How do we know that an advertisement or promotion truly drives incremental revenue? How do we match people to interventions to maximize overall utility? This talk will cover our experiences developing machine learning techniques for predicting treatment responsiveness from randomized controlled experiments and the use of these “persuasion” models at scale in politics, social good, and marketing.
