Michelle Y. Lu, Assistant Professor in Marketing, awarded 2019 SSHRC Insight Development Grant
What Happens When Amazon Knows Everything? Predictive Advertising in a Channel Relationship
Exploration and exploitation of consumer data are always at the heart of the polarizing debate on data analytics. These issues grow increasingly salient in the retail industry as today’s retailers have access to a copious amount of data that not only includes demographics, past purchases, search behavior, browsing history, wish list, cart abandonment, etc., but also real-time geo-location, consumption patterns and payments across a large set of consumers. One way that retailers are leveraging such enormous information advantage is through a new mode of “predictive advertising,” a strategy whereby retailers explore consumer data at a very granular level to discover consumer preferences, predict what product may be of a better match, and exploit this knowledge by advertising that product to a select group of consumers to increase consumer purchase intention. Despite the fast-pacing developments in predictive advertising, little work has been done to understand its strategic implications, let alone its consequences on consumer decision-making and welfare. This research aims to address these gaps in knowledge and shed light on policy implications.