On digital platforms (or in physical settings) where customers arrive repeatedly, platforms must decide which options to offer them, as this influences their subsequent choices as well as the outcomes for both user and platform. This project will 1) classify customers on a digital platform based on their latent motivation (think: whether they're here to learn vs earn, or which out of several options is the primary emotion driving them) using deep mixture models, 2) predict consumer actions by using deep learning to estimate parameters of the consumer choice model, and 3) use reinforcement learning to select customer offerings/recommendations in order to optimize a long-term outcome.