Hundreds of millions of people leave digital footprints in public (e.g., social media/social networking sites and review sites). We are developing System U, which uses psycholinguistic analytics to automatically derive one's personality traits from their digital footprints. Such traits uniquely characterize an individual's psychological, cognitive, and affective style and properties, and can then be used to make hyper-personalized recommendations to individual to influence/intervene the actions of the individual. In this talk, I will give an overview of System U and describe how it automatically derives several types of personality traits from one’s tweets, including human basic value (one's belief + motives) and fundamental needs (e.g., ideals vs. practical). Moreover, I will present a set of validation studies that assess how accurate the System U-derived traits are compared to “ground truth” and how these derived traits actually influence recommendations and people’s behavior in the real world. I will also use live demos and concrete examples, ranging from precision marketing to individualized customer care, to demonstrate the applications of System U and discuss interesting research directions.