Keywords: AI, Marketing Technology, Data Capture, Data Classification, Surveillance, Algorithmic Biases
The growing ubiquity of AI in consumers’ lives can be very convenient, but even if software developers and marketers strive to create excellent service, consumer experiences are not always positive. During their customer journeys consumers experience “data capture,” which is the experience of granting one’s data to AI, and “classification,” which means receiving personalized recommendations generated by AI. In both experiences consumers may either feel served or exploited and understood or misunderstood. To live up to the promise of making consumers happier and more efficient, managers should pay attention to consumers’ anxieties. If managers understand when and why consumers feel exploited or misinterpreted by AI, companies can provide more value for consumers individually and take concrete steps to design improved experiences around data collection and classification.