SmileSeeker: Customer and Employee Affect Tagging System


SmileSeeker is a novel, machine-vision system that captures and provides quantified information about nonverbal communication where social interactions naturally happen. For example, in banking services, tellers observe facial expressions, head gestures, and eye gaze of customers, but this tool lets them both observe their own expressions and analyze how these interact with those of the customer to influence their mutual experience. The tool allows either real-time or offline feedback to help people reflect on what these interactions mean and determine how to elicit better experiences, such as true customer delight. The first deployment of this project focuses on eliciting and capturing smiles, and doing so in a way that is respectful of both customer and employee feelings. This project will also explore ways to share this information and link it to outcomes such as banking fee reductions or donations to charity.