in the nature of the Web, as consumers, firms and regulators become increasingly concerned about privacy. In particular, we predict that, as a result of this privacy-focus, various information sharing and protection practices currently found on the Dark Web will be increasingly adapted in the overall Web, and in the process, firms will lose much of their ability to fuel a modern marketing machinery that relies on abundant, rich, and timely consumer data. In this type of controlled information-sharing environment, we foresee the emersion of two distinct types of consumers: (1) those generally willing to share their information with marketers (Buffs), and (2) those who generally deny access to their personal information (Ghosts). We argue that one way marketers can navigate this new environment is by effectively designing and deploying conversational agents (CAs), often referred to as “chatbots”. In particular, we propose that CAs may be used to understand and engage both types of consumers, while providing personalization, and serving both as a form of differentiation and as an important strategic asset for the firm – one capable of eliciting self-disclosure of otherwise private consumer information.